SBNation.com User Blog: clack

Asking and Answering Questions

clack — Fri, 17 May 2013 17:58:29 -0000

"Inquiring Minds Want to Know" edition of Talking Sabermetrics

It's not alway fun following the Astros' performance this year. Indeed, you have to savor the sporadic wins. So, just for peace of mind, I will step back from the overall sabermetric stats for this Astros team. Instead I'll answer a few random Astros-related questions. The questions aren't necessarily sabermetric subjects, but they are susceptible to being answered with sabermetric data sources.

Question: The Astros' pitching has given up a lot of runs. But is this due to the high powered offenses that they have played so far this year?

Answer: In part, yes. I say, "in part" because I don't want to make excuses for the Astros' pitching. According to Baseball-Reference's pitcher player value statistics, the Astros have faced the second highest level of opponent offensive strength among American League teams. Only the Baltimore Orioles have faced better average offensive opponents this season. (See the "RA9opp" stat here.) On average, the Astros have faced opponent offenses which are 5% better than other AL teams. Unfortunately, this doesn't come close to erasing the 36% differential between the Astros' runs allowed and the AL's average runs allowed. (So much for keeping our peace of mind in these answers.) But if you had the hazy feeling that the Astros seemed to be pitching against a lot of good offensive teams, the stats back you up.

Question: Among starting pitchers in the majors, does Bud Norris have the biggest gap between Home and Road pitching performance?

Answer: Yes. Since the beginning of the 2012 season, Norris has an ERA of 7.07 on the road and 1.89 at home---a gap of 5.18 ERA between home and road. At home, Norris is the third best pitcher in baseball over that period, behind only Justin Verlander and Clayton Kershaw---but he is the worst pitcher in baseball on the road. The Pirates' James McDonald appears to have the second biggest gap between home and road for that period: 6.45 ERA on the road and 2.78 at home. McDonald's 3.67 gap between home and road ERA pales in comparison to Norris' 5.18 gap.

The gap between Norris' home and road FIP for the same period is 2.37, which also appears to be the highest among major league starters. But the fact that Norris over performs his FIP at home (ERA is 1.03 lower) and under performs his FIP on the road (ERA is 1.72 higher) suggests some luck in his H/R performance split.

For whatever reason, Norris has more pitches called balls on the road than at home (38% vs. 34%). Is his control worse on the road, or do umpires favor the home team in balls/strikes calls? I can't resolve that question, but the disparity in Norris' non-strikes thrown at home and on the road contributes to a significant gap in his strike out rate (24% vs. 18%) and walk rate (6.8% vs. 10.8%) at home and on the road.

Norris is also much more effective at controlling lefthanded hitters at home compared to the road. For the same time period, Norris held lefthand batters to a lower BABIP than righthand batters (.266 vs..288) at home. Overall for the period, Norris' home BABIP (.279) is much lower than his road BABIP (.335). But, perhaps more interestingly, Norris has a BABIP against lefthanders (.357) on the road which is almost 44 points higher than the road BABIP for righthand hitters (.313). To some extent, this may reflect Norris' ability to use Minute Maid Park's dimensions to suppress lefthanded batters, who seem to be Norris' nemesis on the road.

Question: Do the Astros' batters strike out so much because they are too passive?

This question, itself, may draw a "What?" exclamation. Normally we don't associate strike outs with patience. But, with rising strike out rates throughout baseball, we have seen some writers blame sabermetrics for making hitters too patient and too passive. Apparently, a rumor spread in scouting circles--perhaps because a number of scouts are hostile to Luhnow's methods--that the Astros are instructing hitters not to swing at 3-2 counts. (Luhnow responded that this rumor is incorrect.) As nonsensical as the question may seem, some people seem to draw a connection between the Astros' sabermetric inclination toward hitter patience and the team's high strike out rate.

The data would suggest a "no" answer to this question. The Astros may want more patience, but their hitters have not been patient. The Astros are ranked 11th out of the 15 AL teams in pitches/PA. The Astros lead the AL in swinging strike percentage and percentage of balls swung at, and are approximately league average in strikes looking and strike outs looking. The Astros have the third highest rate in the AL of swinging at the first pitch. The data suggests that the Astros are not passive at the plate, and, if anything, are too aggressive. The media's narrative about sabermetrics and passive hitters is not supported by the actions of the hitters on baseball's No. 1 strike out team.

Fangraphs has a couple of recent articles on this subject. David Cameron's "The Myth of the Passive Hitter" systematically responds to the claim that the rising strike outs are due to hitters becoming too passive at the plate. He makes the interesting suggestion that changes in the umpires' calling of the strike zone are to blame.

The Atlanta Braves are not far behind the Astros in strike out rate (Astros: 27%, Braves: 25%). That makes me glad, from a selfish perspective, because the media/commentators have focused on the Braves' strike out propensity in recent weeks. I was getting tired of the articles harping on the Astros' record-setting strike out pace. The Fangraphs article, "About the Braves And All Of Their Strike Outs," shows that the Braves have been productive despite the high K rate, and places the strike out issue in perspective. We expected the Astros to strike out a lot, but we hoped for a trade off of more power. Unfortunately, the power has not shown up to the extent we wanted. The Astros are 11th in the AL with an isolated power rate of .152. If the Astros had the same .172 ISO as the Braves, we probably could live with setting the major league strike out record.

Humber DFA'd-- Edgar Gonzalez Signed

clack — Sun, 12 May 2013 14:53:35 -0000

Philip Humber was designated for assignment (DFA) after a costly relief performance last night that cost the Astros the lead and ultimately the game--in addition to pushing his ERA above 9. This shouldn't be a surprise; few pitchers with an ERA over 9 at this stage of the season keep their jobs on a major league roster. With a 9.59 ERA, Humber has the highest ERA among MLB pitchers with 30 or more innings.

Edgar Gonzalez, who was DFA'd by the Astros in April after starting the season on the team's roster, was re-signed by the Astros and takes Humber's roster slot. He will be in the Astros' bullpen for this afternoon's game against the Rangers. Gonzalez who was claimed by the Toronto Blue Jays after the Astros' DFA, was subsequently DFA'd by the Blue Jays and assigned to Toronto's AAA team. Gonzalez later was called up to the majors by the Jays, and was subsequently released after three appearances for Toronto.

Jose Ortiz with chron.com said that Humber probably knew what was coming after his performance last night:

After giving up five runs over two-thirds of an inning Saturday night, Philip Humber sounded like a man who knew the end was near. All the signs were there, as I told Astros broadcaster Bill Brown immediately after Humber’s postgame media session.

“It’s hard, but there’s a lot worse things than struggling on a baseball field,” he said. “I feel bad as far the team goes. I want to do the best I can for the team."

Looking at pitch f/x from last night, Humber's velocity appears to have returned to the 91 mph range that he normally pitched in previous seasons. However, his command suffered, and the curve ball was not very effective.

The Astros signed Gonzalez out of the Mexican League last year and gave him 6 starts in the Astros' rotation at the end of the season. Although his 5.04 ERA was not anything to write home about, he did have his moments when he pitched well, and he appeared to be poised in tough situations. Gonzalez also pitched well in spring training and seemed to have pitched his way into the swing man role. However, a roster crunch led to the DFA, and the Astros were unable to sneak him back to Oklahoma City.

It's not surprising that the Astros re-signed Gonzalez. Given Humber's ERA, one can hardly expect him to be worse. But temper your expectations with the knowledge that Gonzalez has not pitched particularly well this year. He had a 5.49 ERA in 19 innings with Buffalo, and he has a 7.88 ERA in only 8 innings with Toronto. Gonzalez had two relief appearances against Detroit and one relief appearance against Tampa Bay. Most of the damage occurred in a 4.2 inning stint against the Rays, giving up 5 runs, 6 hits, 2 walks, 2 HRs, and a HBP. But this is a small sample size and may not signify much about the future. However, it does highlight the volatility of relief pitching in the majors.

Darin Erstad: The Angel and Astros Player

clack — Wed, 08 May 2013 10:12:21 -0000

When you think about players who are a part of both the Angels' and Astros' history, Nolan Ryan is the most well known name. But what about more obscure links between the Astros and Angels...like Darin Erstad. Erstad is legendary among Angels' fans as a foundation of the 2002 World Series champions. At the end of his career, he would serve as a role player on the 2008 and 2009 Astros.

The Astros have the first pick in the draft this year, and the Angels had the first pick in 1995. The Angels selected Erstad, a three sport player at Nebraska. Erstad was the starting punter on the football team; baseball was not even his primary sport. Here are some excerpts from scouting reports on Erstad before he was drafted with the first pick.

Physical Description: Ideal build. Lean and trim with good body strength. Well proportioned. Looks like and is an athlete. Bright blonde. Punter on football team.

Type Hitter: Real Good!!!

Summation: Very hard nose player. Definitely comes to play. Outstanding athletic ability. Can swing the bat and can hit with some power. Probably the best hitter in the country.

Erstad moved very quickly through the minors. He signed with the Angels in July, 1995, and less than one year later he was in the majors. Immediately after signing, he started in rookie ball and, 29 games later, moved up to A+. He was rated the No. 4 prospect in baseball by Baseball America after posting a 1.028 OPS in 1995. Erstad was 22 years old when he was called up to the majors in June, 1996. The young outfielder hit .284 with a .708 OPS in his rookie season.

Erstad has an unusual, though not unique, career pattern. Erstad's performance is highlighted by an extreme peak season in 2000. The peak age for hitters is around age 26 - 27. In Erstad's age 26 season, he posted 8.3 WAR, which is super star level. He batted .355 with a .951 OPS and 25 HRs. In no other season did he come close to those numbers. That's not to say he wasn't a good player in other seasons---but he was just a solid player. He had a second lower spike in WAR in 2002 with 6.4 WAR on that championship Angels team. He barely crossed the .700 OPS threshold that year, but accumulated the highest defensive WAR of any AL position player. Erstad was a great defensive player, with three golden gloves (2 in the outfield and 1 at first base).

Erstad was 34 years old when the Astros signed him as a free agent before the 2008 season. Erstad realized that his skill set had diminished and concluded that he would be a better fit as a role player in the NL. The Astros wanted an outfielder who could back up recently acquired Michael Bourn in CF and provide defensive replacement duties in LF and 1b. The Astros also made it known that they hoped Erstad would act as a mentor for Hunter Pence, who exhibited an all-out style like Erstad, but seemed to fall short of Erstad's baseball smarts. By all accounts, Erstad and Pence bonded well. Erstad also became the Astros' go-to guy for pinch hitting against RHBs.

Erstad had a surprisingly good season for the Astros in 2008. His overall batting line was not exceptional (batting average of .276 and OPS of .672). But he was superb in the clutch (not a bad trait for a pinch hitter), with a .343 batting average and .856 OPS with runners in scoring position. He also provided some defensive highlights in the late innings. I recall a "walk off defensive assist," when he threw from LF and cut down the tying run at the plate with 2 outs in the 9th inning.

His most memorable contribution in 2008 occurred after Carlos Lee--seemingly having his best season with the Astros-- broke his hand in early August. The Astros had begun to move into contention in the NL Central, and Lee's injury seemed like a fatal wound to the Astros' hopes. Erstad started almost every game in August, and was more than adequate in replacing Lee. He went on a 9 game hitting streak, moving his batting average up to .292 by the end of the month. In addition, Erstad provided a major defensive improvement in LF, demonstrating how defensive WAR can substitute for offensive WAR. (I'll skip September, since the impact of Hurricane Ike on the Astros' playoff hopes is a painful subject).

Unfortunately, by 2009, Erstad was close to toast--"in the toaster," to use a Keith Law phrase. Erstad's age 35 season with the Astros was bad (.194 batting average, OPS below .600), and he chose to retire at the end of the season.

Erstad currently is the baseball coach at the University of Nebraska. Some Angels' fans wonder if he will be the Angels' next manager.

Do walks without power translate to the majors?

clack — Wed, 01 May 2013 06:54:37 -0000

Outfielder Robbie Grossman and shortstop Nolan Fontana have intriguing minor league statistics which bring to mind the "Greek God of Walks" (Kevin Youkilis) made famous by "Moneyball." Coming up through the minors, Youkilis was described as "Barry Bonds without the superhuman power" and "an on-base machine" who lacks "overwhelming power."

The Astros recently called up Grossman to the majors. At the time he was called up, Grossman had posted a 19% BB rate, a 24% K rate, a .452 OBP, and .353 SLG to start the 2013 season. Grossman's career minor league statistics:

(BA/OBP/SLG/OPS) .282, .400, .425, .825

15.4% BB, 19.7% K, .143 ISO

ISO (isolated power) is simply slugging percent minus batting average. Grossman's ISO is almost exactly the same as Youkilis' minor league career ISO of .142. However, Youkilis showed more ability as a contact hitter with a 12% K rate in the minors, while Grossman is somewhat above average in striking out. One of the questions about Grossman's minor league stats is how the combination of above average strike out rate, high walk rate, and relatively low power will translate to the major leagues.

Given the sample size it may be unfair to categorize Fontana, who is only in his second professional season. However, Fontana's amazing career .480 OBP, so far, is consistent with his reputation as a high OBP player in college. But we really don't know where Fontana's power and strike outs will settle. Fontana's stats during his brief minor league career:

(BA/OBP/SLG/OPS) .272, .480, .414, .894

27.2% BB, 18.3 % K, .142 ISO

Although the stats, above, would suggest a very high walk rate accompanied by an above average K rate and below average power, Fontana is early in his professional career. So far in the California League, Fontana has exhibited a below average K rate (16%) and above average power (.198 ISO). However, we have to keep in mind the potential inflating effect of Lancaster on his power. My expectation is that Fontana will be a high walk rate hitter, but defining his strike out and power profile is premature.

Some baseball bloggers question the ability of "high walk rate, high K rate, low power" minor leaguers to sustain their productivity at the major league level. As a first step in examining this question, I will identify major leaguers who fit this profile.

MAJOR LEAGUE CAREERS

I used the Fangraphs' leaderboard filters to identify all major leaguers since 1980 with career hitting stats fitting the following profile: Greater than 10% BB rate, Greater than 20% K rate, and ISO rate less than or equal to .150.

Only 12 players fit this profile. Eight of the players are outfielders, two are catchers, one is a third baseman, and one is a first baseman. Two of the players have an above average career wRC+ : Padres 3b/OF Chase Headley (116) and current Astros' coach Dave Clark (102).

Some averages for this group:

11.6% BB, 22.3% K, .127 ISO, .338 OBP, .373 SLG, .318 wOBA, 93 wRC+

Headley is an attractive comparable player; we probably would be happy if Grossman and Fontana performed similarly in the majors. However, for the most part, players in this group carved out major league careers on the basis of defensive ability, which isn't surprising given the below average offense. With the exception of Todd Pratt and Dave Clark, all of the players exhibited good fielding WAR. The average career runs saved is more than +12.

I think it's reasonable to look at a higher ISO ceiling, given young players' potential for developing more power in the majors. I increased the filter parameters for ISO from .150 to .170 and the size of the group more than doubled, now encompassing 27 players. Besides Headley and Clark, the following players who fit the search criteria also posted above average offense as measured by wRC+: B.J. Upton (105), Austin Kearns (104), Mark Whiten (102), Dexter Fowler (107), Alex Avila (112), Jeremy Giambi (114), and Warren Newson (109). Also, I'm also not surprised to see Mark Bellhorn showing up in the group, since he is often mentioned as a moneyball-style role player on the Red Sox world series championship team. The averages for this group are, in most respects, better than the previous group:

11.9% BB, 22.7% K, .147 ISO, .341 OBP, .395 SLG, .327 wOBA, 96 wRC+

This higher ISO group is composed of six catchers, two third basemen, two first baseman, one 3b/OF, and 15 outfielders. With the criteria allowing a little more power in the group, plus defensive skill is no longer a requirement for most of these hitters to stay in the majors. Nine players in the group are negative fielders, and the average fielding component for the group is slightly below average.

Unless Grossman improves his power somewhat in the majors, my guess is that he will have difficulty securing a starting position in the outfield over his career. (But don't ignore the value of good 4th outfielders.) If Grossman can achieve an average ISO for outfielders (approximately .170), in addition to maintaining a high walk rate, he could be quite productive as a starter in the OF. Even with an ISO around .150, Grossman could develop into a Headley type outfielder if he is capable of maintaining a fairly high BABIP. (Headley's career BABIP: .338.)

Kevin Youkilis provides a good example of a high walk rate player who developed significant power while playing in the majors. Between 2006 and 2007, Youkilis increased his ISO from 149 to 165, and in the next year he posted a .257 ISO. Over his ML career, Youkilis has a .199 ISO. In the 2003 ESPN article linked earlier, Youkilis, the minor leaguer told the writer that his HR power would develop more fully in the major leagues---and he was right.

DO HIGH WALK RATE MINOR LEAGUERS SUSTAIN HIGH WALK RATES IN THE MAJORS?

The second part of my analysis is aimed at this question. You will occasionally hear some skepticism about minor leaguers who excel primarily based on high walk rates. Some people believe that the walk rates are unsustainable in the major leagues if the player has inadequate power or strikes out too much. Naturally, we would expect walk rates to decline somewhat as players move to a higher level. Kevin Youkilis became a high OBP player in the majors--but his walk rate was lower than his 18% BB average in the minors. But can these players sustain above average walk rates in the majors?

To examine this question, for the period 2006 - 2009, I identified the AAA players, 26 year old or less, who had a season with a walk rate higher than 10%, an ISO less than .160, and a strike out rate higher than 19%. Given the limitations of the time period for my data, I am not completely satisfied with this analysis. But we can examine the information, sparse as it may be, knowing that the results are not definitive.

I identified 11 players in the International League and Pacific Coast League who met this criteria. 27% of these hitters never got more than a cup of coffee in the majors. This is roughly similar to the 34% bust rate for AAA high walk rate hitters found in other studies. The remaining hitters in the group have exhibited the following walk rates and offensive performance so far in the majors.

(wRC+, BB%)

Daric Barton, 105, 14.3%

Brandon Boggs, 81, 12.8%

B.J. Upton, 105, 10.5%

F. Gutierrez, 88, 6.5%

Brett Gardner, 98, 10.9%

Gregor Blanco, 90, 12.2%

Justin Maxwell, 98, 10.7%

Michael Brantley, 95, 7.6%

Average: 95, 10.7%

As shown by the 10.7% average BB rate (compared to the AL average walk rate of 8%), the players largely maintained the ability to produce above average walk rates. Only Gutierrez and Brantley have posted below average ML walk rates. Gutierrez had not exhibited consistently high walk rates in the minors and probably doesn't belong on this list. Brantley's walk rate, though, appears to have regressed in the major leagues. The walk rates for the remaining hitters are similar to their minor league walk rates. It's worth noting that both B.J. Upton and Justin Maxwell developed more power, as measured by ISO, in the majors.

An 11 player sample is too small to draw definitive conclusions. At best, the results should be treated as "suggestive." However, the results seem to support the proposition that high minor league walk rates reflect a skill that translates to the major league level.

Your thoughts?

Cliff Johnson Gets Ticket to 'Bronx Zoo'

clack — Mon, 22 Apr 2013 00:04:59 -0000

The Yankees won World Series championships in 1977 and 1978. The daily controversies on that team make it one of the most colorful championship teams in baseball history, and led to the team's nickname, "The Bronx Zoo," as well as the ESPN mini-series, "Bronx is Burning." Owner George Steinbrenner cemented his reputation as a serial hirer and firer. Billy Martin fought his own players, and the players fought each other. The Astros gave their young backup catcher and slugger, Cliff Johnson, a ticket into this tempest, when he was traded in June, 1977.

JOHNSON'S ASTROS CAREER

The Astros drafted Cliff (Heathcliff) Johnson out of San Antonio Wheatley High School in the 5th round of the 1966 draft. At 6-4, 215, he was a tall catcher who also played 1b and outfield. In the Astros' minor leagues, Johnson had seasons with 33, 28, and 27 (twice) HRs. Johnson was given very brief exposure to the majors in 1972 and 73. At age 26, Johnson was called up to the Astros big league club for good in 1974. Johnson was used mainly as a back up catcher and 1b, as well as pinch hitter. He had 210 PA in 1974 and 350ish PA in 1975-76; he was on pace for about 400 PA when he was traded in 1977.

Johnson did not have a reputation as a great fielding catcher; he is one of those players whose best position is in the batter's box. Johnson's power hitting with the Astros was prolific, considering his limited playing time. Johnson has the 125th best career at bats per HR in baseball history--which is particularly noteworthy considering that he batted a significant amount of time in the Astrodome. In 1976, Johnson had 21 doubles in only 318 at bats. Johnson had a .842 OPS with the Astros, producing a 142 OPS+, which takes into account the lower run environment of the 70's. Johnson had a .972 OPS when he was traded in 1977. Those offensive numbers are so good that one wonders why the Astros couldn't figure out how to get him more at bats with the team.

On June 15, 1977, Johnson was traded to the Yankees for pitcher Randy Niemann, utility infielder Mike Fischlin, and a PTBNL, which turned out to be first baseman Dave Bergman. Niemann and Fischlin had brief careers with the Astros and Bergman was used as back up first baseman and pinch hitter for several years.

As a fan at the time, I wasn't really happy with the trade. Johnson had rare power on a team that needed power, and he always seemed to get big hits that won games or gave the Astros the lead in games. Looking back now, we can see that Johnson's HR rate per at bat was better than contemporary Astros sluggers like Jim Wynn, Lee May, and Bob Watson. Because batting average was considered the most important statistic at the time (and OPS had yet to be invented), perhaps the Astros undervalued Cliff, because of his .256 batting average. Johnson's excellence at drawing walks was underappreciated in that era: his OBP with the Astros was about 120 points higher than his batting average. He has the profile of a hitter who would be valued on the current Astros team.

In retrospect, the Astros may have been justified in looking at Johnson's age (29) and following the adage that it is better to trade a player too early than too late. They couldn't predict that Johnson would continue hitting productively through age 39.

JOHNSON'S 1977 - 79 SEASONS AS A YANKEE

Johnson joined a team with big names and big personalities like Reggie Jackson, Goose Gossage, Lou Piniella, Sparky Lyles, Ron Guidry, and Thurman Munson. So, it's no suprise that he was not well known or considered more than a role player. But, Johnson was an important part of that 1977 100 win team, hitting .296, .405, .606 in 56 games with a 171 OPS+. The Yankees were down 2-1 to the Royals in the AL Championship game and came back to win the series, 3-2, before defeating the Dodgers in the World Series. Johnson played a memorable role in the AL Championship series, hitting .400 with a 1.17 OPS, including 1 HR and 2 doubles in 16 PA. This NY Daily News link includes a photograph of Cliff Johnson sitting atop the lockers, watching the Yankees party after the World Series win. Johnson hit poorly during the 1978 season and received only 174 at bats. Johnson's offense appeared to be returning in 1979, hitting 20 HRs for the Yankees before mid-season. But a shower room incident with Goose Gossage would end his Yankees days.

JOHNSON'S FIGHT WITH GOSSAGE

This incident made Johnson famous. Johnson and Goose Gossage got into a fight in the showers in 1979; Gossage slipped and fell on his hand, breaking his thumb, putting the all star closer out of action for two months, and foretelling an end to the Yankees World Series string. By all accounts, Gossage and Johnson were friends and the "fight" started with the two player ribbing each other, but escalated to punches when Gossage questioned Johnson's hitting prowess in the National League. Steinbrenner was furious and fined both players. Not surprisingly, Johnson was traded to the Royals shortly thereafter. (Sports Illustrated link.) This incident probably received more attention because of the Bronx Zoo's reputation for fighting. Not only did Billy Martin frequently challenge his players to fights, but Steinbrenner, himself, would be accused of fighting a Dodgers' fan in the stadium elevator not too many years after this incident. Johnson, for his part didn't like being defined by the incident, saying that he was never a "pugilist."

A couple of interesting post scripts to the incident. This "don't mess with Heathcliff" link is funny, with a photo of Johnson talking to a Yankees pitcher who hit him with a pitch a few months after the trade. Reportedly, Billy Martin paid the pitcher $100 to hit Johnson after Cliff had launched a HR in the previous at bat. After he was hit by the pitch, Johnson would hit a second HR against the Yankees in a blow out win by the Indians. This USA Today article points out that Johnson hit a HR off Gossage in the 2001 Yankees Old Timers game. Gossage responded by hitting the next old timer with a pitch. Sometimes you can't make this stuff up.

SUBSEQUENT CAREER

Johnson is one of those sluggers whose career was extended by the DH. He would hit almost 200 HRs before retiring after the 1986 season; along the way, in addition to the Astros and Yankees, he played for the Indians, Cubs, Blue Jays, A's, and Rangers. He participated in post season games for the Blue Jays and A's. Johnson held the MLB career pinch hit HR record until Matt Stairs passed him in 2010. He lives in San Antonio.

Astros History: Ex-Mariner Mike Hampton Proves Himself

clack — Thu, 04 Apr 2013 18:24:16 -0000

I remember when the Seattle Mariners traded Mike Hampton to the Astros. OK, I don't remember the exact date, but Baseball-Reference tells me it was Dec. 10, 1993. What I do recall is that the trade seemed liked a head scratcher at the time. Hampton was a young (21) left hand pitcher who had only pitched 17 innings at a very young age (20) for the Seattle major league team, resulting in a 9.53 ERA. Hampton had an unremarkable minor league career, and he was unranked as a prospect.

The Astros traded Eric Anthony, a young outfielder whom Astros' fans viewed as the franchise's next big slugger. Eric Anthony had been ranked as baseball's No. 9 prospect by Baseball America before he reached the majors, and he had a career .919 OPS in AAA with monstrous HR power. Anthony was 25 years old, and had played several partial seasons with the Astros. He had not yet established himself as a major leaguer, but his 24 HRs over the 1992 and 1993 season made it appear that he was ready to do so.

I had this nagging feeling that the trade would come back to haunt the Astros. The only positive note was that the Astros' beat writer said that the Astros' scouts liked Hampton quite a bit. At the time, a casual fan might have assumed that Hampton's future would be as a left handed relief specialist. I was wrong about the trade. Hampton would become one of the finest starting pitchers in Astros history. Anthony? Well, he never became more than a back up outfielder.

In retrospect, the Astros and Mariners attempted an exchange of untapped potential. And the Astros took the younger player and won. And obviously what the Astros scouts and front office saw in Hampton was a left hand pitcher with a powerful sinker pitch that would produce ground out after ground out. Hampton would carry a low K rate (5.5 career average) throughout his career, which may be why he was undervalued as a young player. But the groundballs were the story.

Initially, the Astros used Hampton as a left handed reliever, where he compiled a respectable 3.70 ERA as a 21 year old in 1994. In 1995, the Astros converted him to a starter and he produced an even better 3.35 ERA in 150 innings. In 1997, after Larry Dierker was named manager, Hampton began to emerge as a young work horse starting pitcher, leading the Astros into the playoffs by pitching 223 innings. In 1998, Hampton had an ERA+ of 123, and was joined by another ex-Mariners' pitcher, Randy Johnson, on the Astros highest win (102) team. In 1999, Johnson was gone, and Hampton had a chance to shine as the ace of the staff. And he did. He compiled a 22-4 win-loss season, with an ERA+ of 142 in 217 innings. B-Ref's advanced stats tell us he produced an impressive 6.6 WAR. Unfortunately, the Astros lost to the Braves in the playoffs.

With the Astros failing to succeed in the playoffs for three straight years, and Hampton one year away from free agency, the Astros traded Hampton to the New York Mets for Octavio Dotel and Roger Cedeno before the 2000 season. Hampton led the Mets to a World Series that year, and then bolted to the Rockies for the 8th highest pitcher free agent contract in history (8 years, $121 million in 2001). Unfortunately for Hampton, he was pitching at Coors Field during its heyday as a hitter's park. His ERA suffered, not surprisingly, and after a series of trades, he ended up in Atlanta. Hampton's career with the Braves was plagued by a series of injuries and surgeries which left him with the injury prone reputation. Hampton returned to the Astros as a free agent in 2009, but arm injuries continued to hamper him, and eventually ended his season. A young prospect, Bud Norris, replaced Hampton in the Astros rotation. (See, the story connects us to the current team..and the wheel goes round and round.)

A couple of notable points about Hampton's career. First, he has considerable playoff experience, pitching in 11 playoff games (10 as a starter) with an average ERA of 3.74. Second, Hampton can be thankful he was traded to the National League by the Mariners, because he became one of the best hitting pitchers in the league. Hampton compiled 8.3 WAR as a batter. His career slash line: .246, .296, .356, .650. During his time in Colorado, he hit .315 and produced an .881 OPS.

The Astros and Mariners have had a number of notable trades. Some helped the Mariners more, and others were fairly even. But this one went in the Astros' favor.

Sabermetrics: More Stats, New Insights

clack — Wed, 17 Apr 2013 21:40:46 -0000

"Dammit, Jim, I'm a blogger, not an adding machine."--title of Feb. 10, 2010 Boston.com column

I realize that traditional baseball fans sometimes complain about too many statistics and numbers, particularly in the world of advanced metrics. But I think that's the wrong way to think about it. That's like saying there are too many words in our language. Maybe it would be simpler if a synonym didn't exist for almost every word. But that would wipe away a richness in our vocabulary, since each similar word conveys a different perspective or nuance. Similarly, the value of a statistic arises from the insight it provides. And different statistics can provide different insights about the game of baseball. So long as the stat is useful, isn't "more" a good thing?

With that background, let's talk about two statistical measures that add to our insight into baseball. The first topic discusses the under appreciated "RE24" statistic. The second topic addresses a unique way to compare pitchers. This takes us back to one of the original purposes of the Talking Sabermetrics column: explaining the use of particular advanced statistics in order to add to your enjoyment of the game.

RE24 Statistic

RE24 (short hand for run expectancy for 24 base-out states) is shown on Fangraphs' win value page. Frankly, I hadn't paid much attention to this component of the win value family of stats until recently. When Tango, co-author of The Book, says this is one of his favorite stats, I probably should be paying attention. RE24 won the "March Madness Tournament: Baseball Stats Edition" at Beyond the Boxscore, which swept a somewhat lessor known statistic onto the main stage.

What is RE24?

24 possible combinations of outs and base runners exist. (Examples of base-out states: bases empty no outs; runners on 1st and 3d, 1 out; bases loaded, 2 out, etc.) The value of particular hitting events (like walks, strike outs, singles, HRs, etc.) will vary for each base-out state, because the probability of a run scoring (run expectancy) after the event depends on the bases with runners and the remaining outs. For instance, a strike out has the same impact as any other out with the bases empty, but becomes much more damaging with a runner on 3d and 1 out. We could give examples for every other type of event from GIDPs to HRs. Hitting stats like wOBA and wRC calculate a player's offensive production by assigning a league average value to each type of hit or event. RE24 assigns a value to each event based on the event's impact on the actual, known base-out state. In particular, RE24 calculates the increase or decrease in the probability of run scoring based on the change in base-out state. Fangraphs explanation of RE24 is here.

You may be wondering how RE24 differs from other win probability stats like "Win Probability Added" (WPA) and "clutch." RE24 is based on run expectancy, rather than win expectancy. Significantly, RE24 is more context-neutral than WPA and clutch because it does not incorporate the inning and game score components of leverage.

Why is RE24 useful?

RE24 can be thought of as a middle ground between advanced stats and old school stats. If you like RBIs, this is the advanced stats' replacement for RBIs. Some traditionalists think that sabermetrics belittles productive outs and sacrifices. Well, RE24 gives credit for productive outs and successful sacrifices, just like it debits the player for a GIDP. In fact, RE24 takes everything into account in arriving at the change in run expectancy.

Tango goes so far as to suggest that RE24, accumulated over a sufficiently large career sample, may (arguably) be superior to wOBA and wRC in gauging the value of a hitter over his career. Tango's discussion of RE 24, here, is helpful in understanding the concept. Although I won't go into it in this article, RE24 can also be used to compare pitchers, and may be particularly useful in evaluating relief pitchers. As Tango points out in the article, above, RE24 is expressed as runs above league average.

As shown on the fangraphs leaderboard, the Top 5 career leaders in RE24 (for as long as the data is available) are: (1) Barry Bonds; (2) Frank Thomas; (3) Chipper Jones; (4) Albert Pujols and (5) Jeff Bagwell. (Hall of Fame voters, take note of the Astros first baseman.)

What does RE24 say about the current Astros?

The 2012 RE24 for Astros' hitter is shown here. Justin Maxwell led all Astros with 11.21 RE24, followed by Jed Lowrie and Jose Altuve. Obviously the 2013 stats are in small sample size territory, but the current leaderboard is here. Chris Carter, Jose Altuve, Carlos Pena, and Rick Ankiel (is Dave Cameron listening?) are the current leaders in RE24.

The Astros' high strike out numbers were a narrative early in the season. Nobody really knows what strike out rate is "too high." One of the criticisms of the three true outcome players on this Astros team is that the Ks take away the opportunity for productive outs or other positive things that come with contact. The other side of the argument points to the HRs that typically accompany strike outs. This debate is unprovable. Or is it? Perhaps RE24 can cut through the polemics and determine how much the hitters are contributing to run expectancy. What I like about this approach is that it focuses on the individual player, rather than making generalizations. And so far, hitters with 3 of the 4 highest K rates on the team lead the team in RE24, and produced higher than anticipated run expectancy. Despite a 35% K rate so far, Chris Carter has managed to be an American League Top 25 player in RE24 in the last week.

How is RE24 used to determine "added value?"

Runs Above Average (wRAA) reflects the average runs expected from a player's offensive actions compared to the average hitter. Comparing RE24 to wRAA shows whether the hitter produced more or fewer runs than expected by wRAA. For example, Justin Maxwell's 2012 wRAA was 4.1, which means that Maxwell's actual contribution to run expectancy (11.4) as measured by RE24 was 170% high than the runs expected based on his wRAA--which is an excellent ratio.

Remember the debate when Jim Rice was voted into the Hall of Fame? His supporters said his RBI totals made him a feared hitter. Some of the stat heads responded by pointing to his propensity to ground into double plays (GIDP), as well as his low walk rates. Fangraphs shows Rice with a total RE24 of 247, almost 40% less than his total wRAA of 394, suggesting that perhaps the double plays significantly reduced his run production below expectations. (Rice led his league in GIDPs for 4 consecutive years, and was among the league leaders in GIDPs in other years.)

Below I have identified the highest RE24 contributors to the Astros since 1990, and calculated the difference between the player's RE24 and wRAA. The Value Added Percent is the potential percentage increase or reduction in the hitter's runs above average if the player's performance during the 24 base-out states is taken into account.

	RE24	Net of wRAA	Value Added Percent
Jeff Bagwell	699	102	17%
Lance Berkman	520	87	20%
Craig Biggio	376	129	52%
Moises Alou	126	2	1%
Carlos Lee	89	16	22%
Hunter Pence	66	-3	-4%
Derek Bell	69	63	935%
Carl Everett	69	22	47%
Bill Spiers	60	41	216%
M.Ensberg	59	-13	-18%
Luis Gonzalez	54	43	377%
Ken Caminiti	56	38	205%
Mike Lamb	47	28	156%
Jeff Kent	45	6	15%

I doubt that you are surprised that Bagwell, Berkman, and Biggio are the leaders in RE24 by a wide margin. Among those three Astros' icons, Biggio has a significantly higher margin between RE24 and wRAA. This makes sense, given that Biggio was a tremendous situational hitter and virtually impossible to double up during his peak seasons. The differences between wRAA and RE24 may be more problematic as we move down the chart and sample sizes become less reliable. In particular, many of the part time players produced large percentage differences between RE24 and wRAA, which may reflect sample size issues. In addition, part time players may have been more likely to enter games with runners on base. Bill Spiers, a super utility player, accumulated a RE24 far higher than the run production predicted by his wRAA. Undoubtedly this is why Spiers was prized as a pinch hitter. The extreme margin between Derek Bell's RE24 and wRAA is not easily explained. Apparently Bell was only somewhat above average as a hitter---except for hitting in base-out states when he could do the most damage.

Pitcher Similarity Scores

Just a short piece on pitcher similarity scores. Stephen Loftus at Beyond the Boxscore has developed pitcher similarity scores to compare pitchers based on their pitching arsenal. He uses pitch f/x data to identify comparable pitchers based on the following parameters: pitch velocity, pitch break (horizontal and vertical), pitch location, and pitch release points. He applies his method to a sample of pitchers in 2012, and arrives at most similar and least similar pitchers.

I have waded through his spreadsheet to find the most comparable pitchers linked by similarity score to current Astros pitchers. So, without further ado, here are the most similar pitchers:

Travis Blakely: Bartolo Colon

Lucas Harrell: John Lester, Zach McAllister, Luis Mendoza.

Phil Humber: Jeremy Hefner, Chris Volstad, Wade Miley, Dillon Gee.

Bud Norris: Christian Frederich, Tyson Ross, Jarrod Parker.

Jordan Lyles: Gavin Floyd, Matt Cain, Ivan Nova.

Dallas Keuchel: Jason Vargas.

All of these scores meet Loftus' criteria as "very similar." Lyles' similarity to Gavin Floyd was the highest score among these pitchers. And, how about Matt Cain as a comparable to Lyles? We can only hope that Lyles will be similar to Cain. Hopefully Lyles gets it together in Oklahoma City and returns to the Astros in the near future.

Bartolo Colon as a comparable to Blackley is slightly surprising. Perhaps it's more indicative of Colon's current state.

I can see Norris and Parker as similar pitchers. Frederich and Ross? I don't know enough about them to say.

Are you surprised by the results of these similarity scores? Is this a good way to compare pitchers' "stuff?" Do you see any good uses for this type of metric?

Wednesday Astros' Three Things...

clack — Wed, 10 Apr 2013 17:53:02 -0000

Some musings while I sub for David Coleman and wonder if the Astros' offense can continue its break out...

1. The Astros' buffet includes some interesting articles to dine on today.

Richard Justice responds to the national sports media's bashing of the Astros' lineup and payroll, putting up a spirited defense of the Astros' long term plan. Of the bashers, Justice says, "These are the guys who won’t read Moneyball, think Billy Beane is anti-American and believe a ThinkPad is something used to cover a barstool." Justice believes that Astros' fans are more understanding of the Astros' game plan then the national media, most of whom ignore how the Astros got to this point. Justice gets it.

At the Houston Chronicle, Randy Harvey has interviews with Astros' prospects Delino DeShields, Jr. and Mike Foltynewicz. Both prospects were hoping to be assigned to AA to begin this season, but both recognize that the Astros have a plan for them, even if it means playing in A+ Lancaster right now. Broaching the sensitive topic that Altuve is the incumbent 2d baseman in Houston, Harvey said there was some speculation that DeShields was held back at Lancaster in order to change positions. But Lancaster manager Rodney Linares dashes that thought, saying that his instruction is to prepare DeShields to play 2d base in the major leagues.

Linares also makes an intriguing prediction. "I love Tropeano and some of the other great arms in the organization," but he says Folty has all the stuff to become a true No. 1 pitcher. (Check out both articles for more interesting quotes from the interviews.)

This all sounds good. Now we need to see Folty fight the Lancaster headwinds and pitch more deeply into his games.

2. Astros Prospects Get Off To Walking Start.

Most of you know how important walks are to the moneyball philosophy embraced by Luhnow & Co. Until last night's game, the Astros' major league offense had been woeful in the walks department.

But the deeper roots for the Astros' future growth are in the minor leagues, and some Astros' prospects have been outstanding in taking walks. Sure, we have the small sample size caveat, but its nice to see players get off to a good start in patiently working their plate appearances.

Robbie Grossman is an outfielder who may be closest to getting to The Show this year, and he has jumped out to No. 7 in walk rate (22%) in the PCL. Yes, the absolute percentages will regress, but Grossman has the reputation for drawing walks.

Looking at the AA Texas League walk rates, outfielder Austin Wates is 5th in walk percentage (22%), and his outfield mates Domingo Santana (16%) and George Springer (15.4%) are 11th and 12th. Yes, Santana and Springer still strike out a bunch, but the walks are welcome.

You probably already know about Lancaster shortstop Nolan Fontana's astro-nomical walk rates. He has a 25% walk rate and a .583 OBP so far in the early going. Just to give you an idea about the craziness of the California League offensive environment, Fontana isn't even leading the league. Fontana's walk rate is only 4th in the league, and his OBP is 2d in the league. Again, while the absolute rates will regress, Fontana's walking ways are consistent with his reputation.

In the Midwest League, first round draft pick Carlos Correa's walk rate of 21.9% is 9th in the league. It's early, and we should be cautious in reaching conclusions about his plate discipline. But what's exciting is that Correa is showing such patience at 18 years of age.

Why do I bring this up? As I discussed in a previous article, based upon research by Chris St. Johns, prospects' minor league walk rates begin to show predictive ability for hitters' major league success at A level, increasing in importance at successive minor league levels. A high walk rate increases a prospect's odds of major league success by 12% - 30% (depending on level), compared to the odds of low walk rate minor leaguers.

3. Astros Starting Pitchers

Will Erik Bedard become a free agent gem for the Astros? So far, he has pitched really well. It's hard to do much better than a 0 ERA. He pitches deliberately, with a low 90's fastball and a nice slow 77 mph curve ball. He retired early last night because he was on a strict pitch count, after pitching sparingly in the spring. And that's part of the rub. He was injured in the spring; and injuries have been his curse in recent years. One has to wonder if he will be confined to 5 or 6 inning starts this year in order to limit the potential for injury. (Cue the speculation about tandem pitching creeping into the major league level.)

Overall, the Astros starting pitching has produced fairly good results. The Astros starters' ERA is 8th in the AL. But we know that ERA may not tell the whole story. The peripherals should make us a bit more cautious. The FIP is more than a full run higher, putting the Astros' rank at 12th. The Astros' rotation has the second lowest BABIP (.252) in the AL, which suggests some room for upward regression in the ERA. Given the sample size this early in the season, we shouldn't draw any conclusions. But caution should be the watch word.

In addition, injuries continue to chip away at the Astros' starting pitcher depth. Subber10 tells me that John Ely was put on the DL for an elbow injury. I don't know the seriousness--keep an eye out for Subber10's updates. Remember when we had comments here at TCB that the Astros had compiled too much starting pitcher depth in AA and AAA? This shows you why teams can't have too much starting pitcher depth.

Are you worried about the depth of the Astros' rotation? Do you think that the recent injuries will make the front office more reluctant to trade a pitcher like Norris?

Astros Young Guns: Will They Break Out?

clack — Tue, 26 Mar 2013 03:56:05 -0000

Never let the odds keep you from pursuing what you know in your heart you were meant to do.

---Satchel Paige

The Astros will have a number of young players on their major league roster who are still waiting for their big break out. Brett Wallace, Matt Dominguez, Jason Castro, Chris Carter, Brad Peacock, Alex White, and Jordan Lyles were all Baseball America Top 100 prospects who have played in the majors. Yet all of them are still waiting to post their first 2 WAR season---a benchmark for becoming an average major league player.

What are the odds that these young players will have a break out in the future? Luckily, Chris St. John provides us some data to answer that question, with the article "When Do Prospects Break Out?" at Beyond the Boxscore. For players on Baseball America's Top 100 prospect lists, he calculated the year-by-year probabilities that players will break out with 2 WAR, 4 WAR, and 6 WAR seasons, corresponding to average, all-star, and elite players.

St. John's uses two different measures for the timing of break outs: (1) number of years since the player last appeared on a Baseball America Top 100 list; and (2) the player's age. These distinctly different measures of duration do not produce the same results. For example, two players may have played the same number of years at the major league level, but at varying ages. Because I don't know which measure is most representative of the timing for prospect break outs, I have used an average of the two methods.

Using the data in St. John's article, I tabulated the remaining probability that each of eight Astros players, above, will achieve a 2 WAR, 4 WAR, and 6 WAR season in the future. This isn't a prediction for next year, but rather an estimate for any year in the future. The tables below show the remaining probability of achieving the break out using the age and listing year criteria, and the average of the two criteria. This probability, of course, is a general estimate based on averages for Top 100 prospects. Obviously it doesn't take into account individual player characteristics which could increase or decrease the odds that the player will break out.

	Probability of 2 WAR Season
			2 WAR	2 WAR	Average
Hitters	Age	BA 100 Year	Age	Years	Probability
Wallace	25	2010	20.1%	15.6%	17.9%
F-Mart	23	2010	42.9%	15.6%	29.3%
Dominguez	22	2011	51%	30.2%	40.6%
Castro	25	2010	20.1%	15.6%	17.9%
Carter	25	2011	20.1%	30.2%	25.2%
TOTAL			154.2%	107.2%	130.7%
Pitchers
Peacock	24	2012	20.8%	36.6%	28.7%
White	23	2011	40.5%	20.8%	30.7%
Lyles	21	2011	47.5%	20.8%	34.2%
TOTAL			108.8%	78.2%	93.5%
TOTAL--Batters and Pitchers			263.0%	185.4%	224.2%

	Probability of 4 WAR Season
			4 WAR	4 WAR	Average
Hitters	Age	BA 100 Year	Age	Years	Probability
Wallace	25	2010	13.1%	17.4%	15.3%
F-Mart	23	2010	24.1%	17.4%	20.8%
Dominguez	22	2011	28.6%	22.6%	25.6%
Castro	25	2010	13.1%	17.4%	15.3%
Carter	25	2011	13.1%	22.6%	17.9%
TOTAL			92.0%	97.4%	94.7%
Pitchers
Peacock	24	2012	15.4%	17.3%	16.4%
White	23	2011	18.7%	15.8%	17.3%
Lyles	21	2011	24.7%	15.8%	20.3%
TOTAL			58.8%	48.9%	53.9%
Batters and Pitchers Total			150.8%	146.3%	148.6%

	Probability of 6 WAR Season
			6 WAR	6 WAR	Average
Hitters	Age	BA 100 Year	Age	Years	Probability
Wallace	25	2010	12.1%	12.5%	12.3%
F-Mart	23	2010	15.7%	12.5%	14.1%
Dominguez	22	2011	18.6%	13.1%	15.9%
Castro	25	2010	12.1%	12.5%	12.3%
Carter	25	2011	12.1%	13.1%	12.6%
TOTAL			70.6%	63.7%	67.2%
Pitchers
Peacock	24	2012	5.8%	6.6%	6.2%
White	23	2011	6.8%	6.6%	6.7%
Lyles	21	2011	8.1%	6.6%	7.4%
TOTAL			20.7%	19.8%	20.3%
Total--Pitchers and Batters			91.3%	83.5%	87.4%

CONCLUSION

An initial observation is that the Astros' pitchers and batters have different patterns for probability of success. On average, compared to the position players, the pitchers are more likely to achieve 2 WAR, just as likely to achieve 4 WAR, and less likely to achieve 6 WAR. In part, this reflects the fact that the average age of the pitchers is younger than the batters. Why are the pitchers less likely to become 6 WAR players? This reflects a tendency noted by St. John: truly elite pitchers become apparent at an earlier age than batters. The distribution of 6 WAR seasons for batters reflects a wider age range.

Matt Dominguez has the highest probability of success among the eight players. Jordan Lyles has the highest probability of success among the pitchers. In both instances, this is purely based on Dominguez's and Lyles' young age. They both have more remaining time in their career, compared to the other players, to achieve success.

I also calculated total, or cumulative, probabilities for all of the hitters, pitchers, and both hitters and pitchers. Hopefully I'm not bending probability concepts too much to reach the following conclusions:

A high probability exists that at least 2 of the 8 players will achieve a 2 WAR season in the future;
A high probability exists that at least 1 of the 8 players will achieve a 4 WAR season, and a reasonable probability for 2 players to achieve that level;
A moderately high probability exists for 1 of the 8 players to achieve a 6 WAR season in the future.

On the other hand, the probabilities of success for individual players may be sobering for hard core fans of the player. In general, the probability of success in the range of 2 - 4 WAR, is less than 1 in 5 for each player--much less for some. (F-Mart and Dominguez have a probability around 1 in 5 to achieve 2 WAR, though.)

If you are wondering why I haven't included players like Altuve, Harrell, or Maxwell in this analysis, keep in mind that the data is based on players on the BA Top 100 prospect list, and those players were never included. There is ample reason to believe that the blue chip prospects may experience a different timing pattern than other prospects. It's worth noting, though, that Altuve, Harrell, and Maxwell have already exceeded the 2 WAR threshold.

Any thoughts? Is this more or less optimistic than what you expect?

Talking sabermetrics: Astros and extra innings

clack — Sun, 17 Mar 2013 22:31:16 -0000

"The future ain't what it used to be." --Yogi Berra

If Bo Porter wants to look for a place to improve the Astros, an easy place to start is winning extra inning games. The Astros had a 1-11 record (8% W/L) in extra inning games last year. Maybe the manager has some influence on winning close games and extra innings affairs. But I suspect that the Astros could gain 3 or 4 wins in extra innings next year without Bo doing anything special. That's called regression or reversion to the mean--something we say a lot in the talking sabermetric series.

Last month, I wrote "The Astros and the Plexiglass Principle," which discussed the general tendency of teams at the extremes of W/L record to regress in the direction of a .500 record. This article follows up on that discussion with a more specific look at 1 run games and extra inning games. Let's parse, dissect, and reconstruct the 2012 season in search of potential improvement in 2013. (Why? Well, that's what we do.) If you have been reading this column in the past, you know that a team's Pythagorean Record is a formula predicting the W/L record based on a league average distribution of runs scored and runs allowed across the season. W/L records in 1 run games and/or extra inning games can skew a team's ability to meet it Pythagorean expectation (Note that the Astros W/L record in 2012 underperformed the Pythag Record by 4 games.)

Background: One Run Games

Thanks to the outlier of outliers--the 2012 Baltimore Orioles--with the highest win percent in 1 run games (29-9 or 89%) in MLB history, we have seen some recent debate about the repeatability of 1 run margin W/L records. Blake Murphy's Beyond the Boxscore article, "One Run Game Performance is Unsustainable," puts to rest the idea that an extreme winning percent in 1 run games is a repeatable skill. For teams comprising more than 2.300 MLB seasons, he examined the ability to predict 1 run game records based on the previous season's record for 1 run games. He found:

Team record in 1 run games has no explanatory power for the next year record in 1 run games (R-squared less than 2%). Year to year records in 1 run games are basically random.
Teams with a presumed elite ability to win 1 run games (i.e., very high win percents in those games) regress toward .500 records to the same extent as other teams (R-squared of 1.2%).
A team's overall Pythagorean Record has only a minor effect on explaining the regression in 1 run game records (R-squared of 9%). With explanatory power that small, perhaps we should expect regression to .500, rather than the team Pythag winning percentage.
Bullpen FIP has some explanatory power for 1 run game records, but it is small (R-squared of 11%).

Extra Inning Games

Since most extra inning games are won with 1 run, extra inning games are practically a sub set of 1 run games. Not surprisingly, team winning percentages in 1 run games was reasonably correlated with extra inning win percent in 2012 (I found a 27% R-squared).

The Astros' winning percent (39%) in 1 run games in 2012 was relatively close to the Astros' overall Pythag Record. However, based on runs scored and runs allowed in 1 run games, the Astros under performed; the Pythag formula predicts a 47% winning percent. Given that 1 run games, by definition, have a small margin between runs scored and allowed, we shouldn't be surprised that the Pythag predicts close to a .500 record in those games. In fact, this should give us some insight as to why we should expect teams' 1 run game winning percents to regress to .500.

However, the Astros had an extreme record in extra inning games (8% winning percentage), which is much lower than what we would expect from the Astros' runs scored and allowed in extra inning games (40% winning percentage, according to Pythag formula). The Orioles had the best win percent in extra inning games (16-2 or 89%), and the Astros had the worst. By all appearances, the Orioles were very lucky in extra inning games and the Astros were very unlucky. The Orioles shocked the projection systems by winning the AL wild card...and the Astros won the first pick in this year's draft.

In order to conjecture about the possible causes of 1 run and extra inning records, I examined whether player clutch performance, as measured by fangraphs' clutch stat, can explain the differences in teams' win percents for both types of games in 2012. The clutch statistic is based on the win probability family of stats, and reflects the extent that a player's performance in a season was better or worse in high leverage situations than his normal performance. (This stat is not measuring players' or teams'overall talent levels.) I summed each team's batting and bullpen clutch stat to arrive at an overall clutch measure applicable to late and close games, as well as examining batting and bullpen clutch stats separately. I used R-squared as a test of explanatory power.

My results:

1 Run Games

The combination of batting and bullpen clutch explained most of the variation in 1 run game win percent (R square of 64%).
Examining batting and pitching clutch separately, both components influence the 1 run game record (.32 and .42 R squared), but bullpen clutch performance is the bigger influence.

Extra Inning Games

The sum of batting and bullpen clutch explains a significant amount of the difference in extra inning game win percent (30% R squared), but not to the same extent as 1 run game records.
Batting clutch has virtually no impact on extra inning records (3% R squared), but bullpen clutch explains a lot of the variation in extra inning win percent (45% R squared). Compared to 1 run games generally, extra inning games are more influenced by bullpen clutch performance.

The conclusion that clutch performance influences 1 run and extra inning performance tells us some of the "why" behind over- and under- performance, but it doesn't tell us that the performance is sustainable. In fact, it's probably just the opposite. Studies have repeatedly indicated that a player's "clutch" timing of his performance is more luck than skill. My plexiglass principle article discussed the tendency for teams' WPA and clutch performance to regress toward average.

Manager Influence on Extra Inning Games

In terms of strategy, the extra inning game is different from the typical 1 run game. In regulation games, managers usually manage toward winning the game in 9 innings. In extra inning games, the manager often is left with a small remaining group of relievers and no certainty on how much longer the game will last. This tends to magnify the importance of bullpen management during the extra inning affair. Similarly, tactical offensive tendencies, such as sacrifices, probably receive more scrutiny in extra inning games. Therefore, we assume, with some degree of logic, that managers have more influence over extra inning games than regulation games. However, we have no way to measure whether this effect is noticeable or significant.

Last season, commenters in game threads sometimes suggested that Brad Mills' bullpen management was responsible for the poor extra inning record. But should we put much credence to those criticisms, considering that the manager gets blamed for a lot of stuff he doesn't control? Accordingly, I reviewed the box scores of each of the Astros' extra inning games to see if we can observe a common bullpen usage pattern.

I expected to see a pattern of extra inning losses falling on end of the bench pitchers, which might reflect poor bullpen depth and possibly ineffective management. But that wasn't the case. Only 3 of the 11 extra inning losses were attributed to middle relievers. In large part, the failures can be attributed to late inning relievers--the part of the bullpen that the Astros viewed as most reliable. And only one of the losses involved a real end of the bench reliever (Storey). The reliever (Lopez) who achieved the Astros' single win in extra innings didn't cover himself with glory, blowing the save before winning the game.

Interestingly, none of the losing pitchers remains on the Astros' roster. (Should that give any comfort to Bo Porter? Who knows?) Here are the losing pitchers:

Brett Myers: 3 losses in 0.2 IP

David Carpenter: 2 losses in 2.2 IP

Brandon Lyon: 2 losses in 1 IP

F. Rodriguez: 2 losses in 1 IP

Wilton Lopez: 1 loss in 2 IP

Storey: 1 loss in 2 IP

One surprise is that the closer, Brett Myer lost the most extra inning games. And the three losses only required 2/3 of an inning. In these extra inning games, Lyon came into a tie game and immediately couldn't get outs. If there is a pattern, it is that Mills held Myers back in regulation tie games and saved him for extra innings. But he didn't wait until the Astros had a lead in extra innings to use Myers. Does this support the theory that you shouldn't bring a closer into a non-save situation? That's hard to say. Maybe it affected this particular closer, but wouldn't affect other closers. Myers said he was puzzled by his usage after one of the extra inning losses; so maybe it got in his head. Or maybe that is just rationalization on Myers' part.

In general, it doesn't appear that the problems arose because a reliever had to pitch too many innings in extras. Only Storey and Lopez had 2 inning stints, and that wasn't unusual for their typical usage. In most cases, the losing extra inning pitchers ran into immediate trouble and lasted less than an inning.

Really, it seems like the Astros' extra inning record leans more toward bad luck than managerial usage. Perhaps a "closer by committee" approach might help in the future, if it prevents relievers from letting up in non-save situations.

It will be interesting to see how Bo handles the bullpen, but in any event, I think the Astros are likely to revert to more normal W-L results in extra innings.

Astros make new round of spring cuts

clack — Sun, 17 Mar 2013 13:41:49 -0000

The Astros cut 10 from the major league spring camp, sending the players to the minor league camp. Through a combination of minor league assignments and use of options, the Astros cut the following players: (reassigned) Che-Hsuan Lin, Carlos Perez, C.J. Fick, Josh Zeid, Sergio Escalona; (optioned) Robbie Grossman, Jimmy Paredes, Jonathan Villar, Paul Clemens, and Dallas Keuchel.

I don't think any of these cuts qualify as significant surprises. Fick, Escalona, and Keuchel seemed to have an outside chance at making the ML pitching staff, but it appears that both will be OKC bound, where they will be a phone call away from Houston. Grossman, Paredes, and Villar got in some good playing time with the major leaguers, but they have always been expected to start the season in Oklahoma. Lin had only a little time in camp, because he played on the Taiwan WBC team, but he generally has been viewed as AAA depth for the outfield.

This round of cuts seems like a good sign for Chia Jen Lo, who was a long shot to make the team going into to spring training, but has pitched very well. Given that some other viable relievers were cut in this round, Lo obviously is getting a good look.

Noting that the end of spring camp is only a couple of weeks away, GM Jeff Luhnow said:

"We got to get down to 25. Pitchers are going longer in games. We’ve got less innings to dole out. We want to see our position go a little deeper and have a few more at-bats as well. At lot of these guys we’re sending down today have a bright future in our organization. They know they’ll be back.”

Any thoughts?

Astros' best players in franchise history...

clack — Mon, 11 Mar 2013 15:48:25 -0000

The web site "Hall of Stats" uses a sabermetric approach to evaluate the the Hall of Fame worthiness of every player. The methodology is based on an adjusted version of WAR (wins above replacement) and WAA (wins above average). Hall of Stats recently provided franchise pages, ranking all of a franchise's best players. Here is the link for the Astros' page.

Certainly there are no surprises at the top: Bagwell, Biggio, and Cedeno are the three elite players in Astros' history, with Bagwell holding an overwhelming lead at No. 1. Perhaps Roy Oswalt at No. 4, and ranking as the best pitcher in Astros' history, might surprise some people. I have argued in some previous posts that Oswalt is the all time best pitcher in Astros' history. It also might be surprising that Nolan Ryan is only No. 14 on the Astros' list. Of course, this brings up the point that the rankings are based only on the players' contribution to the Astros.

One thing that is noteworthy to me is the low rankings at the catcher position. Joe Ferguson, who played only a few years in Houston, is the top ranked catcher (followed closely by Ashby). Ferguson is the 60th ranked Astros' player, which tells you how weak the catching position has been over the years. I have followed the Astros for many years, and this is consistent with my observation that the team has experienced poor luck at the catcher position. The Astros always seem to be searching for that franchise quality catcher, but never succeed. They drafted catchers with the first round draft pick (Robbie Wine was the No. 6 overall pick in 1983), they traded significant players for catchers (Milt May, Ferguson, Ed Taubensee), and despite all of that, they never really had an elite catcher.

Any thoughts on the all time Astros team? All I can say is that is a helluva bench.

Sabermetrics: Acquiring HR Hitters

clack — Thu, 07 Mar 2013 09:26:12 -0000

Have you noticed the Astros' proclivity for acquiring low batting average power hitters? Justin Maxwell, claimed off waivers last year, is the likely starting center fielder. The Astros traded for Chris Carter and signed free agent Carlos Pena. Matt Dominguez and Tyler Greene, possible starters at 3b and shortstop, potentially fit the same profile.

Indeed, the Astros' competition for the DH-LF-1b positions reflects a surplus of big, slow footed power hitters. Pena, Carter, Rule 5 draftee Nate Freiman, waiver claim Brandon Laird, J.D. Martinez, and Brett Wallace all fit the position of power hitter.

The most obvious explanation for this trend is that the Astros are moving to the American League, with its DH and power hitting lineups. However, a recent fangraphs article by Steve Staude on team specific hitter values led me to think about a possible sabermetric linkage to constructing the Astros' offense. Simply stated, these hitters may hold more relative value for the Astros than other teams.

Team Specific Runs Scored

Staude's fangraphs article discusses the use of a mathematical system called "Markov chains" to produce more accurate estimations of the run impacts of each type of hit, walk, K, ground out, etc. Thankfully--for both you and me--this article is not aimed at describing the complexities of Markov or linear weights concepts. (If you want to go to the deep end of the pool, read Staude's three part series at fangraphs.) The high level summary: Staude's Markov estimation of runs scored reflects the interaction of various offensive events based on the specific team. In effect, the resulting run impact simulates a typical game for the team.

When we estimate the runs produced by a hitter using wOBA or wRC, the estimations are based on an average team. But the actual impacts may be different for an offensive team which is substantially above- or below- average. Basically, because of the team synergies, good offenses are more productive at converting hits and walks into runs and bad offensive teams have more difficulty producing runs from the hits and walks.

Now, we can get around to the types of hitters who might help the Astros' offense. High OBP players are relatively more valuable to good offensive teams. HR hitters are relatively more valuable to bad offensive teams. A single or walk has relatively more value to a high OBP team, because these events have a higher probability of driving in and scoring runs. A HR has relatively higher value for the low OBP team because it guarantees run scoring in an environment of scarce runs.

Staude provides a common sense explanation in the first article in his series:

The more runners that are on base, the more value any subsequent hit has, all else equal, as there are more RBI opportunities...

If the team has a very high OBP, it will be able to sustain longer rallies, and will therefore be less dependent on the home run to score runs (i.e., singles, walks, etc. will be more valuable relative to the home run, compared to low OBP teams).

In a low-OBP team, however, while a home run is likely to score fewer runs than it will in an otherwise similar high-OBP team, the value of a home run relative to other hit types will be greater, as the team will be less likely to rally.

Digging even deeper, if a team hits a lot of home runs, the average value of a home run actually drops, due to more runners having been cleared from the bases by previous home runs.

Where do you think the Astros fit on the good or bad offense continuum? The Astros were 28th in OBP. The Astros were next to last in wOBA and wRC+ (only the Cubs were worse). The Astros were dead last in scoring runs--and by a considerable margin: the Astros scored 583 runs compared to the 29th ranked Marlins' 609 runs. Astros' base runners had a very low probability of scoring. In short, the Astros' offense was really bad. Therefore, the low batting average power hitters may be flawed, but they are more attractive to a team that produces as few runs and base runners as the Astros.

That's not to say that a high OBP, high batting average, low strike out, 30 HR hitter wouldn't be more valuable to the Astros. But the last time I looked, Albert Pujols and Miguel Cabrera were under contract with price tags of $240 and $152 million, respectively. But, given their (for the most part) defensive limitations and batting flaws, whether it be batting average, strike outs, or both, the power hitters acquired by the Astros are inexpensive--and they are relatively more valuable to the Astros' offense than to a high octane offensive team.

Chris Carter Example

The fangraphs article provides a helpful spreadsheet for estimating R/G based on Markov. The average difference between actual R/G and Markov R/G estimates is less than 1%, but the average difference using the Runs Created formula is 8%. By that measure at least, the Markov estimation seems to be more accurate.

Let's use Chris Carter to illustrate how Staude's Markov-based spreadsheet can be used. I started out with the 2012 Astros offense R/G (the spreadsheet includes all 2010 - 2012 team offenses).

The following 2012 offensive players, whom are no longer with the Astros, seem like hitters that would be part of the DH-LF-1b triangle if they had remained with the team: Moore, Pearce, Francisco, Buck, Downs. They combined for 601 at bats in 2012. (In a sense, these are actual, rather than theoretical, replacement level players.) I removed those players' offense from the Astros' 2012 batting statistics, and replaced their offense with 601 at bats by Chris Carter. In performing this step, I scaled Carter's offensive output in proportion to the ABs and PAs of the combined replaced players.

For illustration, I use Carter's Steamer projection as the baseline for calculating R/G impact. (Steamer projects Carter with a .247, .333, .471 slash line.) For an optimistic scenario, I scaled up Carter's 2012 offensive performance with the A's. In 2012, his slash line was .239, .350, .514. This is optimistic, given the combination of small sample size and likely favorable platoon situations associated with his actual 2012 performance. But we can be like John Sickels and hope that Carter will have a real break out season as a full time player.

Here are the Astros' Markov R/G estimate changes:

Markov Runs Per Game

Astros 2012: 3.74

w/Carter (Steamer): 3.91

w/Carter (2012 rates): 3.96

I utilized the change in the Astros' 2012 Pythagorean record to project the incremental change in wins and losses. Based on a continuation of Carter's 2012 rates of performance, the Astros gain 4.0 wins. Based on the Steamer projections, the Astros gain 2.6 wins. With some rounding, we get a 3 - 4 win improvement by substituting Carter for the five players who will be replaced. I haven't reflected the impact of Carter's defense, or lack thereof, on the win impact. Possibly that will reduce the added wins (though that's unclear, since most of the "replaced" players were poor defenders), but this article is focusing on the offense for our discussion.

Despite the fact that the Astros traded a good shortstop for Carter and potential starting pitcher Brad Peacock, this exercise may illustrate why Jeff Luhnow said that the trade improved the current Astros' roster, as well as future Astros' teams.

Astrodome Scoreboard article

clack — Thu, 28 Feb 2013 15:33:36 -0000

Astrodome Scoreboard article

Baseball Prospectus has a nice piece about the old scoreboard in the Astrodome.

2013 Houston Astros Season Preview: Justin Maxwell, Outfielder

clack — Sat, 09 Feb 2013 16:34:21 -0000

In baseball, there are some perks associated with the last place team. The No. 1 draft pick is an obvious advantage. The next biggest advantage is the first choice for claiming major league players placed on waivers. Justin Maxwell may be one of the more successful waiver claims in the Luhnow era. Fangraphs listed Maxwell as one of the 10 best part time position players in the major leagues last year. Jeff Luhnow previously has said that he would like to see what Maxwell can do with a full season of starting at bats. So, it's a good assumption that Maxwell will get plenty of opportunity in 2013.

History

Maxwell was selected by the Nationals out the University of Maryland in the 4th round of the 2005 draft. He played about 75% of his minor league games in CF, with the remainder scattered between RF and LF. In 7 minor league seasons, Maxwell posted a slash line of .261, .356, .456, .812. Aside from his initial short season league, Maxwell has never posted an OPS below .800 at any minor league level. With the exception of a few rehab plate appearances in the PCL, J-Max's batting stats have been posted in neutral or pitchers' leagues. In other words, these are not Pacific Coast League or California League fueled offensive numbers.

Maxwell's progress has been impeded by injuries over his career. Maxwell has undergone arm surgery, which may have weakened his throwing ability. This might limit his outfield positions to LF and CF. Maxwell saw sporadic playing time with the Nationals ML team, averaging less than 70 plate appearances over three season.

He was traded by the Nationals to the Yankees in February, 2011. Maxwell proceeded to tear up the International League in 2011. He posted a .946 OPS and an impressive .328 isolated power (ISO). Maxwell was invited to spring training by the Yankees in 2012, and his offense was impressive. So impressive that the Astros plucked him off waivers in early April, 2012. Reportedly other teams had put in claims too. At the time, some of the TCB commenters were scratching their heads over the waiver claim. Maxwell wasn't well known, and his sporadic playing time with the Nats' ML team didn't produce appealing major league offensive stats.

Despite the lack of experience, at age 29, Maxwell will be one of the older Astros' players. However, Maxwell has four years of team control remaining, which enhances his value.

2012 Season

Maxwell's most valuable position is CF, and the Astros were inclined to give Jordan Schafer an extended try out in CF in 2012. In addition, Maxwell was nicked up by injuries during the season. As a result, Maxwell was given only 362 plate appearances. Despite the limited playing time, Maxwell hit 18 HRs to lead the team. He also led the Astros in ISO (.232). Maxwell was No. 2 in WAR (2.3), base running (1.5), and RBIs (53). 18 HRs, 2.3 WAR, and 53 RBIs in approximately a half-time role. Are you kidding me? Maxwell's slash line: .229, .304, .460, .764. Maxwell was one of the Astros' most clutch hitters, with a 1.172 OPS with runners in scoring position. Take it for what it's worth, since the "skill" component of clutch-ness is debatable.

Skills

Maxwell is the classic 3 True Outcome players, meaning that he projects to have a high K rate, a good BB rate, and a high HR total. Early last season, I wrote about Maxwell as a 3 TO player; one can draw analogies to Jack Cust who had some of the most productive 3 TO seasons in history. Cust, like Maxwell, was picked up by Oakland in his late 20's, after he had posted prolific stats in the minor leagues. Unlike Cust, Maxwell is capable of playing a premium defensive position. Maxwell's advanced defensive stats in CF last year were excellent. Even assuming some regression, Maxwell should project as at least a slightly above average defender.

Maxwell had a decent BB rate (9.1%) on the Astros last year. Given that Maxwell routinely exhibited double digit percentage BB rates in the minor leagues, I think he is likely to improve his walk rate over 2012. As alluded by the 3 TO label, Maxwell's Achilles Heel is the strike out, with a stunning 32% K rate. This suppresses his batting average. Maxwell, who stands 6-5, is also a good base runner; his long strides can be a sight to behold on extra base hits. Maxwell hasn't been given many green lights at the ML level, but he had some nice 35 stolen base seasons in the minors. Maxwell is 131 out of 165 stolen base attempts in the minors (80% success rate).

Maxwell's premium skill is power. His HRs are massive, majestic, monumental...you choose the word. He hit the 6th longest HR in the majors last year (471 feet), which you can watch here.

What to Expect in 2013

Given the liklihood that Maxwell will be given an opportunity as a full time player for the first time in his career, he will be one of the more interesting stories to follow on the team. A positive sign for Maxwell's offense is that his BABIP last season was lower than his x-BABIP, as I wrote here, implying that he could have some beneficial regression in his batting average.

The Bill James projection system, viewed as optimistic by some, predicts a .244, .331, .465, .796 slash line. An average of four other projection systems: .223, .310, .417, .727. Given his sporadic playing time, the projection systems may not be able to get an accurate view of J-Max. Whether it's just fan boy optimism or not, I wouldn't be surprised to see a higher offensive outcome, perhaps in the low .800's OPS range. I don't expect Maxwell's whiff rate to improve much, but I think that the 32% K rate may decline into the high 20% range, given normal regression.

I used Fangraphs' filter (based on age, BB rate, K rate, batting average, and ISO) to identify similar CF hitters in 2012, and it produced only one comparable: Curtis Granderson. Considering that Granderson is paid about $12.5 million more than Maxwell, I don't mind that result.

Maxwell, a RHB, has poor splits against RHPs. Given the sample size issues with most platoon splits, as well as his minor league data, I would expect some improvement in his platoon split. Given that Ankiel is a LHB and can play CF, Maxwell could share some of his playing time. However, given Luhnow's interest in seeing Maxwell as a full time player, I don't think we will see a strict platoon. Bo Porter says that he prefers match ups based on strike zone "hot and cold" zones. Perhaps we will see some CF platooning only for certain types of RHP match ups.

Combine the acquisition of Chris Carter and Nate Freiman with the waiver claim on Justin Maxwell and it appears that the Astros are collecting some hitters who can hit massive HRs. I am waiting to see Carter and Maxwell go back-to-back with long no doubt HRs.

Talking Sabermetrics: Astros and Plexiglass Principle

clack — Tue, 19 Feb 2013 17:59:23 -0000

We are approaching the time of year when we will see "experts" predict the Astros' record. The Las Vegas oddsmakers have weighed in with an over/under W/L record of 59.5 wins (102.5 losses). Baseball Prospectus released it's initial W/L projection: 68-94 for its playoff odds system and a less regressed version at 99 losses.

One of the reactions I have read from some Astros' fans is "how can they project that the Astros will have a better W/L record this season?" One of David's newspaper colleagues provides an example of this line of thinking ("Anybody who is headed for Vegas please call me. I need to get down on the under...") I can understand the reaction. The Astros have subtracted productive players from a team that racked up 107 losses last year, and are headed to the toughest division in the toughest league. This leads some pessimistic fans to believe that a 110 - 120 loss season is in the offing. A New York Post article suggested that the Astros' would make a run at the 1962 Mets' catastrophic record. While anything is possible, I don't think that kind of extreme outcome is likely. I'll get around to some data to support my view; but, first, we have talk about statistical concepts.

In reacting to these W/L projections, I think fans tend to forget the concept of regression to the mean. All else equal, changes in teams' records, over time, will tend to move in the direction of a .500 W/L record. A common fallacy is to add or subtract wins from a team's record simply based on additions or subtractions from the roster. Most of the fans at TCB are familiar with the concept of regression when we examine players' individual statistics. The concept is applicable in a more global way to team projections.

The legitimate projection systems regress predicted W/L records, which compresses the range of expected records more compactly around .500. That doesn't mean the actual range of records will be that compact; random variation and other unexplained factors may cause some teams to over-perform and other teams to under-perform. David Cameron has made a semantic distinction between projections and predictions: "Projections are information about what we think we currently know, while predictions are speculation about things that we probably cannot know." In this case, we believe we can reasonably project the talent on a team's roster, but we can't predict which teams will over- or under-perform it's talent level. In a ballpark sense, projected team records may have an error range of plus or minus 9 games, with one third of the error related to the accuracy of the forecasts of player talent and two thirds of the error related to stuff we can't predict. With the worst record in the league in 2012, there is a pretty high liklihood that the Astros under performed, which is an automatic problem with the addition/subtraction fallacy mentioned above.

Looking at the Orioles, a team which is likely to face regression in an opposite direction to the Astros, Jack Moore's fangraphs article uses bullpen Win Probability Added (WPA) to demonstrate why the Orioles' 92 win record in 2012 might be projected to regress to 76 wins in 2013.

The Astros and The Plexiglass Principle

About 30 years ago, Bill James, the godfather of sabermetrics, developed six leading indicators to determine whether a team is likely to improve or decline. He coined "plexiglass principle," which is a more colorful term than regression. Simply put, this principle contends that teams that improve in one season tend to decline in the next, and vice versa. He also used the term "law of competitive balance" to suggest that teams with losing records tend to improve and teams with winning records tend to decline. The Astros, by the way, qualify for "improvement" on four of James' six leading indicators.

Moore's article shows that WPA, part of fangraphs' win probability family of statistics, is subject more strongly to regression than measures like WAR. This isn't surprising since WPA generally cannot be used to predict players' future performance. However, team WPA is highly correlated with wins and losses.

The 2012 Astros had the MLB's worst WPA in both the pitching and batting categories, for a total WPA of -26. In addition, the Astros were the worst clutch batting team, and the 5th worst clutch pitching team. The 2012 Astros also underperformed its Pythagorean Record--a projection of W/L record based on runs scored and allowed--by four games. WPA, "clutch," and Pythagorean deviations all have large elements of luck or randomness, and should be vulnerable to regression. As Moore states in reference to potential decline by an over performing team, " teams regress to the mean, but the combination of regression and the ever impermanent nature of clutch performance leads to a doubly hard fall." The same reasoning should apply to "doubly hard" regression in the opposite direction for a team like the Astros.

Analysis of WPA Regression

Team WPA reflects the accumulation of players' positive and negative contributions to the probability of winning each game. Certainly WPA is influenced by the talent level of a team, since good players have more opportunity to succeed. But WPA also reflects more transitory effects, like the distribution of hits, HRs, Ks, BBs, and other events across different leverage situations. If players have more success when the game is out of reach, for instance, the contributions produce minimal WPA. Teams can also accumulate high levels of positive or negative WPA if the team is involved in many close games and a lot of close and late situations within the games. "Clutch" is a subset of WPA which measures whether players' performance improved or declined in high leverage situations. In theory, really bad WPA and clutch performance should be subject to substantial regression toward average performance.

My impression is that batting WPA is most susceptible to regression in a short period of time. For my analysis, I examined the 29 teams with a batting WPA of -10 or worse over the 15 year period, 1997 - 2011. (The 2012 Astros had a -12.57 batting WPA.) I tallied the change in WPA for each team's subsequent season to determine if regression occurred.

Team	WPA	Yr. 2 WPA	Difference	Clutch	Yr. 2 Clutch	Difference
Astros 11	-12.8	-12.57	0.23	-2.6	-4.19	-1.59
Cubs 10	-11.31	-0.87	10.44	-4.63	1.73	6.36
Mariners 10	-11.09	-9.01	2.08	0.14	0.72	0.58
Pirates 10	-13.51	-4.32	9.19	0.41	3.54	3.13
Orioles 09	-10.17	-8.55	1.62	-2.54	-0.15	2.39
Royal 09	-10.72	-7.53	3.19	-2.1	-2.22	-0.12
Nationals 08	-11.88	-7.77	4.11	-2.82	-3.71	-0.89
Royals 07	-10.43	-6.66	3.77	-1.4	1.15	2.55
Rays 06	-12.2	-3.04	9.16	-7.42	-1.94	5.48
Pirates 06	-11.37	-8.76	2.61	-6.69	-4.81	1.88
D-Backs 04	-16.78	-6.06	10.72	-1.3	-4	-2.7
Blue Jays 04	-11.42	-5.26	6.16	-1.28	-0.57	0.71
Mariners 04	-10.89	-5.48	5.41	-3.83	1.52	5.35
Brewers 04	-10.56	-0.28	10.28	-2.83	-1.29	1.54
Tigers 03	-20.5	-4.34	16.16	-6.4	-5.45	0.95
Brewers 02	-15.82	-3.68	12.14	-6.37	-0.69	5.68
Tigers 02	-11.56	-20.5	-8.94	0.95	-6.4	-7.35
Royals 02	-11.17	-0.25	10.92	1.66	3.51	1.85
Rays 02	-10.43	-9.78	0.65	2.43	-7.05	-9.48
Royals 01	-11.88	-11.17	0.71	-2.24	-3.51	-1.27
Phillies 00	-10.76	4.54	15.3	-1.08	0.11	1.19
Twins 00	-10.01	2.73	12.74	1.66	2.8	1.14
Twins 99	-16.63	-10.01	6.62	-2.92	1.66	4.58
Angels 99	-10.83	0.43	11.26	-1.28	-2.08	-0.8
Tigers 99	-10.17	-3.5	6.67	-5.18	-2.6	2.58
Rays 98	-13.27	-9.38	3.89	-1.99	-3.78	-1.79
Pirates 98	-10.89	-4.88	6.01	-1.5	-5.14	-3.64
D-Backs 98	-10.84	11.33	22.17	-4.22	2.8	7.02
Tigers 98	-10.45	-10.17	0.28	-3.66	-5.18	-1.52
Cubs 97	-10.35	6.11	16.46	-2.53	1.62	4.15
Average	-12.02	-4.96	7.07	-2.39	-1.45	0.93

All but one of the 29 teams experienced regression in WPA during the next year. (That team was the 2002 Tigers, which followed up a 106 loss season with the 118 loss 2003 season.) The average improvement in WPA during the succeeding season was 7.07---approximately 59% regression to mean. On average, the teams' clutch performance improved from -2.39 to -1.45, which is about 39% regression.

I also examined the Pythagorean Record for each of the teams. On average, these teams underperformed their Pythagorean projection by 2.07 wins. And, on average, the "next year" Pythag deviation improved to one half win below the Pythagorean Record. This is equivalent to a 26% regression in the Pythag deviation.

WPA has a direct effect on W/L record. This analysis shows that teams with a very bad season of batting WPA tend to experience improvement in batting WPA during the subsequent year. Since the Astros have experienced two consecutive seasons of league worst batting WPA and clutch batting, hopefully the team will benefit from significant improvement in WPA and clutch batting during 2013, as most similar teams did during the past 15 years.

Are the forces of regression sufficient to overcome the impact of moving to the AL? Who really knows. At some point in the future, I might venture my own projection of the Astros' W/L record. However, history and WPA provide a glimmer of hope for the 2013 season.

Sabermetrics: Adjusting Astros' Starting Pitchers' 2012 Performance

clack — Mon, 11 Feb 2013 15:47:45 -0000

Sometimes we think we know how good a player performed, until we find out what we don't know. Some "external" factors affect pitchers' performance but may not be reflected in most pitching stats. Let's see how it affects our view of Astros' starting pitchers.

"Sample size" is one of the most frequent terms used in sabermetrics. And, for good reason. A lot of random stuff happens in a baseball game, and players' skills may be affected by situations beyond their control. If the time period for a statistic is too small, aberrant occurrences have too much impact. With a large enough sample size, we hope everything comes out in the wash, so to speak.

Baseball fans put a lot of emphasis on a pitcher's ERA in the previous season. Probably too much. We try to compensate for the ERA sample size deficiencies by looking at advanced pitching metrics like FIP, x-FIP, t-ERA, and SIERA. But even with these metrics, other factors like strength of opposing teams' offense, park effects, team defense, and the pitcher's usage will conceal the pitcher's performance. Even neutralized stats like ERA+ and FIP- don't control for all of these factors. We like to think that these distortions, like whether a pitcher faced first division opponents or not, tend to cancel out over a full season. But, based on adjustments used by Baseball-Reference to develop pitching WAR, that isn't always the case. Because some of the factors, like defense, aren't random, even large multi year sample sizes may not correct the distortions.

Baseball-Reference.com's pitcher value calculations perform a series of adjustments for opponent strength, ballparks, team defense, and pitcher role, which culminates in an adjustment called "RA9Avg." The RA9 Avg. for each pitcher is defined by B-Ref as:

"our best estimate of what an average pitcher would do against these opponents, with this defense, and in these ballparks."

RA9Avg. for Astros' pitchers in 2012 is shown at B-Ref here. (A more extensive explanation is here.) Given the sample size issue, I confined my review to Astros' starting pitchers, rather than relievers.

RA9Avg is used in a recent Beyond the Boxscore article on the variability of pitcher run environment on the same team. The article concluded that the Astros' and Rockies' pitching staffs had the largest range of pitcher run environments, with the Astros' difference encompassed by a RA9Avg of 4.9 for Lucas Harrell and 5.29 for Dallas Keuchel. In other words, Harrell faced the weakest run environment and Keuchel, the most difficult run environment, among Astros' starters.

For my review of RA9Avg, I examined Astros' 2012 starters Harrell, Keuchel, Lyles, and Norris, plus recently acquired pitchers Bedard, White, and Humber. This choice is based on the pitchers who will be in the mix for the 2013 rotation, thus excluding the pitchers whom were traded in 2012.

RA9Avg Adjustment

In order to examine how RA9Avg might affect our pitcher evaluation, I calculated a ratio of RA9Avg to league average Runs Allowed per 9, and used the resulting adjustment factor to calculate the change implied for each pitcher's Runs Allowed per 9. I show the AL average RA9Avg for comparison, since the Astros will be changing leagues in 2013.

	RA/9	Adjust for RA9Avg	Adj. RA/9
Harrell	4.18	-0.443	3.737
Keuchel	5.91	-1.147	4.763
Lyles	6.18	-1.060	5.120
Norris	4.81	-0.554	4.256
White	6.06	-2.312	3.748
Bedard	5.44	0.037	5.477
Humber	6.53	-0.365	6.165

AL Avg.			4.47

All of the pitchers, except for Bedard, benefit from recognizing the RA9Avg adjustment. Because the Astros' team defense is below average, according to defensive metrics, all of the Astros' performances are disadvantaged without an adjustment. Alex White who pitched in front of a bad defense in ballparks with high park factors, receives the largest benefit from the adjustment. Keuchel, Lyles, and Norris also had large effects; however, among the three, only Norris' performance shifts to better than league average with the adjustment.

Most of these pitchers have a ERA higher than than their Fielding Independent Pitching stat in 2012. Below see a comparison of the RA9Avg adjustment with the "ERA - FIP" differential shown at Fangraphs. (Bedard, with an upward RA9Avg adjustment, and Keuchel, who has a ERA lower than his FIP, are excluded.) This may give us an idea as to whether the RA9Avg adjustment explains the differential between ERA and FIP.

	RA9Avg Adj.	E-F
Harrell	-0.443	0.02
Lyles	-1.060	0.56
Norris	-0.554	0.42
White	-2.312	0.28
Humber	-0.365	0.67

As shown above, the RA9Avg adjustment is double or more than the ERA - FIP differential for several pitchers. We could take this one of two ways: either RA9Avg impact is larger than we expected, or perhaps the Baseball-Reference adjustments methods are inaccurate.

Some interesting observations: on average, Harrell faced the weakest offensive teams, and Keuchel and White faced the strongest offensive teams; Norris was hurt the least by the defense--due to his K rate and fly ball rate; White and Humber pitched in the most hitter friendly ballparks, and Norris pitched in the most pitcher friendly ballparks.

Is the Adjustment Accurate?

There is always a catch, right?

I would treat the RA9Avg adjustments, above, as illustrative, rather than definitive. The examples demonstrate the potential for these adjustments to significantly affect single season results. I think this exercise provides us an idea as to which pitchers may have been helped or hurt the most by the run environment. But the B-Ref adjustments are not perfect.

I don't want to come off as criticizing the B-Ref adjustments too severely. A lot of effort went into creating adjustments which have conceptual merit. However, the methods have some potential flaws which may affect the accuracy. In particular, the sample size problem can be seen here too. For example, we know that defensive metrics can be volatile in small samples, and the defense adjustment assumes that a team's defense is more or less uniform from game to game. The assumption that an opposing team's offensive ability is uniform throughout the year is another possible shortcoming.

But, setting aside questions about the precision of the B-Ref adjustments, does this change your view of any of the Astros' starting pitcher candidates?

Sabermetrics: Earl Weaver and the modern manager

clack — Mon, 21 Jan 2013 19:40:03 -0000

With the death of Earl Weaver, we have seen numerous articles discussing his legacy as a manager. Weaver had an intuitive feel for what we now call "sabermetrics;" he was the sabermetrics manager before there was sabermetrics. So it's appropriate to examine Weaver's managerial influence in the "talking sabermetrics" series here at TCB. To a great extent, I will rely on Chris Jaffe's great piece, "11 things I didn't know about Earl Weaver," at the Hardball Times. Jaffe is the most well known saber expert on evaluating managers---he knows much more than I about managers and their effect on baseball games.

As the Astros begin a new season with a new manager, we can squint and see an interesting connection to Weaver. Jaffe points out Weaver's imprint on Nationals' manager Davey Johnson. Johnson was a savvy second baseman for Weaver, and Jaffe sees him as the modern descendent of Weaver's managerial philosophy. Well, guess what? Bo Porter coached under Johnson with the Nationals. Maybe the Weaver lineage is spreading to Houston.

It's not just sabermetricians who have pointed to Weaver as the "moneyball" manager. Writers as diverse as George Will and Tom Verducci made the same observation. Verducci quotes Billy Beane:

"I made no bones about it when I first got the job: I always wanted the next Earl Weaver as manager. Earl was ahead of his time. He understood offensive baseball, pitching rotations, the efficiency of three-run homers versus a single and a sac bunt...if you get to the core of what he accomplished, he was the template of the way I'd like to run a team. Consciously or not, he understood mathematics and probability."

Weaver wrote a book on managerial strategy which stated the principle, "your most precious possession on offense is 27 outs." That was almost 30 years ago. Verducci quotes Theo Epstein as saying he was 'blown away" when he read Weaver's managerial strategy book a few years ago.

Bases on Balls and OBP

Rightfully, Weaver is famous for his love of 3 run Home Runs. He realized that the power game was much more important to winning than small ball tactics. At the time, managers like Gene Mauch were sometimes referred to as the "scientific" managers because of their devotion to bunting, moving runners over, etc. But Weaver was disdainful of their tactics.

However, the overlooked part of Weaver's philosophy was the recognition of walks and OBP as offensive keys. For the period 1969 - 1981, Weaver's Orioles had such a massive lead over the rest of the league in drawing walks that it is clear that he was constructing and managing a team by a different book than everybody else. Jaffe says: "Weaver’s Birds are so far ahead [in walks] that the second-place Red Sox are nearly as close to last as they are to Baltimore."

Verducci talked to an elderly Weaver in recent years about "moneyball." He hadn't heard of moneyball, but Weaver became excited when Verducci mentioned Beane's OBP philosophy: "That was my favorite right there, on-base percentage!" As an example, Weaver explained that the previous Orioles manager had played outfielder Don Buford sparingly. Weaver told Buford he would play regularly if he could get his OBP up to .400 and walk 100 times per year. Verducci points out that Buford's career OBP was .335 before Weaver took over the team, and increased to .388 by the end of his career under Weaver.

Pitching and Defense

People focus so much on the Orioles' offense that they overlook the value that Weaver placed on team defense. Weaver was willing to give regular playing time to a few weak offensive players like Paul Blair and Mark Belanger in order to reap the benefits of plus-defense. He figured that exceptional power hitting at low value defensive positions like first base (Boog Powell) would offset the weak offense by the key defensive players. According to the advanced defensive metric, Total Zone, Weaver managed the best defensive team of all time; and according to Jaffe, Weaver's teams are the only teams in baseball history to exceed 11 dWAR in a season.

Most people realized that Weaver's teams had extremely productive pitching rotations, with multiple 20 game winners in many seasons. However, it is the interplay of defense and pitching which made the Orioles' rotations special. Weaver demanded two things from his pitchers: great control; and induce the batter to put the ball in play in the direction of the Oriole's superior defense. Jaffe points out:

Baltimore pitchers never were much for striking batters out. Only the Royals and Brewers fanned fewer from 1969 to 82. Weaver didn’t need flamethrowers as long as his fielders caught the ball. What Weaver needed from his pitchers was control. Only the Yankees walked fewer batters than Weaver’s squad did from 1969 to 82. Weaver thus had complementing defensive strengths; his pitchers wouldn’t short-circuit the defenders by issuing any free passes, and in turn, the defenders would bail out the hurlers when need be. This made the sum more than the whole of its parts.

In some ways, this reminds me of the way that the saber oriented Rays have constructed and managed their teams. The Rays are well known for using their defensive strength and shift tactics to develop DIPS-busting pitching rotations. Out of curiosity, I compared the relative pitching BABIP performance of Weaver's Orioles and Maddon's Rays:

(Team BABIP/ League BABIP/ Difference)

Orioles (1969 - 1973) .254 / .273 / .188

Rays (2008 - 2012) .277 / .294 / .177

We have seen the Astros draft starting pitchers with advanced control this year. If the Astros can develop position players with advanced defensive ability (Carlos Correa anyone?) to go with those pitchers, maybe the Astros can construct a Weaver-esque pitching rotation.

No Pressure, Bo

We could discuss other Weaver strategies--strong bench depth, giving each player a role and playing everybody, match ups and platooning--but you can read Jaffe's article for a more thorough exposition.

I've mentioned that we can see a potential lineage between Weaver and Bo Porter. Grasping at straws? Sure, that's what fans of bad teams must do. But we also know that Weaver was an "unknown" when he took over as the Orioles' manager. Weaver was a minor league manager who had never advanced above AAA as a player. (Weaver credited his own playing talent deficiencies with making him a good manager.) Porter has a similarly unimpressive playing career (like a career OPS+ of 59), and he doesn't have a "name" which is recognized by the casual fan. Maybe Porter can become the Astros' Earl Weaver of the future. Sure, we could say that about every relative unknown who was named a manager. But sometimes it turns out to be true.

Alan Ashby Returns to the Astros Broadcast Booth

clack — Sat, 05 Jan 2013 04:54:32 -0000

Ever since Jim Deshaies bolted to the Cubs' broadcast team, we have seen considerable angst among Astros' fans. Who would be the new television color announcer? I think many fans will be relieved because former Astros' catcher and radio broadcaster Alan Ashby is replacing Deshaies in the television broadcast booth. The Toronto news story is here and the Chronicle's news story is here.

Ashby isn't the only former Astros' player returning in a different role to the team. Morgan Ensberg and Adam Everett, stars of the 2005 World Series team, will join the Astros' organization as instructors.

It appears that Bill Brown will join Ashby on many of the television broadcasts. But Brown requested that his time commitment be reduced, and he will not be the full time television play-by-play announcer. Ashby will move over to play-by-play duties when Brown isn't on the broadcast. We don't have news yet on the radio broadcast crew yet.

Astros' fans were upset when radio broadcaster Ashby was let go after the 2005 season by the Astros. Ashby talks frankly in the Toronto news story about how tough it was to accept the Astros' decision then. “In 2006 I sat out, and realism told me that this aging, mediocre former player without the large name was not what people were looking for. I figured it was over.”

Given that background, it's not surprising that he is thankful to the Blue Jays for hiring him. With the Toronto broadcast team, he became one of the most respected baseball color guys. And maybe some Astros' fans will view this as righting a situation which shouldn't have occurred.

I also like the move to hire Ensberg and Everett as instructors. Ensberg was one of my favorite Astros' players in the mid-2000's. And Everett was just a great, great defensive shortstop. I have no doubt that Everett knows as much as anybody about infield defense. Both Ensberg and Everett were smart players, which should help them as instructors. I hope the minor leaguers listen to them.

Astros' fan angst? It's not gone. I'm glad to have Ashby back. But will I ever get to watch the Astros' broadcasts here in Austin? Comcast has some work to do in getting cable and satellite contracts signed. Postolos--or whomever is in charge--get 'er done!

Thoughts?

Talking Sabermetrics: Postscripts on Astros' Veras and Humber Acquisitions

clack — Wed, 26 Dec 2012 14:28:13 -0000

We have had several articles about the Astros' waiver acquisition/contract signing of Philip Humber and the free agent signing of Jose Veras. I don't want to be repetitious of the evaluations in these articles. But a couple of recent sabermetric articles may give us a glimpse of the Astros' thinking behind the two pitching acquisitions. So, here are a couple of quick points about each player's 2012 season.

Humber and kwERA

Glen DuPaul at Beyond the Boxscore wrote about the 2012 starting pitchers who are likely to improve or decline based on the pitching metric "kwERA." This metric was devised as a quick measurement for pitching performance, but DuPaul has previously found that kwERA is surprisingly effective at predicting starting pitchers' future performance over the remainder of a season or for the next season. The kwERA metric gives equal weight to strike out % and walk %, and is scaled to ERA. This seems similar to FIP and x-FIP, except that it ignores HRs. DuPaul's previous Hardball Times article suggested that kwERA is better than FIP and x-FIP at predicting future performance, and concluded that simple is better in this case.

Based on the gap between ERA and kwERA in 2012, DuPaul shows Humber as no. 2 on his list of starting pitchers most likely to improve in 2013. Humber's kwERA gap is 2.03 runs and is second only to Jake Arrieta of the Orioles. Humber's kwERA was 4.41 in 2012. This may not seem like an impressive "target" for regression. But keep in mind that the average American League's starter ERA was 4.37 in 2012. Humber had a bad year, but he pitched like an average starter in the AL, according to kwERA. If you consider the fact that Humber pitched in the higher run environment of the AL, it's possible that he pitched better than several of the pitchers in the Astros' rotation. It's also worth noting that Humber's kwERA is almost the same as his 2012 SIERA (4.48), which is also a predictive pitching stat. Obviously, there are no guarantees here, but it seems like a worthwhile gamble.

The Astros' pick up of Humber is a similar gamble to the Pirates' signing of Francisco Liriano, who also is on DuPaul's list of pitchers most likely to improve in 2013 based on kwERA. The Liriano signing inspired Fangraphs to write about the "slow death of ERA" as a front office evaluation method.

What is the kwERA for the Astros' pitchers with at least 60 IP? Here it is, courtesy of the rotovalue web site.

Astros kwERA

Lopez (traded) 3.24

F. Rodriguez 3.42

Veras (signed) 3.84

Norris 3.87

Lyles 4.32

Humber (signed) 4.41

Harrell 4.44

Keuchel 5.43

It's hard to say why kwERA may be better than FIP and x-FIP in predictive ability. We usually think that more information (such as the inclusion of HR rates) is better. But that may not be the case, particularly for short term periods. One possible reason: HR/Flyball and HR/9 are relatively volatile stats. Yes, both HR statistics have some year-to-year correlation, but the correlation on a year over year basis is 40% - 50% less than the year to year correlation of K% and BB%.

Jose Veras

My last Talking Sabermetrics article discussed DuPaul's findings that K rate is the best predictor of relief pitcher performance, with particular reference to the prospect of a F-Rod rebound. Only a few days later, the Astros signed Jose Veras, who brings a 2012 K rate of 26.3% to the table, highest among current Astros' relievers. As you may recall, one of the reasons for relying on K rate in evaluating relief pitchers is the fact that K rates stabilize in a smaller sample size than most statistics. Relief pitcher results tend to be volatile from year to year, mostly due to typically small sample sizes.We can speculate that the Astros' evaluation of Veras is consistent with heavy reliance upon K rate for rating relief pitchers.

Here at TCB, we had some discussion of Veras' walk rate weakness and his potential for high leverage pitching. Around the same time, I found BtB writer Bill Petti's spreadsheet of pitching statistic correlations. I came up with a couple of correlation nuggets which might be relevant to Veras.

First, year to year K rate correlation is 20% higher than BB rate correlation. Maybe Veras' K rate, his positive attribute, is more certain than his BB rate, his weakness. Perhaps there is a little bit of hope for some improvement in his BB rate.

Second, K rate is highly correlated (.47) with a player's future Wins Probability Added (WPA), while BB rate has a lessor correlation (-.07) with WPA. WPA is moderately correlated with next year WPA (.33). Granted, these correlations are for starting pitchers, so I am making the leap that a similar relationship exists for relief pitchers. Change in WPA is the input for calculating reliever shutdowns and meltdowns; therefore, WPA is particularly relevant to relievers. And it makes sense that pitchers with high K rates can get out of jams more readily, thereby leading to the relationship between K rates and WPA. For what it's worth, Veras had a high WPA last year (1.31) and has posted positive WPA for all but one year in his career. Take these as interesting observations, rather than predictions.

Talking Sabermetrics: The Astros' relievers...and defensive metrics vs. scouting reports

clack — Mon, 10 Dec 2012 06:19:59 -0000

Time for some sabermetric deep thoughts. Maybe not so deep. And more like a couple of unrelated subjects that came to mind. But hopefully not superficial thoughts either. Just sabermetric thoughts.

ASTROS RELIEVERS

Glenn DuPaul at Hardball Times listed his top five relief pitchers who could improve in 2013. The Astros' Fernando Rodriguez was on the list, and DuPaul writes:

Despite his struggles with walks and home runs, Rodriguez's peripherals (FIP, xFIP, SIERA, etc.) indicate that he was much better last season than his ERA would reflect.

Rodriguez was a solid reliever in 2011 with similar peripherals, but his 2012 strand rate (65.2 percent) caused his ERA to inflate. I think his velocity, strikeouts and peripherals are a better indicator for his future.

Houston could see Rodriguez return to being a very good reliever next year for very little cost: Rodriguez will make the league minimum.

Rodriguez had some bad moments in high leverage situations last year, and, as a result, doesn't get much love from Astros' fans. As I've written previously, Rodriguez's pitching performance wasn't at bad as we think. As we try to evaluate the 2013 relief corps, it's not unreasonable to project F-Rod as a useful part of the Astros' bullpen.

DuPaul has a simple approach to projecting relief pitcher performance. Reliever performance is notoriously volatile from year to year, in large part because the small sample size. Relievers typically pitch one-quarter to one-half as many innings as starting pitchers. He relies mostly on strike out percentages to evaluate relievers, pointing out that strike out percentage is one of the few statistics to have statistical reliability around the 60 innings mark.

In another Hardball Times' study, DuPaul finds that strike out percentage is a better predictor of future performance for relief pitchers than other measures like FIP, SIERA, and x-FIP that are typically used to project the future run prevention rate. Another surprising finding is that BB% adds relatively little to the prediction capability provided by K%. It's unclear why this is the case. Perhaps relief pitchers are unlikely to stay in the big leagues without showing a minimum level of control. Or maybe the conversion of a relief pitcher's walks into runs is controlled too much by subsequent relief pitchers, which adds to the volatility in predicting run prevention.

Here is a list of the Astros' top five K rate relief pitchers in 2012.

(K % / SIERA)

Storey 26.8% / 2.99

Ambriz 26.5% / 3.59

Cedeno 26.1% / 3.18

Rodriguez 25.2% / 3.53

Wright 24.2% / 2.83

The sample sizes are small (even in the relief pitcher world) for Storey, Ambriz, and Cedeno. Rodriguez is the only one of the five to exceed the 60 inning mark associated with stabilizing K rates. The Astros selection of Josh Fields in the Rule 5 draft is certainly consistent with relying on K% to evaluate relievers. His K rate of 32% and 39% in AA and AAA is really, really good.

Advanced Defensive Metrics vs. Scouting

The advanced defensive metrics, primarily DRS and UZR, evoke criticism in some quarters. When I read an article suggesting that WAR should encompass both scouting and advanced metrics to measure defensive value, I wondered "how different are scouting evaluations of defense compared to play-by-play metrics?"

We don't have the professional teams' scouting reports available to us--and certainly not in a form that can be compared to runs saved metrics. But we do have the fan scouting reports (FSR) collected by Tango, which are conveniently converted by fangraphs into a form which can be compared to UZR and DRS. (Unfortunately the FSR is not available until the next year.) FSR probably can be used as reasonable representation of the "eye test."

I used Fangraphs to develop a defensive leaderboard of 120 players for the period 2009 - 2011. Both UZR and DRS are highly correlated to FSR: for DRS, .73 correlation and .53 R-squared; for UZR, .70 correlation and .49 R-squared. Looking at several different comparisons (including annual runs saved at the team level), DRS usually has a better correlation with fans scouting reports than UZR. Total Zone results are much less similar to FSR (.38 R-squared). Other metrics like errors, RZR, and out of zone plays have little correlation to FSR.

On the one hand, the high level of correlation tells us that DRS and UZR are largely coming to the same conclusions as the "eye test." However, roughly one half of the variation in FSR is not explained by the advanced metrics. I'm not sure that this is surprising or a cause for concern, but it could be. Clearly, FSR and UZR/DRS reach different conclusions about the relative defensive value of some players. And, it's worth noting that UZR and DRS are more closely correlated with each other than they are with FSR.

Furthermore, we don't really know much about the precise reliability of scouting reports like FSR. I have wondered in the past whether FSR respondents are influenced by the UZR/DRS results they have seen previously. Given that scouting reports for each player are dominated by fans of his team, there is a real possibility of bias toward popular or unpopular players. For that matter, even professional scouting reports could be subject to similar biases, though perhaps to a lessor extent.

Talking Sabermetrics: Astros Hitter x-BABIP

clack — Tue, 20 Nov 2012 16:09:06 -0000

A couple of weeks ago I wrote about Astros' pitcher x-BABIP. The x-BABIP calculation for pitchers is a newer concept than x-BABIP formulas for hitters. And we probably are somewhat more confident in the x-BABIP benchmarks for hitters, given its wider use. Today, I will complete the x-BABIP discussion by comparing Astros' hitters x-BABIP to actual BABIP.

Take a step back for the context of this discussion. As you probably know, BABIP is "batting average on balls in play" and x-BABIP is "expected BABIP." The common usage for the x-BABIP comparison is to assess whether the batter's hit results (such as batting average) are lucky or unlucky. A hitter who posted an actual BABIP less than expected BABIP may have been unlucky or vice versa. This, in turn, might tell us whether the batter's performance is likely to revert upward or downward in the next season. There are no guarantees, of course. But it's an interesting exercise.

REVIEW 2011 x-BABIP RESULTS

In October, 2011, I compared Astros' hitters 2011 BABIP to their x-BABIP for that season. We can review the 2011 comparison and see how successful it was in predicting positive or negative BABIP regression for 2012. In my view, these kinds of comparisons are more valuable in suggesting the direction of the future BABIP, as opposed to predicting the actual BABIP for the next season. Therefore, I will compare the 2012 actual BABIP to the 2011 BABIP, inquiring whether the BABIP increased or decreased as suggested by the 2011 x-BABIP.

Bogusevic, Paredes, and Downs posted BABIP higher than x-BABIP, suggesting that BABIP would decline in 2012. Bogusevic experienced almost a 100 point decline in BABIP; Paredes and Downs had more than a 100 point decline in BABIP. The BABIP over-performers in 2011 suffered a sharp decline in BABIP.

Lee, Barmes, Sanchez, Altuve, Schafer, Towles, Corporan, Johnson, and Quintero posted BABIP lower than x-BABIP, suggesting that their BABIP might rebound in 2012. Towles and Sanchez drop out of this comparison, since they were minor leaguers in 2012. Of the remaining players: Lee, Schafer, and Quintero posted lower BABIP in 2012; Barmes, Altuve, Corporan, and Johnson posted a higher BABIP in 2012. Lee, Schafer, and Barmes had small 2012 BABIP differences from 2011. The results for BABIP underperformers, alone, is inconclusive. However, taking under and over performers together, the x-BABIP predicted the direction of BABIP change in 7 of 12 cases.

2012 x-BABIP

In 2011, I used the Hardball Times x-BABIP calculator. For this exercise, I will use the Fangraphs x-BABIP calculation. The formulas are different, and I'm not saying that the Fangraph method is better. This is a convenience on my part, since Fangraphs' Eno Sarris provided a compilation of x-BABIP for 2012 batters with at least 300 at bats.

The Fangraphs 2012 x-BABIP article is here. Just for those who want Justin Ruggiano back, he had the highest BABIP in excess of x-BABIP in the major leagues; tread with care in gambling on Ruggiano's performance in 2012. The only two BABIP over-performers among 2012 Astros' hitters were Chris Johnson and J.D. Martinez. Johnson, of course, is no longer with the Astros. J.D. Martinez had an actual BABIP of .290 compared to x-BABIP of .284. This is somewhat disappointing to me, since I would have hoped that the drop-off in Martinez's hitting would have been explainable by BABIP. Not the case, though.

I pasted the information regarding Astros' hitter BABIP under performance from the article below.

(Player, BABIP, x-BABIP, difference)

Maxwell .292, .304, .012

Altuve .321, .334, .0128

Lowrie .257, .293, .0357

Greene .292, .344, .0502

Bogusevic .257, .330, .0734

We should be encouraged that the Astros' three best hitters, Maxwell, Lowrie, and Altuve, under-performed their BABIP, implying that they achieved their offensive performance despite some bad luck in the BABIP Department. Tyler Greene had a large gap between his BABIP and x-BABIP. One can hope that this means he will move in the direction of a higher offensive output in 2013. Note that Bogusevic was one of the biggest under performers of x-BABIP in the major leagues.

The Fangraphs article calculated x-BABIP for hitters with 300 plate appearances. I calculated x-BABIP for some of the Astros' hitters with less than 300 plate appearances, with the obvious caveat that they are based on small samples. Jason Castro has the largest sample, falling short by only a few plate appearances.

	BABIP	x-BABIP	difference
Dominguez	0.299	0.3291	0.0301
Wallace	0.331	0.3425	0.0115
Moore	0.309	0.3239	0.0149
Castro	0.309	0.3542	0.0452
F-Mart	0.278	0.3024	0.0244
Gonzalez	0.264	0.3108	0.0468

Again, all of these smaller sample size Astros hitters under performed their x-BABIP, implying the liklihood of reverting to a higher BABIP in the future. In another thread someone asked if I had calculated a x-BABIP for Dominguez---well, here it is, and it suggests better potential than the BABIP predicted by the Bill James system. On the other hand, Dominguez's sample size is so small that perhaps we shouldn't read much into it. Jason Castro's sample is more reasonable, and his 2012 x-BABIP is encouraging.

Too Much BABIP Under-performance?

The large number of BABIP under-performers raises some questions to me. Perhaps the Astros were just unlucky? Possible. But could there be other explanations? Does Minute Maid Park suppress BABIP? I'll discuss that in a minute. Is the Fangraphs x-BABIP formula biased toward under-performance? I don't know. We may have to wait for next year's actual performance to get a better read on the formula. Another possibility--not something we like to consider--is that some of the Astros' hitters do not have major league hitting ability--and, therefore, BABIP under-performance reflects lack of talent.

All of the data I have reviewed indicates that Minute Maid Park is slightly above average for BABIP. As additional evidence of this, the Astros team BABIP is higher at home than on the road during 2012. And this is also true over the 4 year period ending in 2012. Therefore, I doubt that MMP suppresses the Astros' hitters BABIP.

Talking Sabermetrics: What Does Astros Pitcher BABIP tell us?

clack — Mon, 05 Nov 2012 14:51:47 -0000

BABIP (Batting Average on Balls in Play). Simple statistic. But much analyzed by sabermetricians.

DIPS theory, an important sabermetric concept, indicates that pitchers have limited control over the outcomes of batted balls in play. A corrollary to DIPS is that batters probably have more influence over their BABIP than pitchers do over the BABIP they allow. As a result, analysts and fans frequently compare a pitcher's BABIP to the league average BABIP and assume that the difference between the pitcher's results and the average is due to some combination of luck and defense. This can provide a starting point for predicting the direction of a pitcher's regression from season to season.

However, this isn't the end of the story. We know that pitchers have differing tendencies for fly ball and groundball rates, which affects BABIP (since groundballs generally produce more hits in play than fly balls). It's widely accepted that specialty pitches (e.g., knuckleballs or Mariano Rivera's cutter) can confound BABIP expectations. And it doesn't take much to expand that conjecture to other pitchers who seem to induce weaker than average contact. A better way of looking at BABIP is to view it as a 30 or 40 point range around the league average. Pitchers with really high or low BABIPs beyond that range probably have experienced unsustainable results. But it is also possible that pitchers' differing skills and pitch types will slant their BABIP result toward the high or low end of the normal range. Because BABIP is subject to quite a bit of random variation, it is difficult to distinguish pitcher-specific BABIP from luck or defense.

A recent article in the "Community Research" section of Fangraphs provides an interesting effort at illuminating pitcher BABIP. Steve S presents his results in Projecting BABIP Using Batted Ball Data, and develops a formula for pitcher-specific "expected BABIP," or x-BABIP. (As you may know, x-BABIP formulas have been applied previously to hitters.) Later in this story, I will use that formula to calculate x-BABIP for Astros' pitchers. The most interesting aspect of his article is that it shows a myriad of correlation coefficients between and among BABIP, batted ball types, pitch f/x data, and pitch types. I wouldn't take these results as conclusive, but I think they show the direction of certain relationships, and provide some leads for future hypotheses which might help explain how or why pitchers achieved a particular performance level.

Not surprisingly, line drive rates and infield fly rates are found to be important determinants of BABIP. However, line drive rates are less predictable, even if multiple years of data are used to predict a future line drive rate. The pitcher has some effect on the line drive rates; for example, groundball and strike out rates seem to be correlated with preventing line drives. But, in general, line drive rates probably reflect more year to year random fluctuation. Infield fly ball rates, on the other hand, appear to be more predictable and consistent from year to year. As the Hardball Times glossary states: For some pitchers, inducing infield flies may be a repeatable skill. And infield fly balls are an important outcome, since infield pops are the surest form of out other than a strike out.

Another thought provoking observation from the article: different, and perhaps divergent, pitching skills are related to preventing line drives and inducing infield flyballs. Four seam fastballs in the zone combined with using slower pitches to change speeds appear to be the best recipe for inducing infield flyballs. Fastball movement has a closer relationship to infield flyball rates than velocity. Avoiding line drives, on the other hand, appears to depend on sinkers and 2 seam fastballs, as well as higher velocity. To some extent, these two elements of run prevention profile as two different types of pitchers.

x-BABIP

The fangraphs article develops the following formula for a pitcher's expected BABIP: xBABIP = 0.4*LD% – 0.6*FB%*IFFB% + 0.235

I calculated the x-BABIP for some of the Astros' pitchers likely to return next year in key roles. Comparing the pitchers' actual BABIP to x-BABIP provides some information regarding the liklihood of a positive or negative regression in the pitcher's performance next year. If the pitcher's actual BABIP exceeds x-BABIP, this may support an argument that the pitcher is likely to revert to a lower BABIP, and vice versa. However, if the lower than expected BABIP performance is primarily due to poor defense (not an unreasonable possibility, since the Astros did not rank well on advanced defensive stats), than a reversion to x-BABIP may depend on an improved defense in 2013. The variance column is actual BABIP minus x-BABIP (i.e., a positive variance means that the pitcher is expected to revert to a lower BABIP).

	BABIP	IFFB	FB	LD	FDP wins	x-BABIP	Variance
harrell	0.289	9.1%	30.6%	17.4%	(0.20)	0.288	0.001
norris	0.301	9.4%	39.6%	21.2%	(0.20)	0.297	0.004
lyles	0.301	8.8%	29.0%	17.1%	(1.90)	0.288	0.013
keuchel	0.277	9.1%	30.6%	17.4%	0.20	0.288	-0.011
wright	0.289	8.8%	23.6%	21.5%	0.20	0.309	-0.020
lopez	0.297	7.5%	21.2%	23.8%	0.60	0.321	-0.024
F-Rod	0.312	19.1%	46.5%	18.2%	(1.10)	0.255	0.057
NL Avg.	0.300

The column titled "FDP Wins" is the potential impact of batted ball and the timing of pitching outcomes during 2012, expressed on a WAR type basis. I described Fielding Dependent Pitching Wins in a previous article here. A negative FDP Wins means that the pitcher was hurt by the number and timing of balls in play, and is consistent with a positive variance between BABIP and x-BABIP.

Results and Predicted Direction

Lucas Harrell. Neutral. Harrell's BABIP is one point higher than his x-BABIP--for our purposes, his performance was consistent with his x-BABIP. However, Harrell's FDP-Wins is negative, primarily because he was below average in leaving runners on base. If you believe that this mostly reflects bad luck, then he may experience improvement in the future. I'm not sure we can assign all of the consequences of negative timing to bad luck, though. The Astros' defense faltered too often with runners on base, and Harrell sometimes had control issues in those situations.
Bud Norris. Positive Regression. Norris' actual BABIP was somewhat higher than his x-BABIP, indicating the potential for a reversion to a lower BABIP. Norris allowed a high line drive rate, and was fairly decent at inducing infield flies. Since line drive rates are more erratic than infield fly rates, it is possible that Norris' x-BABIP next year could be lower than 2012. Combined with other indicators like SIERA (3.90), the signs appear to be good for a bounce back by Norris in 2013.
Jordan Lyles. Positive Regression. Lyles' actual BABIP was substantially higher than his x-BABIP. This, in combination with a severely negative FDP-Wins, suggests the potential for significant improvement in his performance next year. Like Harrell, Lyles frequently was hurt by defensive misplays with runners on base. Lyles is doing a lot of things right, and he should improve significantly with any degree of better luck and improved defense.
Dallas Keuchel. Negative Regression. Keuchel's .277 BABIP is substantially below his x-BABIP. This is a bad sign for potential improvement next year. Perhaps we can see a glimmer of hope in his ability to suppress line drives and induce a reasonable number of infield flyballs.
Wesley Wright and Wilton Lopez. Negative Regression. Lopez and Wright allowed a BABIP substantially below their x-BABIP. This could suggest that both may regress toward allowing more hits next season. However, it's possible that the x-BABIP comparison may not work as well for relief pitchers. Both Wright and Lopez allowed high line drive rates, even though they are groundball pitchers.
Fernando Rodriguez. Positive Regression. Some of the fans soured on F-Rod because he blew some high leverage appearances. But he really is a better relief pitcher than the 2012 results. F-Rod has the biggest variance between his BABIP and x-BABIP of any on the chart. F-Rod's low x-BABIP (.255) is driven by a high infield flyball rate (19.1%), combined with a reasonable line drive rate (18%). Maybe the infield fly rate and x-BABIP are a bit extreme, due to the sample size. But F-Rod fits the profile of a pitcher who can induce infield pops and suppress BABIP. F-Rod's SIERA is 3.53, another indicator of potential improved performance in 2013.

Home/Road Splits

Three Astros' starters--Norris, Lyles, and Harrell--exhibited among the largest ERA splits for home vs. road in the majors. For Norris and Lyles, the H/R split in BABIP was a major reason for the ERA differential. The BABIP splits: Norris (H) .263; (R) .326. Lyles (H) .284 ; (R) .319.

Norris is an extreme case for H/R splits. He has the worst road ERA (6.94) among qualified starters. Norris fell short of the inning threshold to rank as qualified starter at home. But if he had qualified, Norris would have the second best home ERA among MLB starters. That is amazing. Norris was almost the best major league starting pitcher at home and the worst starting pitcher on the road.

Norris has similar extreme differentials between x-BABIP and actual BABIP for home and road--except in opposite directions. Norris' x-BABIP/ actual BABIP: (H) .305 / .263; (R) .294 / .326. This would suggest that regression for both home and road BABIP will reduce the size of Norris home and road ERA splits.

But we really don't know why one team has three starting pitchers with such large ERA home/road splits (2 to 5 runs variance). Does Minute Maid Park provide an unspecified ballpark advantage? Does the Astros defense play much better at home? We could probably come up with more lines of speculation. The bottom line is, we don't know.

Talking Sabermetrics: Pitchers' Control and Injuries

clack — Wed, 31 Oct 2012 14:32:47 -0000

We have mentioned it a number of times. During Jeff Luhnow's first season, the Astros have shown a preference for acquiring strike-throwing pitchers. This is apparent among the drafted college pitchers, as well as many of the minor league pitchers acquired in trades at mid-season.

There might be any number of reasons. The most obvious is the obvious. If you looked at the typical pitching coach's list of commandments, you will probably see "throw strikes" at, or near, the top of the list. If we assume that control pitchers also are most likely to exhibit command within the strike zone, then we can add "location, location, location" to the pitching admonitions. We can also speculate that the preference for control pitchers may be exploiting a market inefficiency. Because strike outs are seen by teams' scouts as an indication of "stuff," possibly control has become undervalued relative to the other main peripheral statistic, strike outs.

Fangraphs' Jeff Zimmerman raises another possible attribute of pitchers' control: Does control and command of the strike zone tell us something about pitchers' future injury risks? His article "Injury Chances for Strike Throwers" inspired today's Talking Sabermetrics topic.

The FG article starts with an interesting quote from Tim Kirkjian of ESPN, discussing Oakland GM Billy Beane's view regarding the traits he wants in young pitchers:

GM Billy Beane doesn’t require power, he wants outs without walks. Plus strike throwers generally have good mechanics that help prevent injury. Beane also isn’t afraid to go with young pitchers, what at least in theory are less likely than older ones to get injured.

Beyond the obvious reasons to favor strike throwing pitchers, a sabermetric oriented GM believes that control pitchers have a lower risk of injury. Certainly the proposition has some logic. Control pitchers must develop good, repeatable mechanics; and good mechanics should be associated with a reduced injury rate.

I can think of two more similar explanations for believing that control is related to injury rates. First, over-throwing is the enemy of control, and presumably over-throwing increases the chance of arm injury. Second, we would expect high velocity to be correlated with reduced control--maybe a better way to state this is that lessor control can be tolerated from hard throwers. While not all hard throwing pitchers are injury prone, generally throwing at a very high velocity puts more stress on the arm joints.

The explanations may be logical but that doesn't prove that the connection between control and proneness to injury is true. Zimmerman tried to test the theory by comparing various measures of control (strike %, zone %, non-intentional BB%) with pitcher DL visits. Zimmerman's analysis produced mixed / weak results to support the notion that control pitchers are more likely to be reduced injury risk. Only pitch f/x zone percentage seems to be related to a lower risk of injury. Of course, it's possible that DL visits are too imprecise a measure of pitcher injury risk, since it isn't limited to arm injuries nor does it reflect the severity of the injury.

But that's not the end of the story. Zimmerman notes that the data supports the idea that pitchers with really bad control are more likely to be injury risks:

While I was only able to find one of the three categories that showed strike-throwers being healthy, I did find that extreme non-strike throwers had a higher likelihood of ending up on the disabled list.

This finding also raises a cause-effect issue. Perhaps the extreme non-strike throwers are already suffering injury impacts while they pitch, and this leads to poor control. Or maybe the lack of control puts the pitchers in too many high pressure, high pitch count innings, which leads to injury. However, even if the finding is due to these alternate hypotheses, it is still relevant to front office pitcher acquisition decisions.

Zimmerman's article uses the following thresholds for extreme non-strike throwers: <60% strikes; <47% zone; >10% non-intentional BBs. Pitchers in these ranges experienced a disabled list rate of 45% - 49%, roughly 10% - 15% higher than normal.

One of the best templates for a "Talking Sabermetrics" article is to find a research article at Fangraphs or Beyond the Boxscore, and then apply the findings to Astros' players. If you have followed the Talking Sabermetric series, I suspect that you already noticed the cookbook approach. That's what I did here.

I examined the status of Astros' starting pitchers (excluding those whom are non longer with the organization) relative to the three "non-strike thrower" thresholds. (I used BB% instead of non-intentional BB%, by the way.) I calculated strike percentage from TexasLeaguers.com pitch f/x data, with the remaining two categories derived from Fangraphs. The results are shown below.

	Strike %	BB%	Zone%	Red Flags
Norris	64.3%	9.0%	48.7%	-
Harrell	62.9%	9.4%	49.0%	-
Gonzalez	*56.7%*	7.6%	48.8%	1
Lyles	61.4%	6.7%	48.7%	-
Keuchel	60.0%	*10.3%*	*43.5%*	2
Weiland	61.3%	8.9%	*40.6%*	1

Setting aside whether these measures help us evaluate injury risk, they obviously tell us a lot about each pitchers' control. Fortunately, neither Harrell, Norris, or Lyles are among the extreme non-strike throwers in any category. All three pitchers are expected to be part of the Astros' rotation next year, and they didn't have the control problems that would mark them as particular injury risks. On the other hand, based on the Fangraphs' data, their control results don't suggest that they have an above average chance of avoiding injury (a zone percentage above 51.5%).

Edgar Gonzalez, Dallas Keuchel, and Kyle Weiland each qualifies as an extreme non-strike thrower in at least one category. Gonzalez generally appears to have good control (lowest BB rate among these pitchers). However, he fell below the 60% strike threshold. Notably, strike % is the weakest of the three indicators for injury risk. So, I don't think the result is alarming for Gonzalez (particularly given the sample size).

I was interested in including Weiland in the comparison, because we know that he pitched with a shoulder injury during his stint on the major league roster. And, indeed, he he had the lowest zone percentage among the selected Astros' starters. The only Astros' starting pitcher with a lower zone percentage was Gallaraga, who was released before the season ended.

Dallas Kuechel failed in two categories (zone percentage and BB percentage) and barely met the 60% threshold for strike percent. Keuchel's results seem more alarming; his control was terrible. Perhaps even more concerning is that Keuchel's minor league record indicates that he has succeeded as a control pitcher. His major league walk rate in 2012 is more than twice his minor league career rate. During the season, I questioned whether Keuchel had changed his approach to pitching when he was called up to the majors. However, given the results in the fangraphs article, I now wonder if injury or fatigue could have been involved in his control issues. He isn't a pitcher I would expect to have injury problems, but a medical check might not be a bad idea.

Do you think that the possible connection between injury risk and control tendencies will affect the Astros' off-season pitching moves?

Looking for the next Jack Cust... (Talking Sabermetrics)

clack — Fri, 19 Oct 2012 16:38:34 -0000

"Talking Sabermetrics" has covered advanced hitting stats like wOBA and wRC+, and now we use them to screen ML and IL hitters.

Scott Moore, Bryan LaHair, Justin Ruggiano, Justin Maxwell. Those are three of the 4A hitters who showed surprising potential at the major league level in 2012. There is something fascinating about looking for major league help among the ex-prospects buried in AAA because their age relegated them to "non-prospect" status. They are called 4A players because they are too good for AAA but never made it in the big leagues. Some of them were never given sufficient big league at bats during their prime. Many of them are poor fielders who play non-premium defensive positions. The fact that the Astros will have a DH in 2013 makes this a more interesting search than previous seasons.

Don't get me wrong: I am very interested in the Astros signing veteran major league hitters. But I also expect the Astros to sign some 4A hitters as NRIs (non roster invitees). If the NRI signee gets lucky in spring training, he may start the season on the ML roster (like Travis Buck in 2012). Or they may start the season in AAA, but end up on the ML roster later in the season (see Scott Moore).

I put Cust's name in the title for a couple of reasons. First, Jack Cust was one of the most successful signings of a 4A player when the Oakland A's plucked him from the Padres' AAA team in 2007. He averaged a wOBA over .370 for the next four seasons in Oakland. Cust was a sabermetrics success story. Second, Cust was one of Jeff Luhnow's first NRI signings of 2012. Cust didn't make the Astros' roster and ended up signing with the Yankees' system. In the International League during 2012, Cust had perhaps his best AAA performance (wOBA .394, wRC+ 147) since that 2007 season when he was signed by the A's.

I will focus on the Mexican League and International League. Both are considered AAA leagues. Why focus on these two leagues? Luhnow has indicated that he will look more closely at the talent in Mexico than the Astros have in the past. The International League has a low run scoring environment--significantly less hitter friendly than the Pacific Coast League--which means that the batting stats are less likely to be inflated.

Mexican League

(Note: Keep in mind that the Mexican League is a high run scoring environment)

1. Leonardo Heras (age 22) CF. Heras doesn't fit the 4A description, and that's why I highlight him at no. 1, even though he isn't the top hitter in the Mexican League. Heras' young age makes him a prospect. In addition, unlike others on this list, he plays a premium fielding position. Advanced stats of interest:

wRC+ 139 wOBA .410 OPS .945 ISO .230 BB 10% K 16%

Sure, you have to discount the stats somewhat because of the league's hitting environment. But at age 22, and in only his third professional season, he has potential for additional development and improvement. Heras showed the ability to hit for average, hit for power and steal bases. He also has a high speed score. At mid season, Fangraphs suggested that he deserves a shot in at least the PCL or IL:

Heras is looking elite in a league that is 6 years older than him on average. If this is not the kind of player the ML exists to find, then who is?

Perhaps Heras' size (5-8, 155) has been an impediment to attracting major league attention. However, he did hit 24 HRs, which indicates more strength than you would expect for his size. Moreover, for a .320 hitter, his .347 BABIP is not overly high, considering the league, suggesting that he has been more than just lucky. He might be an interesting addition at the AAA level. Apparently, Heras is expected to be the lead off hitter for the Mexico WBC team; I'm not sure what effect that would have on his signability.

2. Brett Harper (age 30), DH/1b LHB. I limited my search to hitters at age 30 or younger, and Harper was the best Mexican League hitter in that age range. Early in his career he was the best power hitter prospect in the Mets' organization, but was hurt by playing for a team in a non-DH league. He has hit well for MLB affiliated AAA teams over the years. In 2012, the lefthanded batter launched 27 HRs in only 368 PA and posted an ISO over .300. He is the son of a major leaguer. Some selected advanced stats in the Mexican League:

wRC+ 164 wOBA .449 OPS 1.009 ISO .302 BB 11% K 20%

3. Alex Valdez (age 27) 3b/DH. A former A's prospect, Valdez had stints with the Nats and Red Sox AAA teams in recent years. Showed some HR power with decent speed on the base paths. He is currently playing in the Venezuelan Winter League. Some selected advanced stats in the Mexican League:

wRC+ 150 wOBA .428 OPS 1.070 ISO .238 BB 9% K 14%

International League

1. Mauro Gomez (age 27) 1b/3b/DH. The Red Sox signed Gomez as a minor league free agent and he rewarded them when he won the International League MVP. With the trade of Adrian Gonzalez, Gomez received a little over 100 PAs with the Red Sox, posting a ML line of .275, .324, .422. His walk rate isn't great, but he has shown good power. Red Sox manager Bobby Valentine spoke glowingly of Gomez's hitting ability. Sabermetric writer (and Red Sox blogger) Marc Normandin wrote earlier this year:

Gomez isn't likely to be some future star, but there are plenty of scouts who like his bat a whole lot, and think that with a real chance in the majors he could turn into something productive.

I'm not sure if the Red Sox will re-sign Gomez. But he won't beat out Ortiz or Middlebrooks for DH or 3b, and I have the feeling that Boston will seek to acquire a bigger name hitter for 1b. Some advanced stats for the International League, which Gomez led in overall offense:

wRC+ 165 wOBA .420 OPS .960 ISO .279 BB 8% K 21%

2. Corey Brown (Age 26) OF, LHB. Brown is a former Oakland A's 1st round pick (2007) out of Oklahoma State. The Nats traded for Brown in 2010, and I'm sure that Bo Porter knows a lot about him. Brown has demonstrated both good power and base stealing speed. But the question mark during his career has been contact ability and batting average. However, he may have made a break through in AAA this season, showing both power and a decent batting average. He ranked second in the IL for wOBA and third in wRC+. Brown had a cup of coffee with the Nats in 2012 and got some attention with a game winning walk off hit. It's hard to predict whether Brown will be available either through trade or as a minor league free agent. Brown's age puts him on the borderline of prospect status, and the Nats may want to keep him in their plans. Some advanced stats:

wRC+ 144 wOBA .394 OPS .888 ISO .238 BB 11% K 25%

3. Ernesto Mejia (Age 26) 1b. Mejia was the Braves' player of the year in AAA. Mejia, 6-6 in height, hit 24 HRs for Gwinnett. His walk rate is weak, but he appears to have legitimate power for a DH role. Advanced stats:

wRC+ 135 wOBA .377 OPS .849 ISO .206 BB 6% K 24%

4. Other Notables... Josh Satin (1b, 3b, Age 27) of the Mets provides a good walk rate and moderate power, and ranked sixth in the IL for wRC+ and wOBA. Matt LaPorta (1b, Age 27), an uber hitting prospect whom the Indians acquired in the Sabbathia trade, is out of options and could become available this year. LaPorta continued to perform well in AAA (.366 wOBA and .208 ISO), but his major league offense has been a huge disappointment across more than 1,000 PA. LaPorta underwent hip surgery at the end of the season.

Talking Sabermetrics: Pitching in the American League

clack — Tue, 16 Oct 2012 10:58:41 -0000

A recent theme for the "talking sabermetrics" series is the Astros' move to the American League. Perhaps you were trying to suppress thinking about the Astros' move, pushing it to the deep recesses of your mind. But it's true. The move will happen. And sooner rather than later.

For today's article, we will look at some statistical nuggets about the difference between AL and NL pitchers.

Do NL Pitchers Throw More Fastballs?

This is something I've heard for 30 years. Supposedly National League pitchers use the fastball more frequently than American League pitchers. I assumed it was true. But the data doesn't support this claim. If anything, in recent years AL pitchers relied more heavily on the fastball than NL pitchers.

Because base stealing traditionally is viewed as a more important tactic in the NL, people surmise that NL pitchers will throw more fastballs in order to control the running game. Perhaps the adage about NL pitchers throwing more fastballs was true at one time. But over the years, many coaches and pitchers have changed leagues. I wouldn't be surprised to see differences between the leagues decline over time.

This 2009 Hardball Times article used pitch f/x data over a three year period to debunk what it called the "myth" of higher fastball usage in NL. 58.09% of total NL pitches were fastballs, compared to 59.05% in the AL. The article also points out that the adage about NL reliance upon fastballs contradicts another adage: junk ballers improve their performance moving from the AL to the NL.

Does the conclusion from the 2009 article still hold up?

I examined fangraphs data on AL and NL teams' pitching usage. By using data at the team level, the data will reflect the actual usage of pitchers, so that there is no need to separate relievers and starters. In both 2011 and 2012, the median team fastball percentage is higher in the AL than the NL.

The average fastball percentage for a AL team is 58.06% compared to 57.16% in the NL.

Some would suggest that pitchers batting in the NL would see more fastballs than the average hitter, since they are less experienced hitters. And, if that is true, it suggests that the AL advantage in fastball usage must be even higher for pitches seen by non-pitchers.

Another bit of speculation you sometimes hear is that AL pitchers throw more breaking pitches because the sluggers are so good that they have to resort to "fooling" them. However, the data on AL fastball usage doesn't support that notion. We often hear hitters say that the best pitch is a well located fastball. And that may explain the AL fastball percentage.

Other Pitch Types and Velocity

Not only do the AL teams throw a higher percentage of fastballs, but the average velocity is higher than in the NL. In 2012, the average AL team's FB velocity is 91.88 mph, compared to 91.28 mph in the NL. Since fastball velocity generally is correlated with pitching success, this may suggest that AL pitching is better than NL pitching. However, this observation is far from proving that as a fact.

Now let's look at other types of pitches and see if the percentage usage favors either league. The data reflect the average 2012 AL and NL team, with italics used to show the league with highest usage for a pitch.

AL / NL

(percentage)

Slider 13.93 / 14.81

Cutter 6.19 / 5.4

Curveball 10.0 / 10.6

Change Up 10.18 / 9.56

Admittedly the differentials generally are small, so don't read too much into the league differences. The data shows that the NL tends to throw the slider and curveball more, while the AL pitchers are more likely to throw cutters and change ups. The change up in the AL is 1.27 mph faster than in the NL, which is consistent with an average fastball that is 0.6 mph faster. Maybe AL pitching strategy relies more on "fooling" hitters---if you consider the change up as the pitch most aimed at tricking batters.

Junk ballers

As noted previously, there is a general assumption that junk ballers and soft tossers can fare better if they move from the AL to the NL. I don't have a definitive answer to that question. But the 2012 data, above, suggests that the average velocity for NL pitching is lower, and perhaps relies more on traditional breaking pitches than the AL.

Looking at the Fangraphs 2012 leaderboard for qualified pitchers, the NL has twice as many pitchers (10 to 5) with an average FB velocity below 89.5 mph. The AL has no qualified pitchers with a FB velocity below 86 mph, while the NL has three. There were two more teams in the NL, which may explain some of the difference. And we are looking at small sub-groups, which limits our conclusions. But the comparison doesn't dispel the notion that soft tossers may have a safer haven in the NL.

This makes me wonder if a soft tosser like Keuchel will have a tougher time moving to the AL. Keuchel had the lowest average velocity (89.0) among Astros' starting pitchers, followed by Edgar Gonzalez (89.5).

In addition, the Astros' bullpen seemed to lack high velocity arms, even by NL standards. Without some reinforcements, the Astros' bullpen may appear even worse when it faces AL hitters.

Rhiner Cruz (95.0) had the only bullpen arm comparable to the higher end velocities frequently seen in other teams' bullpens. However, Cruz's control and command issues limited his usage in high leverage situations.

Setting aside Cruz, Fernando Rodriguez (93.9) was the power arm in the bullpen, and his velocity isn't elite. Jose Valdez (93.8) had the next highest average velocity out of the bullpen, but I would not put too high expectations on a career minor leaguer.

Use of Pitchers

The DH has some direct impacts on the way pitchers are used in AL. NL pitchers may be removed from a game for non-performance reasons; in other words, the offensive situation may compel the need for a pinch hitter. AL pitchers are more likely to be removed for bad or deteriorating performance.

As pointed out by this 2009 analysis (for fantasy purposes) at the Hardball Times, the AL starters tend to throw deeper in games and are more likely than NL starters to be removed in the middle of an inning. Not surprisingly NL starters are more likely to be removed at the end of an inning than AL starters.

Comparing 2012 data at Baseball-Reference, AL teams average 5 complete games, while the average NL team has 4 complete games. (The Astros had 3 complete games, in case you were wondering.) The average AL starter threw 1 more pitch per game started than the average NL starter in 2012. The countervailing effect of the DH on starting pitcher usage is that the AL lineups are tougher, making starting pitchers more susceptible to removal for performance reasons. That may explain why AL pitchers pitched the same number of innings per start as NL pitchers in 2012. The AL pitcher's tendency to pitch deeper due to the DH appears to be offset by more pressure for performance related pitcher removals.

The DH indirectly affects pitcher usage patterns based on its impact on the roster. With a DH, teams may have less need for pinch hitters, allowing teams to carry more bullpen pitchers. Since starting pitchers are more likely to be removed mid-inning than in the NL, the use of bullpen platoon specialists becomes more frequent. As Cee Angie noted in her TCB article, this creates a need for more hitting specialists, resulting in a roster dilemma for AL teams.

According to Baseball-Reference data for 2012, lefthand batters and lefthand pitchers in the AL constituted larger percentages of total plate appearances than in the NL (46% to 42% among batters and 30% to 29% among pitchers). This is consistent with greater use of platoon specialists for both batting and pitching in the AL. But in the AL, pinch hitters are used in situations with 16% more leverage than pinch hitters in the NL. (This isn't surprising, given the effect of the DH.)

Some thoughts: don't expect the need for fewer LOOGYs or less platooning of batters when the Astros move to the AL. If anything, there will be more pressure for platooning on both offense and defense.

How will this affect the Astros' roster decisions?

Talking Sabermetrics: Third Base Coaches And Sending the Runner Home

clack — Tue, 09 Oct 2012 14:46:29 -0000

Dave Clark seems like a great guy, a coach who is well liked by players. But his decisions as a third base coach are not popular with the fans. At least that is the impression we get from the internet. (And we all know that everything on the internet is true.) AstrosB at SB Nation Houston has mentioned the popular view of Clark, saying that he is "affectionately known as 'Stop Sign.'" And, in fairness to Clark, most teams' third base coaches make decisions that are unpopular with the fans---that's seems to be the nature of the job.

Sabermetrics Looks At Sending The Runner

I admit that I have complained a few times about Clark's third base decisions. But two articles at Beyond the Boxscore make me wonder if Clark is getting a bum rap. BtB's Jim Gentile has some great analysis in "The Slow Death of Aggressive Baserunning" and "Parsing the Demise of the Windmill." These two articles examine the decision to hold or send a runner home from 2d base with a single. If Clark is viewed as Mr. Stop Sign, that may just demonstrate that he is in line with the baseball trend of holding runners at 3d base.

Gentile's articles show that, with runner on second and a single, the hold rate at 3d base has increased continually since the 1950's. The stop sign at 3d base has increased from 25% in the 1950's to 37% in recent years. I don't want to over-generalize, but the growing trend of more conservative hold rates at 3d base seems to cross situational factors like outs, stage of the game, and scoring margins. For example, teams behind by a big margin tend to hold runners more than teams which are ahead by a big margin---and this is true throughout the last 60 years; however, the trend over the years toward more conservative hold rates affects teams on both sides of that scoring margin.

An interesting question is whether the recent trend toward more conservative decisions by the third base coach is leaving too many scoring opportunities on the table. That is difficult, perhaps impossible, to determine. But my gut feeling is that the trend probably reflects improved efficiency in scoring runs. First, Gentile's data indicates that the hold rate trend is accompanied by a slightly growing rate of the runners ultimately scoring. That doesn't prove that the trend is more efficient, but it suggests that it might be. Second, most likely the trend reflects the growing knowledge and experience of managers and coaches over time. Given the broad mix of ages and generations on MLB coaching staffs, it makes sense that experience with the stop sign is handed down from coach to coach, which results in incremental improvement over time. And don't forget that statistics and scouting information are more widely available to teams in the later years. If a team can succeed by bucking the trend, an enterprising manager somewhere would do it.

So, back to Coach Clark. We don't have data on his specific hold rates. But, given the continuing trend to hold more runners, and the possibility that this trend may produce greater scoring efficiency, maybe we shouldn't be so harsh in criticizing Clark for his stop signs. Furthermore, the short LF at Minute Maid Park probably should result in Clark exercising a higher percentage of stop signs compared to third base coaches in other parks.

There could be any number of additional hypotheses for the trend toward more conservative third base coaches. Have outfield arms improved that much? Are players slower? Are ballparks smaller? But I am skeptical of these reasons.

My guess is that the trend reflects a growing acceptance of the value of conserving outs. We know that teams used to be more aggressive in stealing bases and more willing to give up outs to move runners. Sabermetrics probably is one factor in the changing attitude, with its focus on OBP and avoiding outs. The changing run environment over the years, particularly the higher HR rates, may also play a role in the manager's mind set. Losing too many runners on the base paths may reduce the number of 3 run HRs that win games.

A Look At the Stop Sign and Win Probability

An interesting way to analyze the third base hold decision is through the lens of win probability. (This is the foundation of Win Probability Added, WPA, which shows the impact of an event on the probability in real time of winning the game.) And the Win Probability Inquirer tool at Hardball Times can be utilized to analyze the win probability associated with particular base, out, inning, and score situations. Of course, the results will be based on average players and won't take into account all of the specifics, like the base runner's speed, the outfielder's arm, the quality of subsequent batter, and so forth, that are needed for particular decisions. But it might give us some insight on the third base coach's decision.

If I had the time to model every base, out, inning, and score situation, perhaps the exercise would be more useful. But, I am not that interested in third base coaching decisions. As an illustration, I will look at the runner on 2d with the batter hitting a single for a more or less neutral situation: tie game in the middle innings. For each of the three outcomes (hold the runner at 3d, runner scores, or runner is out at the plate), I determine a post- event base-run-out state and use the Inquirer tool to calculate a win probability for the outcome. Note that I assumed that the runner who singles stays at first on an out at the plate; if the complication of a runner moving up on the throw to the plate were to be added into the analysis, it would improve the "send the runner" decision ever so slightly.

The focus of this analysis is to determine the break even success rate required to send the runner ("break even send rate"). This procedure solves for the expected success rate for sending the runner home which will produce a better win probability than holding the runner. For example, if the break even send rate is 50%, then the third base coach should not send the runner unless he believes that the runner has more than 50-50 chance of scoring. The third base coach's assessment of the scoring probability would include all of the relevant factors, such as the location of the batted ball, the outfielder's arm, the runner's speed, etc. As added information, I also show the actual hold and scoring rates based on Gentile's article.

				5th Inning, Tie Game
				Single w/ Runner on 2d

		Win Probability			Break Even	MLB Avg.	MLB Avg.
	Runner Held		Scores	Out	Send Probability	Held	Out

No out	65%		67%	50%	88%	55%	1%
1 out	58%		63%	46%	71%	43%	3%
2 out	49%		60%	45%	27%	17%	5%

Notice that a very high expected success rate (88%) is required in order to send the runner home with no outs. That means that the third base coach must be nearly certain that the runner won't be thrown out with zero outs. By contrast, the third base coach should just roll the dice with two outs. As long as the probability of being called safe at home is slightly above 1 in 4, the third base coach should send the runner with two outs. Even with one out, the third base coach's threshold before he should send the runner is fairly high, 71% probability.

The MLB Average is also expressed as a percentage, but it is a much different type of value, since it doesn't indicate probabilities, but rather the actual average hold and thrown out rates. (If you want to know the score rates, it's just 1 minus the out percentage.) The high and low break even probabilities are supportive of the high hold rate with zero outs and the low hold rate with 2 outs--definitely an indication that the decisions are at least roughly consistent with win probabilities. If anything, I wonder if there may be some advantage to holding more runners at third base with no outs and perhaps even 1 out. I don't have enough information to be confident in making that statement, but it seems like a 88% probability is a high enough threshold for sending the runner to support more than a 55% hold rate with no outs. On the other hand, the 1% current out rate experienced in that situation is so low that refinements in the hold decision may have only a marginal impact.

This type of analysis also gives me appreciation for the third base coach's job. We know that Dave Clark isn't taking an I-Pad into the third base box so that he can work on a spreadsheet when he makes his decision. (And even if that was possible, how easy is it to distinguish a 70% probability from a 88% probability in real time?) But think about all of the factors which are not included in the analysis, above, but should affect the decision: not just the runner's speed and outfielder's arm, but also the offensive ability of subsequent batters, the way that the ballpark plays, whether the opposing pitcher is tiring, and the ability of the catcher to block he plate.

Do you have any thoughts about the MLB trend toward holding more runners at third base? And for what it's worth, Gentile's data indicates that the AL is slightly less likely to hold runners at 3d base than the NL. (This extends prior to the DH rule, by the way.) Will that affect the Astros' tactics next year?

Final Game Thread for 2012 Astros vs. Cubs

clack — Wed, 03 Oct 2012 18:31:51 -0000

The Astros try to end the 2012 season on a high note with a sweep of the Cubs.

Astros v. Cubs, Game 2 Game Thread

clack — Wed, 03 Oct 2012 00:11:40 -0000

Current Series

Astros lead the series 1-0

Mon 10/01	WP: Lucas Harrell (11 - 11) SV: Wesley Wright LP: Jason Berken (0 - 3)	3 - 0 win
Houston Astros The Crawfish Boxes @ Chicago Cubs Bleed Cubbie Blue Wednesday, Oct 3, 2012, 1:20 PM CDT Wrigley Field Edgar Gonzalez vs Travis Wood Mostly cloudy,rain. Winds blowing out to center field at 5-10 m.p.h. Game time temperature around 65. Complete Coverage >
Wed 10/03		1:20 PM CDT

Current Series

Astros lead the series 1-0

Mon 10/01	WP: Lucas Harrell (11 - 11) SV: Wesley Wright LP: Jason Berken (0 - 3)	3 - 0 win
Houston Astros The Crawfish Boxes @ Chicago Cubs Bleed Cubbie Blue Wednesday, Oct 3, 2012, 1:20 PM CDT Wrigley Field Edgar Gonzalez vs Travis Wood Mostly cloudy,rain. Winds blowing out to center field at 5-10 m.p.h. Game time temperature around 65. Complete Coverage >
Wed 10/03		1:20 PM CDT

Talking Sabermetrics: OPS vs. wOBA and Cubs vs. Astros

clack — Tue, 02 Oct 2012 14:46:35 -0000

Two quick hits on the sabermetric front today. First, let's talk about OPS vs. wOBA and the relative effect of the two metrics on Astros' hitters. Second, a nugget regarding the difference between the 2012 Astros and 2012 Cubs.

OPS vs. wOBA

OPS (on base plus slugging) and wOBA (weighted on base average) are two offensive statistics we often use. Earlier this year, I discussed the difference between OPS and wOBA, pointing out that OPS is a quick and dirty measure of offense, but clearly inferior to wOBA in terms of accuracy. Both OPS and wOBA are correlated with runs, but wOBA is more closely related to scoring runs. Despite the fact that wOBA is the preferable metric, I admit that I sometimes use OPS. One of the main reasons is that wOBA, a fangraphs statistic, is not uniformly available on other baseball statistic web sites (like baseball-reference.com), which makes OPS easier to use in comparing data across multiple sources. The next link should make me think twice about using OPS when wOBA is available.

Hardball Times' recent article on the marginal effects of offensive events on OPS and wOBA is worth reading. The article shows that OPS may be pretty good at measuring offense at an aggregate team level, but it falls well short of wOBA is measuring the marginal effect of specific offensive events. That's not surprising since wOBA is based on linear weights, which measures the offensive value of specific events like walks, singles, doubles, HRs, etc. But the article demonstrates that the inaccuracy of OPS is surprisingly large if we focus on the change in OPS caused by each specific event. For example, on average: OPS over values a single, relative to a walk, by 52%; OPS over values a double, relative to a walk, by 98%; OPS over values a double, relative to a single, by 30%.

The article also finds that simply changing the weighting between OBP and SLG in the OPS formula is inadequate to correct the distortion. The reason is that the relationship between OPS and wOBA is variable (not uniform) at the individual player level.

This made me wonder which Astros' hitters are most over valued or under valued if you use OPS, rather than wOBA, to measure their offensive performance. In order to make this comparison, I created OPS and wOBA indices based on assumed averages of .717 for OPS and .315 for wOBA. (In other words, the index is a ratio of the player's OPS or wOBA to the assumed ML average.)

The following Astros' hitters are undervalued the most by the OPS metric, because their wOBA index is higher than their OPS index: Brian Bogusevic (1.05), Jordan Schafer (1.04), Chris Snyder (1.03), and Jose Altuve (1.01). The following Astros' hitters are overvalued the most by the OPS metric: Tyler Greene (.95), Matt Downs (.95), Fernando Martinez (.96), and Matt Dominguez (.96). Note that the ratio in parenthesis is the wOBA index as a percent of the OPS index.

The differences probably aren't a big deal. But the moral of the story? Don't just look at a hitter's OPS...the wOBA will tell a more accurate story.

Cubs vs. Astros Records

The Astros may have been lonely in the 100 loss club, and they took the direct route in bringing some company home for dinner. Monday's Astros win over the Cubs pulled the cubbies down into the 100 loss swamp. Currently the Astros have 106 losses, and the Cubs, 100 losses. Both teams are clearly the worst in the majors, with losses outdistancing other teams by at least three games.

What's the main difference between the Cubs and Astros? By that, I mean, what characteristic is most responsible for making the Cubs a better W-L team than the Astros?

I suggest looking at the defensive components of team WAR (fangraphs). The Cubs are +11 runs and the Astros are -45 runs on defense. That is a 56 run fielding differential. Assuming that 10 runs equals a win, that means that defense accounts for somewhere between a 5 and 6 wins difference between the two teams. Given that the two teams are separated by 6 games in the standings, defense appears to be a major cause of the difference in record.

You can also look at second base defense to recognize one of the largest discrepancies. Darwin Barney is +12 and Jose Altuve is -16, for a total of 28 runs difference in fielding by the two starters at that position---almost 3 wins difference. This kind of isolated comparison is cherry-picking to some extent. So, don't take it as "Jose Altuve's defense is the reason that the Astros have the worst record." That wouldn't be a valid conclusion. Moreover, viewing only the fielding component also ignores the fact that Altuve made substantial offensive contributions. But it does underscore the need for Jose to improve the defensive part of his game.