Sorry I've gone AWOL, the last two months contained a heavy dose of pneumonia (which sucked), midterms (which suck but it's hard to complain about college), and spring break (which ruled).  With only five to seven games left in the season for the D-League teams, we now have a very concrete idea of which teams are good and which are bad. The advanced stats still have use, though: the four factors give us a great idea of why each team performs as they do. Here is the full chart, follow the jump for leaders and trailers pace, efficiency, and each of the four factors.

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In the middle of a busy week, so enjoy the simple beauty of the D-League advanced team stat chart without my boring words.

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To date, the Tulsa 66ers have been among the elite in the NBA D-League.  The 66ers are riding a 12 game winning streak and their 20-6 overall record leads the league.  According to their tempo-free profile, this is no fluke.  Tulsa's +6.5 efficiency differential trails only Rio Grande Valley and Erie and by an insignificant margin.   However, the call-ups of guard Zabian Dowdell (by the Phoneix Suns) and forward Larry Owens (by the San Antonio Spurs) could make things more difficult for the D-League leaders.

Dowdell's statistical profile this year is varied.  So far, the guard has only managed a 49.8% true shooting percentage, which ranks 153rd out of 193 D-Leaguers with at least 130 minutes played.  However, he was much better in 270 minutes (not much of a sample) last season, when he put up a 57.5% mark which would currently rank in the top 50.  More importantly, given his size (6-3, 191) and position as a point guard, Dowdell has an assist-to-turnover ratio of 2.6, which ranks 9th in the D-League so far.  He has shown the ability to score in the past, and will probably need to do so at a better rate to have success in the NBA.  However, it appears clear to me that the real reason Dowdell is getting his chance in the Association is due to his point skills, not his scoring.

Judging by this piece from Scott from earlier in the month, Owens's call-up might be a bit of a surprise, as he wasn't on Scott's shortlist of call-up candidates.  However, the Spurs saw something they wanted in the 6'7" forward, and I think I see it too.  Owens is a solidly efficient scorer, with a 55% TS% (ranking 83rd out of 193) and particularly good from three (25/67, 37%).  HIs 5.5 rebounding average is respectable, particularly on a slightly slow team like Tulsa in only 31 minutes per game.  Finally, Tulsa has been a good defensive team for the past two seasons, and Owens has been a large part of both those teams.  

Although I'm sure their teammates are happy for their new opportunities, the departure of Dowdell and Owens could make things tougher for the Tulsa 66ers going forward.  Such is life in the D-League, as the ever changing talent landscape affects teams on a nearly daily basis.  The 66ers have managed to maintain their organizational success regardless of the names on the roster over the past two seasons, and personally, I expect them to continue to do so in 2011.

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The Reno Bighorns finished the 8th week of the D-League season with a 15-8 record and a similarly impressive efficiency differential of 4.5 points per 100 possessions.  The major reason for that success is their domination of the charity stripe.  The Bighorns are tied for first in the D-League in offensive free throw rate (free throws made per field goal attempted) and are third in defensive free throw rate.

It's not that the Bighorns are a particularly good shooting team, or that their opponents aren't making their shots at the line.  They're shooting 73.5% and "allowing" a 72.4% against.   As with most great scorers and most great scoring teams, the Bighorns excel at attacking the basket.  The Bighorns currently have three players averaging more than five free throw attempts: recent assignee PG Jeremy Lin (7.4 per game), injured PG Aaron Miles (5.8 per game) and G D.J. Strawberry (5.9 per game).  Overall, the team is taking 33 free throws per game, a very high number.

On defense, preventing free throws is pretty simple: don't foul.  The Bighorns tend to avoid foul trouble well, as none of their big-minute, big-scoring players average more than four fouls per 40 minutes of game time.  Only two players who have played significant minutes have foul issues: Hassan Whiteside (5.35 per 40 minutes) and Doug Thomas (5.83 per 40 minutes).  Unsurprisingly, these players don't play heavy minutes.  It may be related that the Bighorns give up a fairly good effective field goal percentage - 51% - but their overall defense is above average, at a 104.3 defensive rating.  This suggests to me that both their wing players are good at keeping their man out of the lane and that the post players are able to defend the hoop (although not as well as some teams) without fouling.

The Bighorns have been above average on both ends of the floor this year.  A large portion of that success has come because of their dominance of the free throw lines.   As players like Miles and Lin contend for and potentially receive NBA call-ups, we may see this dominance decrease, but for now we should expect the Bighorns to continue to win D-League games and to win them at the line.

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This week, I'd like to focus on one of the oddest teams in the D-League, at least according to the advanced statistics: the Texas Legends. The Legends boast the most efficient offense in American professional basketball, scoring 115.2 points per 100 possessions, better than 2nd place D-League team Utah (110.1) and the San Antonio Spurs (112.1), who lead the NBA.

Given the Legends' roster, this isn't surprising.  They have Joe Alexander,  Sean Williams, and Justin Dentmon all scoring at least 15 points per game and had Antonio Daniels and Dominique Jones for more than half of the season as well.  Daniels, Williams, and Dentmon all sport True Shooting percentages above 60%.  The team ranks above average in every offensive factor - they shoot the ball well, they hit the offensive glass hard, they get to the line (and shoot very well there), and they don't turn the ball over.

However, for all their offensive wizardry, they have been completely incompetent on the defensive end.  The only pro team with a worse defensive rating than the legends is the Idaho Stampede at 114.2.  The Legends check in just slightly ahead at 114.0, worse than the worst NBA team, the Phoenix Suns.   Unfortunately, it's difficult to prescribe just why the Legends are having this problem.  Sean Williams has a decent defensive reputation - as far as I can tell - so the middle shouldn't be the main problem.  However, the Legends get killed on the defensive glass, allowing 30% of opponents missed shots to be rebounded, which is even more confounding considering the size of Joe Alexander and newly starting forward Keith Clark.  The fact that the Legends are giving up an effective field goal percentage of 53% also suggests that teams are having no trouble getting easy shots.  Just to compound all of this, teams don't have issues getting shots up against the Legends, as opponents only turn the ball over 15% of the time.

I haven't seen nearly enough of the Legends to explain why the defense has been so incredibly awful, but that's why they have only managed an 8-7 record despite a hyperefficient offense.  If you have any explanations, I'd love to hear them in the comments section.  

Reggie Williams will go down as one of the best players to ever play on D-League courts.  Williams tore teams apart for 31 games in 2009-2010 with the Sioux Falls Skyforce, scoring 26.4 points per game and chipping in 5.5 rebounds, 3.2 assists, and 1.5 steals.  

"Surgical" describes Williams's play perfectly; he only required 16 shots per game (and 6 trips to the free throw line) to create the offensive destruction he unleashed on the doomed defenses of the D-League.  His efficiency numbers tell an even more frightening story: a 67.6% true shooting percentage and a 118 offensive rating both ranked in the top 5 in the D-League last season.  Players just don't put up TS% numbers like that.  Only four players in all of division 1 managed it against NCAA defenses in 2009-2010.  Only three D-League players did.  

To truly put it in perspective, there isn't a single NBA player since the inception of the three-point line in 1979  to score as efficiently as Williams did with the Skyforce last season while using at least 24% of his team's possessions and playing 30 minutes per game.  The closest are Sir Charles Barkley's two best seasons, 1987-88 and 1989-90.  Those seasons saw Barkley average 26 and 23 points respectively on 58.7% and 60.0% shooting from the field respectively.

Reggie Williams hasn't become Charles Barkley with his call-up to the association, but he's become an important and efficient player for the Golden State Warriors.  

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Although they only sit at 6-3, behind the Iowa Energy in the East, the Erie Bayhawks sport the most efficient team in the D-League through nine games in four weeks of D-League play.  With an offensive rating of 110.7 and a defensive rating of 97.4, the Bayhawks excel at both ends of the floor.  Their +13.3 differential leads the league by over 5 points.  Erie's offense doesn't have a single standout right now, with contributions coming from all across the roster.  The most efficient scoring so far has come from Nate Linhart, whose 42-71 shooting includes 12 three pointers, good for a remarkable 67.6 effective field goal percentage.  The Bayhawks' league-best defense is anchored by Christian Eyenga in the middle, who has blocked 1.13 shots per game despite only playing 24 minutes on average.

Unsurprisingly, the Iowa team which leads Erie by 1.5 games in the standings is playing at a similar level.  Iowa's defense isn't quite as stout as Erie's, checking in at 102.8 - still over four points better per 100 possessions.  On offense, the Energy are essentially equals to Erie, with a 110.4 offensive rating.  The Energy have been lead by the hyper-efficient Courtney Sims, who is converting on a remarkable 64.2% of his shots as well as 8.9 rebounds - 3.2 offensive - per game.  Kyle Weaver's sharpshooting - 19-38 from three - has him with a True Shooting percentage of 70%, numbers that are typically reserved for NCAA marksmen, and he also leads the team with 4.0 assists per game.  However, unlike with Erie, these numbers need to be toned down a bit to account for pace.  As their name suggests, the Energy play a fast game, with nearly 99 possessions per game compared to 96.8 for the average team and only 93 for the Bayhawks.

On the other side of the coin, we have the Dakota Wizards, who continue to absolutely sputter on offense.  They actually play good defense, allowing 103.6 point per 100 possessions.  However, they have been an unmitigated failure on the offensive end, below average in each of the four factors.  Most importantly, they have a terrible 43% effective field goal percentage, a full seven percentage points below average.  It's impossible to run an effective offense without making shots, and to add to that, the Wizards don't rebound well, they don't get to the line, and they turn the ball over.  Chris Johnson has been the only real bright spot on this team, particularly for his rebounding (9.4 per game) and shotblocking (3.3 per game), but also for a decent 56.3 TS%.

Other notable numbers:

Best Offense: Texas Legends (119.5)

Best Defense: Erie Bayhawks (97.4)

Best Shooting: Rio Grande Valley Vipers and Texas Legends (55% eFG)

Best FG Defense: Bakersfield Jam, Erie Bayhawks, Iowa Energy (46% eFG)

Best Offensive Rebounding: New Mexico Thunderbirds (31%)

Best Defensive Rebounding: Idaho Stampede (74%)

Best Ball Security (TO rate): Fort Wayne Mad Ants (14%)

Most Turnovers Forced: Tulsa 66ers (22%)

Most Free Throws Per Shot: Iowa Energy (.36 FT/FGA)

Least Free Throws Allowed Per Shot: Maine Red Claws (.23 FT/FGA)

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No fancy analysis this time, sorry.  For more on these stats, check out last week's post.  

For pace statistics, blue represents slow, and red represents fast.  For the others, red represents worse than average and green represents better than average.  For all stats, darker signifies farther from the average.

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In the first edition of what I plan to be a weekly feature on team-level advanced stats in the Development League, one number which stood out was the remarkable defense played to date by the Maine Red Claws.  Through the first two weeks of games, the Red Claws led the league in defensive efficiency with a 95.9 mark, a full 11 points per 100 possessions better than the league average team.  Although we can expect bigger spreads in talent in a smaller, more volatile league like the D-League, that 11 point difference would be larger than any of the elite defensive teams the NBA has ever seen (at least since 1974 and the recording of turnovers began). Larger than the Ewing Knicks (8 points per 100 in '93 and '94) and the Twin Tower Spurs (8 points better in 1999) as well.

Obviously, it's only been 5 games and this is the D-League and not the Association, but to call the Red Claws anything other than "dominant" so far would be selling them short.  After adding in their most recent game, a 119-111 victory over the Terrence Williams-led Springfield Armor, the Red Claws defensive rating fell even further to 94.4 points per 100 possessions.  

Here's the odd thing about the Red Claws: they don't have a center on their roster.  Jordan Eglseder and Magnum Rolle, the two guys on this team who can really clog the middle and block shots, have only combined to play 74 minutes for Maine due to injuries.  Their active roster contains six guards and four forwards, none of whom are listed at taller than 6'9".  The best defensive teams are usually tall and have a shot blocking presence (Patrick Ewing, Charles Oakley, Tim Duncan, David Robinson, etc.).   Despite having nobody of this kind of caliber, even relative to D-League talent, teams just can't consistently score on the Red Claws.

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Now that we're two weeks into the season, we have a decent enough sample of games to take a look at what teams are doing well and what teams are doing poorly.  For a broad look a team's performances, I use the Four Factors, created by Dean Oliver and seen in his book Basketball on Paper.  From Basketball-Reference:

How do basketball teams win games? While searching for an answer to that question, Dean Oliver identified what he called the "Four Factors of Basketball Success":

1. Shooting (40%)
2. Turnovers (25%)
3. Rebounding (20%)
4. Free Throws (15%)

The number in parentheses is the approximate weight Mr. Oliver assigned each factor. Shooting is the most important factor, followed by turnovers, rebounding, and free throws. [Editor's note: I agree with the order, but disagree with the weightings.] These factors can be applied to both a team's offense and defense, which in a sense gives us eight factors. 

First of all, to get a handle on what the factors mean for the various teams, we need to know how the league has performed so far.  League pace is down from last season from 104.5 possessions per game to 97.3.  Unsurprisingly, as the pace has gotten less frenetic, offenses are succeeding more often.  The league offensive rating (points per 100 possessions) is up to a robust 106.9 from only 97 last season.  This efficiency mark is actually equivalent to the NBA's mark so far in 2010-2011.  This can only be a good thing for D-League players, as their game is, at least superficially, far more similar to the NBA game than last year.  Shooting percentages have settled around an effective field goal percentage (field goal percentage with the extra point from threes factored in) of 50%.   Team's are rebounding 28% of missed shots, turning the ball over in 16% of possessions, and reaching the free throw line 0.3 times per field goal attempted.

The team with the largest positive efficiency differential so far is the 3-1 Erie Bayhawks, with a 111.7 ORtg and a 97.5 DRtg.  They're accomplishing this with excellent shooting (54% effective field goal percentage,  and decent offensive rebounding and ball security.  They are also playing fantastic field goal defense, allowing a paltry 44% eFG%, driving much of their success on the defensive side of the ball.

On the other side of the coin is the 0-4 Idaho Stampede.  They've actually scored at a decent rate, with a 112.5 ORtg based on average shooting and fantastic ball security (12% turnover rate).  However, they just haven't been able to do anything on defense, allowing a staggering 123.6 points per 100 defensive possessions.  In every facet of the game, Idaho has been awful, allowing a 56% eFG, allowing opponents to collect 29% of offensive boards, only forcing turnovers in 9% of possessions, and allowing opponents to reach the line more often than average. The next worst DRtg sits at 113.6 (by the Texas Legends), putting the Stampede in a league of poor defense all by their lonesome.

To see these statistics for every DLeague team, check out the PDF file below.  For pace statistics, blue means slow and red means fast, and darker colors represent the extremes.   For the others, red represents worse than average and green represents better than average, again with darker colors representing the extremes. 

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In last night's lone D-League game, the Dakota Wizards fell to the Iowa Energy, 111-103.  In the game recap on the D-League's official site the two players mentioned on the Wizards are forward Renaldo Major, who put together a fantastic offensive performance, scoring 28 points on only 14 shots from the field, as well as center Chris Johnson.  Johnson's 23 points came in a far less impressive fashion - the big man only connected on eight of his 19 shots from the field and also turned the ball over on eight separate occasions. 

In order to quantify just how inefficient Johnson's scoring was, we turn to a metric used in HoopData.com's fantastic advanced box scores: Points Contributed per Possession Used.  This statistic is defined as follows:

Points Contributed = PC = Pts + Ast*2/3 - AstFGM*2/3

Possessions Used = PU = FGA + TO + Ast*1/3 - AstFGM*1/3 + FTA*0.44

Where AstFGM are assisted field goals made.

Points Contributed per Possession Used = PC/PU

Although it's not exactly easy to just calculate this number off the top of your head, it's relatively intuitive.  The number of possessions used is based on shots taken, turnovers, assists, and free throws - the only four ways a possession can come to an end.  The number of points contributed depends on points scored (obviously) but also on the player's assists as well as how often that player's baskets were assisted. 

The fact that Johnson had eight turnovers is clearly a big factor in why his night was so inefficient, as a turnover ends a possession with zero probability of scoring.  However, when we dig into the box score, we also see that he had a ton of help scoring his 23 points.  Here are all of Johnson's made shots, from the play-by-play on the D-League's official site.

Johnson Alley Oop Dunk Shot: Made (2 PTS) Assist: Cooper (1 AST) 

Johnson Layup Shot: Made (4 PTS)

Johnson Layup Shot: Made (6 PTS) Assist: Gerrity (1 AST)

Johnson Slam Dunk Shot: Made (10 PTS) Assist: Gerrity (4 AST) 

Johnson Slam Dunk Shot: Made (12 PTS) Assist: Anderson (1 AST)

Johnson Slam Dunk Shot: Made (14 PTS) 

Johnson Slam Dunk Shot: Made (21 PTS) Assist: Gerrity (5 AST)

Johnson Jump Shot: Made (23 PTS) Assist: Gerrity (6 AST)

Johnson was able to attack the rim, scoring near the basket on seven of his eight shots, but that was due to the ability of his guards to create those opportunities.  He was assisted on five of the seven shots at the rim and on his only jumper.

Now, we have all the data necessary to calculate Johnson's PC/PU.  Johnson scored 23 points, had 3 assists, 6 assisted field goals, 19 shot attempts, 8 turnovers, and took 9 shots from the free throw line.  That comes out to 21 points contributed in 30 possessions used, or 0.7 points per possession.  In a league where the average team scores roughly 0.9 points per possession, that's very poor.  Considering Johnson took just under 30% of Dakota's total possessions - combining both on-court and off-court possessions - and used them very inefficiently, it's no surprise that they lost the game.  23 points may get him in the game recap, but Johnson should hope that NBA front offices don't find this box score.

Although many NBA fans are only marginally aware of the existence of the D-League, it played a prominent role in the association's landscape last year.  The biggest connection for mainstream NBA fans is probably when Sundiata Gaines drained a buzzer beating three-pointer to beat LeBron James and his Cavaliers in only his fifth game out of the D-League.  The D-League also produced NBA players like Reggie Williams and Anthony Tolliver, and high draft picks like Byron Mullens and Hasheem Thabeet saw time in the D-League.  With the increased influence the D-League now has on the NBA, some NBA fans may look to invest a little more time in understanding and watching their minor league system and getting to know the players it's developing.

There are, unsurprisingly, substantial differences between the D-League and the association.  In order to quantify those, I've take a look at six components of the game that should help us understand the differences between the styles of the two leagues.  They are pace (possessions per game), three pointers per field goal, free throws per field game, assists per made shot, turnover rate, and overall efficiency, all using stats from the 2009-2010 NBA and NBADL.  Follow the jump for lots of graphs.

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Floating around the rumor mill lately are reports that San Diego Padres GM will be fired after the season is over.  Towers spent the last 14 seasons as the GM of the Padres, and over that span San Diego has made the playoffs 4 times, including their only World Series appearance in 1998.  Assuming Towers will indeed lose his job, the Padres record over his Tenure will be 1107-1159, for a .478 winning percentage.

Of course, Jeff Moorad and the new Padres ownership group probably isn't terribly interested in the 1998 World Series run nor the back-to-back division titles in 2005 and 2006.  As ESPN is wont to remind us, the world of professional sports is a "What have you done for me lately?" world.  The Padres 74 win season this year certainly looks great compared to their 2008 win total of 63.  However, their run differential suggests a talent level closer to 66 wins.  Regardless, the talent on the field right now leaves something to be desired.  The question must be asked, though - what did Towers do to deserve getting fired?

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It's another down year in the North Side.  The Cubs are barely above .500, and Murphy's Law appears to be in full effect once again.  Perhaps the biggest disappointment of this season for the Cubs has been the inability of Milton Bradley to adjust to life in Chicago.  The Cubs knew they were taking a risk with Bradley, as the slugger's long list of injuries and attitude problems hardly needs to be listed here.  Now, Bradley's season is over after the Cubs suspended him for the season on Sunday. 

It's not injuries that have brought Bradley crashing down to earth after a remarkable season with Texas last year.  Bradley's played in 124 games so far, 2 fewer than last year.  Bradley's wOBA fell 78 points from last year, a difference of over 30 runs in a similar sample size.  His traditional statistics look especially poor, as Bradley's .257 batting average, 12 HRs, and 40 RBIs have drawn the ire of Cubs fans.

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Seth Smith

#7 / Left Field / Colorado Rockies

Height: 6-3

Weight: 215

Bats: L

Throws: L

Born: Sep 30, 1982

Once again, the Colorado Rockies success is the major story of the National League playoff race.  At the time of this writing, the Rockies currently sit 2.5 games in front of the San Francisco Giants for the NL Wild Card lead, with a record of 82-64 after opening up 18-28, with playoff odds below 1%.

A big part of the Rockies' good fortune this year has been the emergence of Seth Smith.  At 27, Smith has emerged as a producer at the big league level after two insignificant major league stints in the previous two seasons.  Smith's impressive stats above have impressed both traditionalists and sabermetricians alike. His .402 wOBA currently ranks 13th in the entire major leagues among players with 345 or more PAs (the amount Smith has as of Tuesday night)

Smith's contributions haven't been limited to the batter's box.   In 75 games as a LF, Smith has posted a remarkable +7.5 UZR (+18.4 UZR/15).  Smith's .913 RZR ranks favorably as well, and would tie for third in the league if he were qualified.  However, these numbers should be taken with a pound of salt, due to a small sample size and the fact that Smith did not have anything more than an average COF defensive reputation coming into the league.

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Nick Johnson

#20 / First Base / Florida Marlins

Height: 6-3

Weight: 235

Bats: L

Throws: L

Born: Sep 19, 1978

Nick Johnson's career has become one of the major oddities of professional baseball over the last decade.  Johnson debuted in 2001 with the New York Yankees, and after mediocre seasons in 2001 and 2002, Johnson broke out in 2003.  He became more selective and made more contact, resulting in a much higher walk rate (17.8% vs. 11.3% in 2002) and a much lower strikeout rate (17.6% vs. 25.9%).  We see the impact of these rates in his slash line statistics, as a .243/.347/.402 season in 2002 became a .284/.422/.472 line in 2003.

Fast forward to 2009.  Johnson's walk rates have remained fantastic since that 2003 season with New York, bottoming out in 2004 at 13.7% (vs. a league average of 8.7%) with Montreal after an offseason trade.  High OBPs and above average fielding (+3.3 UZR/150 career) carried Johnson to seasons of 4.6 and 5.3 wins respectively in 2005 and 2006.  Johnson's career never jumped to superstardom because of injuries, which forced him to miss siginificant time in both 2004 and 2008, and all of 2007.

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When reading analyses of trades past, it is very common to see the analyst insert the caveat that "we'll really know who won this trade in 3 years," or something along those lines.  Of course, it's obvious that the Yankees won that famous "trade" in which they bought Babe Ruth from the Red Sox.  Consider, though, that if Ruth had suffered a career ending injury in the first year following the trade, we'd never talk about it.  That wouldn't make it a smart deal for the Red Sox.  This is only the most obvious of examples, but the point is that we base far too much of how we evaluate trades on results, both in the immediate aftermath and in retrospective look-backs, as opposed to process.

Let us consider the following trade.  For the sake of the exercise, only the relevant information of the players involved will be presented.  No names, no teams.  This trade occurred with free agency rules in place, and arbitration rules were as they are today.  Minimum salary was roughly 140,000, and one marginal win cost roughly 750,000 dollars overall.  A free agent win cost roughly 1.5 million.  Here is the deal:

TEAM A (NL 7.5 GB OF PLAYOFF SPOT) TRADES
------------------------
PLAYER 1 - AGE: 27 POS: RP ML SEASONS: 2.5 ML IP: 159.3 CAREER WAR: 3.1 CONTRACT STATUS: PRE-ARB
AGE 25: 8.5 K/9 3.4 BB/9 29.2 IP
AGE 26: 8.6 K/9 3.5 BB/9 83.2 IP
AGE 27: 9.0 K/9 3.5 BB/9 46.0 IP
---
PLAYER 2 - AGE: 25 POS: SP/RP ML SEASONS: 1 ML IP 16.2 CAREER WAR: -0.8 CONTRACT STATUS: PRE-ARB
MINORS -
AGE 23: 7.7 K/9 4.1 BB/9 163.1 IP between AA/AAA
AGE 24: 10.9 K/9 3.6 BB/9 60.1 IP AAA
AGE 25: 9.6 K/9 2.9 BB/9 80 IP AAA
---
PLAYER 3 - AGE: 23 POS: SP ML SEASONS: 0 ML IP: 0.0 CAREER WAR: 0.0 CONTRACT STATUS: PRE-ARB
AGE 21: 8.6 K/9 3.9 BB/9 139.2 IP A
AGE 22: 8.3 K/9 2.8 BB/9 172.0 IP A+
AGE 23: 7.7 K/9 3.3 BB/9 133.2 IP AA

-----------------------------------------------------------

TEAM B (AL, 19.5 GB) TRADES

-----------------------------------------------------------
PLAYER 4 - AGE: 33 POS: 1B/DH ML SEASONS: 11 ML PA: 5409 CAREER WAR: 43.3 CONTRACT STATUS: SIGNED THROUGH AGE 33 SEASON AT 2.40MM REMAINING
AGE 31: +55 bRAA, -2 TZ, 5.5 WAR
AGE 32: +67 bRAA, -3 TZ, 6.5 WAR
AGE 33: +30 bRAA, -7 TZ, 2.7 WAR

DO NOT CLICK "CONTINUE READING THIS POST" OR READ PAST THE JUMP ("***") BEFORE VOTING IN THE POLL, OR IF YOU FIGURE OUT WHICH TRADE THIS POST IS REFERRING TO.

The point of this is to evaluate a trade without the bias that comes from the names, and knowing what happened in their careers.  Let me know who you think wins this deal.

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Marco Scutaro

#19 / Short Stop / Toronto Blue Jays

Height: 5-9

Weight: 175

Bats: R

Throws: R

Born: Oct 30, 1975

Every year sees players jump from relative obscurity to stardom.  Although Marco Scutaro's traditional numbers (.291 AVG, 11 HR, 55 RBIs) have kept him under the mainstream media radar, Scutaro is having a year that will excite any sabermetrically inclined fan.  After bouncing between 2B, 3B, and SS with Oakland from 2004-2007, Scutaro seems to have settled in as a SS with the Blue Jays, and his UZR with Toronto has been fantastic, rating at +17.5 runs in just over a full season's worth of games (+10 this year).  Not only that, but Scutaro has been an on-base machine, supplementing his .291 batting average with a 13.3% walk rate to post a Jeter-esque .385 OBP.  Combine that with his modest power (.138 ISO, best in his career), and Scutaro has been worth +15 runs with the bat as well (by FanGraphs wOBA)

Overall, Scutaro has been almost exactly worth 5 wins so far in 2009.  This is certainly uncharted territory for the 33-year-old, and it certainly begs the question of what we can expect from him going forward.  Why did a player who only put up  5.2 wins total in 5 full seasons from 2004-2008 suddenly double his career production in one fell swoop in 2009?

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The White Sox have arguably been the biggest movers and shakers of this year's soft trade deadline, adding two gigantic contracts in the forms of Jake Peavy and Alex Rios.  The White Sox, through these deals, have added over 110 million dollars of salary between 2010 and 2014.  There's no question that Jake Peavy and Alex Rios will provide some sort of production over the course of these contracts, even if it's not the level of production that the White Sox are paying for.  The question for the White Sox is whether or not they can still manage to operate from under the burden of these and other large contracts.  Before adding Peavy and Rios, the White Sox were already at a $96MM payroll entering the season - 12th highest in the league, but the 13th highest was $82MM.  The White Sox certainly belong to that second tier of large-market teams, behind the New York teams, the Cubs, and the Tigers, but more in line with the L.A. teams, Seattle, and Philadelphia. 

It's possible that the White Sox could afford to add payroll because they subtracted over 25 million dollars in payroll over the 2008 offseason.   Still, these additions have pushed them right back into that 120 million dollar range.  With the economy as it is, I find it more feasible for the White Sox payroll to remain in the 100-110 million range as it did in 2006 and 2007.  Let's take a look at the team that the White Sox will have under control for the 2010 season.

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Derek Jeter's HR totals the last 3 years (2009 excluded): 14, 12, 11.  So far, through 45 fewer games than 2008, Jeter already has 12 HRs.  Much has been made about the homer-increasing effect of the New Yankee Stadium.  Let's take a look at where the 10 HRs Jeter has hit at the new park map out at the House that Ruth Built.  Red dots represent balls that would not make it out at Old Yankee Stadium.

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UPDATE: THE WHITE SOX HAVE ACQUIRED ALEX RIOS FROM THE BLUE JAYS FOR NOTHING IN RETURN. In the wake of this news I've decided to bump this analysis to the top.

Buster Olney today has reported that 28 year old Blue Jays OF Alex Rios has been claimed on waivers.  As Olney states in the article, this leaves the Blue Jays with three options.

• They could work out a trade with the team that claimed Rios.
• They could pull him back from waivers, and keep him for themselves the rest of this season.
• They could simply allow the team that claimed him to take him, at no cost.

The obvious question then remains.  What should the Blue Jays do with Rios?

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As has been much discussed in the Sabermetric blogosphere, the Philadelphia Phillies made the questionable decision to sign Raul Ibanez to a 3 year, 31 million dollar deal while simultaneously letting a similar player in the younger Pat Burrell walk without even offering arbitration.  Raul, however,  has done his best to attempt to silence critics this year, however, putting up a fantastic .305/.371/.620 line in Philadelphia. 

Still, it is well known that Citizen's Bank Park is a homer haven while Raul's old stomping grounds Safeco Field is a cavernous pitcher's park.  Because much of Safeco's damage is done to right handed hitters, it is worth a look to see if Raul's home runs this year have been impacted by his move from Philly to Safeco.  Here is Raul's home run chart (both home and away homers included) superimposed on to Citizen's Bank Park.  Some error from scaling may occur here.

Check out www.hittrackeronline.com for more awesome home run data.

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