SB Nation User Blog: bruinhoo

WaPo on Ed O'Bannon

bruinhoo — Sun, 14 Jun 2009 11:10:00 -0000

As part of a series examining the life after retirement of various athletes, today's Washington Post has a rather lengthy piece on Ed O'Bannon. While Ed's life after basketball is not a new story for many of us on BN, it is an interesting read, discussing his post-NBA life playing overseas as well as his newcareer in Las Vegas.

As an aside, I am nearly certain that PAA was on the LAX-Dulles redeye that I just got off of.

UCLA v. Villanova: By The Numbers

bruinhoo — Fri, 20 Mar 2009 08:31:00 -0000

Bumped. GO BRUINS. -N

Well, didn't last night's finish take a few months off our our lives. After squeaking out a win in a game reminiscent of the second-round battles of recent years, our Bruins now face the real second-round game, against a Villanova wildcats team playing on its second home court.

Villanova enters Saturday's game with a 27-7 record, earning an at-large berth and the East region's #3 seed after finishing 4th in the Big East. In the Big East Tournament, the Wildcats edged out a one point victory against Marquette before losing to Louisville in the Semifinal round, 69-55. The Wildcats played a fairly difficult version of the unbalanced Big East schedule, with home-and-home matchups with Syracuse, Marquette, and Providence; in conference, they played 10 games against NCAA tournament teams, 12 games against tournament competitors overall, with a 6-6 record (Entering the week, UCLA had played 14 games against NCAA tournament competitors, with a 7-7 record).

Villanova and UCLA have faced ~~two~~ three common opponents: Texas, DePaul and Notre Dame, with similar results. Villanova lost to Texas, 67-58 in New York on December 9, won at DePaul, 74-72, and defeated Notre Dame in their penultimate regular season game, 77-60 in South Bend. The Bruins lost to Texas in Austin by a 68-64 score, beat DePaul 72-54 in the Wooden Classic , and beat Notre Dame, 89-63 in Pauley. [edit to include DePaul, HT to godblesstyus]

Now to the numbers...

RPI UCLA: #33, Villanova: #13

Pomeroy UCLA: #10, Villanova: #19

Sagarin UCLA: #17, Villanova: #16

The variance among the different computer ratings in relation to the treatment of UCLA is certainly notable here. While the RPI of the Bruins compared to Villanova reinforces the seeding advantage held by the Wildcats, the other, more predictive rating systems see a much closer matchup.

One quick note about the three rating systems which I cite here. Each of the ratings uses a different methodology, and a different way of measuring success in order to come up with a ranking. The RPI uses a formula based upon the win % of each team, plus the win % of each of its opposing teams, and the win % of the opponent's opponents. This formula does not look at how each team earns its record (does not look at score margin, turnovers or anything other than Wins and Losses). Ken Pomeroy's formula, rather than focusing on only W-L, uses a complex set of game data which aims to predict future performance, rather than accounting for how good or bad a team has performed to date. The Sagarin ranking that I post here is actually a synthesis of two separate ratings which Sagarin calculates; one being an RPI-like formula taking into account only wins and losses, the other taking into score margin rather than a team's record.

Sagarin considers the latter of his formulas to be the better predictor of future performance. To illustrate the different results which arise, and to give us additonal points of reference going into tomorrow afternoon, here are the the ratings broken down by formula.

Sagarin Won-Loss: UCLA: #21, Villanova: #10

Sagarin Predictive: UCLA: #10, Villanova: #19

While the Sagarin Predictive formula, from what I can gather, is functionally quite different from Pomeroy, they both come up with the same relative ranking of these teams, and both find UCLA to be the better team, though by a slight margin.

Next is a look at the efficiency metrics and pace of play for the Bruins and Villanova.

Villanova

* Offense: 114.3 points/100 possessions (#24 in D-1)

* Defense: 91.4 points/100 possessions (#27 in D-1)

* Pace: 68.8 possessions/40 minutes (#74 in D-1)

UCLA

* Offense: 120.6 points/100 possessions (#3 in D-1)

* Defense: 92.8 points/100 possessions (#43 in D-1)

* Pace: 66.4 possessions/40 minutes (#163 in D-1)

As rye noted in his post on Villanova, the Wildcats play at a noticeably faster pace than do the Bruins, gaining about two and a half additional possessions per game. Their success has also been well balances among both sides of the court.

Using the above efficiency measures, together with the average pace of the two teams' play, the average game score of each team, based upon an equal schedule composed of average Division 1 teams would be:

Villanova: 79-63

UCLA: 80-62

By all measures, tomorrow's game looks to be a tight battle; no matter who comes out on top, I would expect the result to come down to the final possession or two, where I hope that a repeat of last night's last second defensive lockdown will allow our Bruins to spend a few extra days on the east coast and a trip up I-95 to Boston.

Pomeroy projects the Bruins to win a nail-biter, 74-73, accounting for Villanova's semi-home court advantage, with the Wildcats holding a 47% chance of winning. Sagarin's combined formula predicts a 4-point Villanova win, if the game is considered to be played on their home court, while the predictive formula alone calls for a 1-point Villanova win. Go Bruins!

UCLA v. VCU: By The Numbers

bruinhoo — Wed, 18 Mar 2009 23:37:47 -0000

Bumped. GO BRUINS. -N

For those of you that were not around at tournament time last year, I wrote up a series of posts, one before each game, looking at the numbers underlying the performance of our upcoming opponent, with a strong focus on Pomeroy and Sagarin's ratings and adjusted statistics. As this seemed to create good mojo last year (through the first two weeks, at least), I thought that I would try again.

As has been the subject of much discussion on this site since Sunday night, we will be facing VCU tomorrow night in Philly. I will leave talk of seeding and upsets for other posts.

Virginia Commonwealth University (VCU) enters the tournament with a 24-9 record, having won the Colonial Athletic Association regular season and tournament championships. VCU defeated Georgia State, ODU, and George Mason to earn the CAA's automatic bid, and the east region's 11 seed. The Rams are riding a 5 game win streak, following a Bracketbusters loss @ Nevada on February 20.

VCU has played 2 games against NCAA tourney teams: a 73-69 home win vs. Akron, and an 81-70 loss to Oklahoma in Oklahoma City. The Bruins and Rams share no common opponents.

Now to the numbers...

RPI UCLA: #33, VCU: #50

Pomeroy Rating UCLA: #9, VCU: #56

Sagarin Rating UCLA: #17, VCU: #74

One of the things that quickly comes to mind when looking at the various computer ratings is where we rate compared to our seeding, and the variance between the RPI and other computer ratings when it comes to UCLA. While I expect a hard fought game on both sides, which likely will be close throughout, it is not the tossup-to-clear upset pick that many in the press would like us to believe. VCU is a good team, but a win tomorrow would be a major upset.

Next is a look at the efficiency metrics and pace of play for the Bruins and VCU.

VCU

* Offense: 108.0 points/100 possessions (#74 in D-1)

* Defense: 93.6 points/possession (#49 in D-1)

* Pace: 67.1 possessions/40 minutes

VCU's pace of play most closely approximates Cal among this season's UCLA opponents, though VCU's defensive metrics rate better than those of Cal (along with a weaker offense)

UCLA

* Offense: 120.9 points/100 possessions (#3 in D-1)

* Defense: 92.6 points/100 possessions (#41 in D-1)

* Pace: 66.6 possessions/40 minutes

VCU: 72-63

UCLA: 81-62

This game will be a much greater opening round test than our Bruins are used to, only Josh Shipp among this year's players has played a 1st round game against anything but a lower-tier automatic qualifier. Tomorrow will not be the light warmup that we have become accustomed to the past 3 seasons.

Pomeroy is projecting a 75-66 Bruin victory, with a 20% chance of VCU pulling the upset, while Sagarin's formula predicts a 7-8 point UCLA win. A close 1st round game, which could be thrown into question by another lackadaisical start, or DC's health status.

Examining the efficiency of the Bruin lineup

bruinhoo — Sat, 28 Feb 2009 23:04:30 -0000

Or, as SJH asks, I shall deliver. The linked post raised the issue of comparison between the efficiency of our starting 5 and the bench, as well as comparing particular players on a per minute basis. In light of this, I have calculated the per minute statistics in 5 categories [points, rebounds, assists, steals and blocked shots] for each of the scholarship players on this year's roster. I will present two sets of these statistics: One set consist of the entire season to date, while the second set reflects games played since the Pac-10 opener (Pac-10 play + Notre Dame). The first set has the advantage of a larger sample size, while the latter better reflects the state of the team at this point, as well as the stronger level of competition which the team now faces.

The season-long data set:

Points/Rebounds/Assists/Steals/Blocks (per minute played)

Collison: 28 games, 31.5 mpg: 0.47    0.07    0.16    0.052    0.005
Holiday: 28 games, 26.6 mpg: 0.34    0.14    0.13    0.055    0.017
Shipp: 26 games, 28.3 mpg:    0.48    0.11    0.06    0.046    0.014
Dragovic: 27 games, 22.6 mpg: 0.39    0.16    0.06    0.036    0.015
Aboya: 28 games, 27.0 mpg:     0.37    0.22    0.02    0.030    0.008
Roll: 28 games, 17.8 mpg:         0.42    0.08    0.08    0.036    0.016
Keefe: 27 games, 15.0 mpg:     0.20    0.24    0.02    0.030    0.010
Lee: 23 games, 11.0 mpg:       0.31    0.14    0.06    0.052    0.079
Gordon: 28 games, 10.7 mpg: 0.35    0.33    0.02    0.060    0.040
Anderson: 28 games, 8.7 mpg: 0.29    0.07    0.13    0.049    0.020
Morgan: 18 games, 5.6 mpg:     0.46    0.20    0.04    0.010    0.100

The statistics dating from the start of conference play:

Points/Rebounds/Assists/Steals/Blocks (per minute played)

Collison: 16 games, 33.2 mpg: 0.45    0.07    0.14    0.041    0.004
Holiday: 16 games, 26.8 mpg:   0.29    0.13    0.14    0.042    0.012
Shipp: 16 games, 30.1 mpg:      0.48    0.09    0.06    0.031    0.015
Dragovic: 16 games, 26.3 mpg: 0.42    0.16    0.05    0.043    0.007
Aboya: 16 games, 28.2 mpg:     0.38    0.22    0.03    0.024    0.009
Roll: 16 games, 17.9 mpg:         0.39    0.06    0.07    0.042    0.021
Keefe: 15 games, 11.7 mpg:     0.18    0.23    0.01    0.021    0.007
Gordon: 16 games, 10.8 mpg: 0.33    0.26    0.02    0.052    0.029
Lee: 12 games, 8.9 mpg:           0.21    0.15    0.03    0.056    0.019
Anderson: 16 games, 7.8 mpg: 0.23    0.06    0.14    0.048    0.008
Morgan: 7 games, 3.7 mpg:       0.54    0.12    0.04    0.000    0.038

The statistics do shed light on a few areas of interest which have come up on this site form time to time. On a per-minute basis, Drew Gordon has been the team's most efficient rebounder, as well as the most efficient in creating steals and blocked shots. Josh Shipp has been the team's most efficient scorer, slightly besting DC. After a slow start to the season, Nicola Dragovic has become the team's 3rd most efficient scorer.

For all of his recent, much discussed struggles, Jrue Holiday has been the equal of DC in creating assists and steals on the defensive side of the ball. Malcolm Lee rates equal to or better than the other Bruin wings in rebounding, steals and blocked shots. James Keefe rates as the #2 rebounder on the team, but rates as the least efficient scoring threat, as well as on the lower end of the list in steals and blocks.

While the conclusions which one takes from these stats may differ, I do think that a case can be made for giving Drew Gordon and Malcolm Lee additional playing time. The trick is juggling the lineup as to minimize any harm to the team's scoring ability, while realizing the potential benefit in rebounding and in these (admittedly limited) defensive metrics.

A Look into the numbers: why do we win or lose?

bruinhoo — Thu, 26 Feb 2009 08:34:49 -0000

Bumped. GO BRUINS. - N

Ok, so I do not have a definite set of reasons for the ups and downs in this basketball season, or a roadmap showing what our warriors need to do to finish this season with a Pauley banner-raising ceremony. What I do have is a look at how the game statistics have differed between Bruin wins and losses over the course of this season. Much of what I have discovered falls into the "no duh" category, while other sets of data had surprisingly little correlation to game outcome

I Imagine that few here would be surprised to hear that the most significant variance between Bruin wins and losses has come thanks to the SPTR's, relating to the number of fouls called, and opportunities at the line for both teams.

FTm-FTa, FT% (Fouls awarded) [per game averages]

UCLA win:

UCLA: 14.1-19.6, .719 (17.0)

Opponent: 11.3-17.1, .663 (16.8)

UCLA loss:

UCLA: 8.0-11.9, .675 (15.3)

Opponent: 16.7-21.4, .780 (19.0)

In games which the Bruins have won, each team has, on average, been called for an approximately equal number of fouls, with the Bruins attempting 2.5 more free throws than their opponent. In Bruin losses, the opposing team has drawn slightly less than 4 fouls more than the Bruins, but have had an even greater knack for getting to the line, attempting 9.5 more free throws than the Bruins in those games. The idea that more fouls + fewer free throws = lose is not exactly thinking outside of the box, but having a basis for the idea can't hurt.

Another statistical category which shows a noticeable variance among wins and losses is UCLA Defensive Rebounding/opponent Offensive rebounding. While success in offensive rebounding displays no correlation to winning (the Bruins have fractionally outperformed in losses over victories on the offensive end), the average number of defensive rebounds varies greatly between Bruin wins and losses, as do offensive rebounds by the opposing team.

UCLA

Win: 31.1 rebounds/game (21.35 defensive)

Loss: 25.9 rebounds/game (15.86 defensive)

Opponent:

UCLA win: 26.6 rebounds/game (7.9 offensive)

UCLA loss: 25.0 rebounds/game (8.7 offensive)

In victory, the Bruins have brought in an average of 5.5 more defensive rebounds (a whopping 34.6% more) than in losses, while opponents have recovered nearly 1 more offensive rebound in games which they win (10% more) despite totaling fewer rebounds in sum in victories over the ben ball warriors.

Three-point shooting holds another statistical variance between wins and losses. There is a certain logic to the idea that a losing team will shoot more 3-pointers in an attempt to make up ground, particularly late in the game. In UCLA's case, the numbers bear this out. Interestingly, UCLA's opponents also attempted more 3-point shots in games which the Bruins fell.

3PTm-3PTa, 3PT% (per game average)

UCLA:

Win: 7.5-18.1, .416

Loss: 7.6-20.7, .366

Opponent:

UCLA win: 4.7-14.0, .333

UCLA loss: 6.7-16.9, .398

While the number of made 3-point shots remains roughly the same for the Bruins win or lose, they attempt 2.6 more shots to do so. This suggests that, even with the long-range proficiency of several of our players, jacking up a bunch of 3's is not necessarily the best strategy when the team is locked in a tight battle. Allowing a hot shooting opponent to take a high number of shots from behind the arc, to no surprise, is also correlated to Bruin losses.

While other other statistics show a strong correlation to wins and losses, such as shooting % and assist/turnover ratio, the number of shots attempted show very little variation among wins and losses, for both the Bruins and opponents.

FGm-FGa, FG%; Assist/TO ratio

UCLA

Win: 29.2-56.1, .520; 1.32/1

Loss: 25.7-56.6, .455; 1.03/1

Opponent:

UCLA win: 22.0-55.4, .437; 0.60/1

UCLA loss: 24.7-55.1, .493; 1.06/1

Many of the lessons which looking at the numbers associated with wins as compared to losses are basic and rather obvious (Shoot better! Protect the ball!...), there are other statistical variations which may be of interest in watching the last few weeks of this season play out. While taking care to note that correlation with a result does not necessarily imply causation, as well as the capriciousness of the SPTR's, it can be helpful to know what the effect of foul call distribution has been, as well as the importance of defensive rebounding and the knowledge that attempting to shoot out of a long-range slump in volume is not always the best way to win a game.

Tyler Lamb targeted by racist taunts

bruinhoo — Fri, 16 Jan 2009 21:13:32 -0000

Tyler Lamb targeted by racist taunts

C/O 2010 verbal commit Tyler Lamb, along with a Mater Dei teammate, were subjected to racist heckling and taunts throughout their game @ Servite HS last Friday. Behavior by the Servite students was stated to include "monkey noises" and questions regarding the parentage of Lamb and teammate Gary Franklin throughout the game.

I am not one to crack down on booing/heckling, even at the HS level, but this is just wrong. Not sure what was in these student's minds, but clearly their parents still have work to do (as well as to watch less European soccer).

(HT to Deadspin

A Pomeroy-influenced peek into the Pac-10

bruinhoo — Sat, 03 Jan 2009 01:27:10 -0000

With the start of the Pac-10 regular season now upon us, I thought that another view toward conference play might be in order. Ken Pomeroy's CBB ratings are an informative look at the current state of D-1 basketball.

A quick note to start; while his ratings are, IMO, as good a rating formula as is currently available for the college game, at this early stage in the season, it is not perfect for the purpose of comparing teams into the future. His methodology uses season team performance updated on a daily basis - while as good a way to accurately gauge performance as we have, can present problems when looking into the future, particularly when teams have varying mixes of youth and experience, whose maturity and skill may grow at different rates (for example, UNC have a highly talented and experienced team, having returned most of last years' Final Four team. While they will undoubtedly get better as the year goes by, the positive effect of additional games and practices is likely less for them as for a team composed largely of freshmen, or other first-time collegiate starters). This is likely just a long way of saying that I like the current update of this data to look at a few points of interest heading onto conference play, rather than guessing who is going to win.

As of this afternoon, the projection for Pac-10 play is as follows:

Arizona St: 14-4 (17-1); 9-0, 8-1

UCLA: 12-6 (14-4); 9-0, 6-3

Washington: 11-7 (10-8); 8-1, 2-7

Stanford: 10-8 (10-8); 8-1, 2-7

Cal: 10-8 (9-9); 7-2, 2-7

Washington St: 9-9 (9-9); 7-2, 2-7

USC: 9-9 (9-9); 7-2, 2-7

Arizona: 9-9 (9-9); 7-2, 2-7

Oregon: 4-14 (2-16); 1-8, 1-8

Oregon St: 2-16 (0-18); 0-9, 0-9

The first W-L record is the overall conference record projected for each team, factoring in some level of luck (or lack of) and other variables, and is independent of specific matchups. The second record is the product of the sum of the projected results for all Pac-10 conference games. The third record reflects the projected home record for each team, while the fourth record reflects the projected away record for each team.

An interesting subtext to the dataset is a strong home-court advantage that comes through the projections. Pomeroy gives home-court has a defined, fixed value which may not take into account that some venues give a greater real advantage, but provides statistical stability.

Today's data set projects that Arizona State will win all but one road game (@ UCLA), and that UCLA will lose three (@ ASU, Stanford, UW). No other Pac-10 team is projected to win more than two road games in conference; the Bay Area and Washington schools, as well as SC and Arizona, are projected to win two (all - @ Oregon, OSU); Oregon is projected to win only @ OSU, and OSU is projected to win none

Related to the last point is the projected weakness of the Oregon schools, particularly regarding the ease which Pomeroy sees the rest of the conference successfully navigating the Oregon road trip. The ratings do provide for some wiggle room accounting for luck and other variables throughout the season, but the only home game which an Oregon team is currently projected to win is Oregon hosting OSU. In reality, I cannot see every Pac-10 team sweeping the Oregon swing, but regardless, this is an indication of just how far behind they are from the rest of the Pac.

The pronounced home-away split present in these figures leads me to note a clear division among conference teams; Arizona State and UCLA at the top, the Oregon schools at the bottom, with the rest of the conference residing in a middle tier which currently appears both larger, and more evenly matched than in recent years.

Among the six teams in the middle of the conference, all are projected to defeat each of the remaining middle-tier teams at home, and lose to each team on the road, as well as UCLA and Arizona State, but win at Oregon and Oregon State. The uniform nature of the home-away splits tells me that, as of now, the middle of the Pac-10 is wide open for the taking. A team with room to grow and mature, such as WSU, or continue to learn a new coaches' system (Arizona) can make a strong run through the conference, and into March.

Oregon State showing off some great Pac-10 defense

bruinhoo — Thu, 01 Jan 2009 08:25:45 -0000

With all of the attention surrounding Dewayne Walker taking the NMSU job, and the Kenny debacle, the bowl season may have lapsed from the general Bruin consciousness. With the Rose Bowl to go, the Pac-10 is now 4-0 in this bowl season. In this afternoon's Sun Bowl, Oregon State defeated Big East runner-up Pitt, 3-0, in the lowest scoring bowl game in 50 years.

After allowing Oregon to score 65 points in their regular season finale, the Beavers held the Panthers to only 178 total yards, and allowed only a single failed (58 yard) FG attempt in the final two minutes of regulation.

Congrats to Oregon State on a successful end to this season. And to the University of Arizona, and to Cal, and Oregon. Here's to a 4-1 bowl record for the Pac-10 in 2008-09!

An inexperienced roster: Non-conference Ben Ball

bruinhoo — Sat, 06 Dec 2008 10:18:28 -0000

In examining the performance of the Bruin basketball team over these early weeks of the season, one of the keys in evaluating this team and its future outlook is the youth and inexperience of many of the players. This year's roster does not start from a position of maximum depth; 11 out of 13 possible scholarships have been used. After factoring in the heralded 5-man freshman class, we are faced with only 6 returning scholarship players (number crunching done for my fellow north campus majors ;).

SJH, in his post-Texas thoughts, raised the point that the team, as it now stands, has only two players with significant experience. This got me thinking about truly how much playing time and experience that this team has. Entering the season, the returning players and their experience follows:

Collison: 107 games, 76 starts, 28.5 minutes/game

Shipp: 107 games, 102 starts, 30.5 minutes/game

Aboya: 107 games, 17 starts, 15.7 minutes/game

Roll: 80 games, 0 start, 15.4 minutes/game

Keefe: 57 games, 1 start, 8.9 minutes/game

Dragovic: 31 games, 0 start, 8.3 minutes/game

DC and Josh Shipp are the undisputed anchors of this team, with over 3,000 career minutes logged over 107 games each. As a senior who has started a handful of games over his UCLA career, it may not be entirely accurate to characterize Alfred Aboya as inexperienced, but he is being asked to fill a new role this season as the team's primary post presence - with a corresponding increase in minutes and a need for greater discipline without Kevin Love or LRM to help shoulder the load.

James Keefe's main collegiate experience comes from a handful of games at the tail end of last season. While the minutes that he played in the last postseason were productive, the fact remains that he had started only 1 game entering this season, and averaged fewer than 9 minutes per game played at UCLA.

To date, Michael Roll has played a role similar to that during his freshman and sophomore seasons, though as a result of the foot injury which caused him to miss most of last season (and receive a medical redshirt), Roll has played only a handful of games in the last 20 months. After being kept out of the opener, Nikola Dragovic has seen his playing time increase dramatically in these early contests, in contrast to the limited playing time granted him during his first two years in Westwood.

Now to look at this in context of the starting 5 and the rotation:

Darren Collison: 107 games (76 starts), 28.5 minutes/game

Jrue Holiday: 0 games

Josh Shipp: 107 games (102), 30.5 minutes/game

James Keefe: 57 games (1), 8.9 minutes/game

Alfred Aboya: 107 games (17), 15.7 minutes/game.

Collison and Shipp's roles are consistent with prior seasons, in terms of starts and minutes played. Aboya has averaged 10+ minutes more than his career average, while Keefe has more than doubled his minutes in his first starting role. Jrue, of course, is the newcomer to the collegiate game.

Michael Roll: 80 games (0), 15.4 minutes/game

Nikola Dragovic: 31 games (0), 8.3 minutes/game

Malcolm Lee: 0 games

Drew Gordon: 0 games

Jerime Anderson: 0 games

J'mison Morgan: 0 games

The bench rotation holds at the top a solid role player, albeit one coming off of a redshirt year, in Roll; and in Dragovic, a junior having seen only limited playing time coming into this season. The remaining depth consists of a group of true freshmen who, although very talented, will need time to truly grasp the intacracies of coach Howland's style of play and to earn his trust in important game situations.

As can be seen, this team is centered on a pair of experienced seniors, and a elite freshman in Jrue Holiday. Aboya is being asked to expand upon his role of prior seasons, while James Keefe has been thown into the starting lineup with only a few games of meaningful experience. To support this lineup, we have a junior coming off of a redshirt year, another junior who had played only sparingly in his UCLA career, and four freshmen.

What the future holds for this Bruin squad cannot yet be told. But to imagine that the current state of the team's performance will bear much resemblance to the team come February/March is to underestimate the effect of a roster in which most of the players are being introduced to the college game, or greatly expanding their once-established roles. This is not to say that inherent flaws (if any) in the roster will not become a problem, but as the season progresses, these players will progress at an individual level, and come together as they practice and play together over the next several weeks. It will be fun watching this team develop, whatever the outcome of the season and the struggles within.

An early BCS primer

bruinhoo — Wed, 26 Nov 2008 06:00:46 -0000

Bumped. GO BRUINS. -N

This past Sunday's CFB post led to an very interesting series of comments, some of which involved the current state of the BCS picture. While this does not have any direct effect on the Bruins, it was suggested that my comments on the subject may be of interest.

With the advent of the National Championship Game in addition to the existing bowl structure, 10 teams participate in the BCS. The champion of each BCS member conference (ACC, Big 10, Big XII, Big East, Pac-10, and SEC) gain automatic berths, leaving 4 "at-large" spots. The at-large teams are chosen by each BCS bowl that has an open berth, by an annually rotating order.

While at-large berths are, by definition not predetermined, there are certain BCS rules which apportion at-large spots.

The #1 and #2 ranked teams in the final BCS standings play in the national championship game, without regard to conference champion status. If either of those teams did not win its conference (such as Nebraska, 2001) or is the champion of a non-BCS conference, that team takes one of the at-large spots.

The #3 ranked team in the final BCS ranking, if not the champion of a BCS conference, is guaranteed an at-large berth (unless another at-large team from the same conference has qualified for the national championship game). If the #3 team does not require an at-large berth, the #4 ranked team may qualify in the same manner.

Another at-large rule comes from the compromise made a few years ago, with the intent of allowing greater access to highly ranked teams from non-BCS conferences. An exception allowing up to one team per year from a non-BCS conference to gain an automatic bid was created, as follows:

3. The champion of Conference USA, the Mid-American Conference, the Mountain West Conference, the Sun Belt Conference or the Western Athletic Conference will earn an automatic berth in a BCS bowl game if either:

A. Such team is ranked in the top 12 of the final BCS Standings, or,
B. Such team is ranked in the top 16 of the final BCS Standings and its ranking in the final BCS Standings is higher than that of a champion of a conference that has an annual automatic berth in one of the BCS bowls.

No more than one such team from Conference USA, the Mid-American Conference, the Mountain West Conference, the Sun Belt Conference, and the Western Athletic Conference shall earn an automatic berth in any year. (Note: a second team may be eligible for at-large eligibility as noted below.) If two or more teams from those conferences satisfy the provisions for an automatic berth, then the team with the highest finish in the final BCS Standings will receive the automatic berth, and the remaining team or teams will be considered for at-large selection if it meets the criteria.

This provision is typically not an issue, as even a single non-BCS team finishing in the top 12/16 has been more of an exception than a rule (2004 Utah, 2006 Boise St). This season is an anomaly in that 3 non-BCS conference champions may finish in the top-16, and would be eligible for automatic bids without the above limitation.

- Utah has locked up a spot in the BCS (12-0, MWC champion, #6 in this week’s BCS)
- Boise State (11-0, #9), having clinched the WAC championship would qualify under 3(a) or (b) with a win next week, but for the one team rule. As it stands, they would need to leapfrog Utah (as well as Penn St, and Texas Tech in the process) to gain a BCS spot.
- Ball State (12-0, #15) has completed its regular season, and will next play in the MAC championship game. A win would result in a 13-0 season, and would likely preserve the team's current position in the BCS top-16, and allowing it to qualify under 3(b) if not for the one team rule (as the ACC champion, at least, will not finish in the top-16).

With the automatic (conference champion) BCS berths are automatic, I'll take a look at how the at-large bids may shake out. To start with, Utah will gain an automatic bid under the non-BCS conference champion exception. As a result, the at-large pool shrinks to 3 berths.

As I see the BCS picture, whichever of Oklahoma/Texas that does not make the Big XII title game gets an at-large bid, as does the loser of the SEC title game (unless Florida loses twice). Together with Utah’s automatic bid, only one at-large spot remains.

The BCS selection rules state that at-large teams are taken from teams finishing in the top-14 of the final BCS ranking, provided that:

1. The team has won at least 9 regular season games, and

2. No more than two teams from a conference may participate in the BCS, unless the #1 and #2 teams are non-champions of a BCS conference.

This rule, seemingly unknown to many, including (as demonstrated last Saturday) some CFB analysts, will eliminate from at-large consideration otherwise eligible teams from the Big XII and SEC. Assuming that the SEC will place Alabama and Florida in the BCS, and two of Oklahoma/Texas/Texas Tech will represent the Big XII, and using this week's BCS ranking and conference standings, 5 teams are eligible for consideration for the final at-large berth: USC (#5), Boise State (#9), Ohio State (#10), TCU (#14), and Ball State at #15 (If USC passes Oregon State to win the Pac-10, this at-large pool shrinks to 4 teams for 1 berth.).

As noted earlier, the team gaining this final at-large berth is picked by the applicable BCS bowl committee, and is limited only by the above rules. There is a chance that if USC wins out, it will gain an automatic BCS berth by finishing either #3 or #4 in the final BCS ranking (if one of Florida/Oklahoma/Texas loses, this is probable). If this occurs, then all at-large berths will be taken. Even if that eventuality does not occur, I find it hard to believe that an 11-1 USC squad would be left out of the BCS.

If USC goes 1-1 to end the regular season, we are left with 10-2 Ohio State and 10-2 USC as the most likely choices for the final BCS bowl bid, with (a possibly 12-0) Boise State holding an outside shot; very slim, but buoyed by its 2006/07 BCS history. Any of these teams could reasonably be chosen by a game shopping for an at-large berth, based upon the unique circumstances of competitiveness and fan travel facing each bowl game. All else equal, I believe that at 10-2, USC would be taken ahead of 10-2 Ohio State. Regardless of how the teams are currently perceived, I believe that the 35-3 beating of tOSU in September makes it impossible for Ohio State to be picked without the narrative of that game being dominated by the issue (in the Sunday comments, bucknellbruin made the case for Ohio State).

As a non-champion of a non-BCS conference, I do not see TCU having any shot at an at-large bid. Likewise, I do not see Ball State with a realistic chance, particularly with fellow non-BCS conference champion Boise State ranked ahead of it in the at-large pool.