Battle of the Sexes: Free Throw Edition

As a UNC basketball fan, this season has definitely been a roller coaster ride.  UNC is 3-0 against top 25 teams, beating #1 Michigan State on the road, #3 Louisville on a neutral court, and #11 Kentucky at home.  UNC has also had some bad loses: UAB, Belmont, and Texas.  Two of the losses were by 3 points, and UNC missed over 20 free throws in both of those games.  Last weekend, I attended the Toledo-Dayton women's basketball game, and there were hardly any missed free throws.  So this got me thinking: are women any better than men at free throw shooting?

When looking at all Division I free throw percentages for both men and women (as of December 27), men are slightly better at making free throws, as shown below. The median free throw percentages (thick black lines) are 69.1% for men and 68.4% for women.  The variability is also much smaller for the men than women.  Note that the UNC men make 61.3% of their free throws, ranking them 333 out of all 345 teams.

Next, I wanted to look the the free throw percentages of the top 25 ranked teams, which is shown below.  For easier comparison, I have also included the distribution for all Division I teams.

For both men and women, teams ranked in the top 25 are on average better at making free throws than compared to all teams.  When restricted to top 25 teams, women have a better free throw percentage than men.

So who is better at making free throws: men or women?  Men are slightly better on average than women, but when restricted to the best 25 teams, women are on average better.  Regardless, I'm hoping that UNC can increase their free throw percentage in the second half of this season.

College Basketball Commitments

I came across a very nice article describing the college commitment habits of 700 top basketball recruits.  The author does a great job of delving through the data and concisely summarizing the main findings.  A few of my favorite highlights:

1. First, just obtaining all of this data (all high schools and colleges attended for all 700 athletes) must have been a Herculean task.  
2. I like that he also displays the data with several bar charts and a very colorful cumulative density plot showing how early in their high school career that recruits commit to a college.
3. Of the players who spent at least 2 seasons playing in college, over a third didn't end up where they started.
4. Think that these top recruits only bounce around universities to get the most exposure?  4 of the recruits attended 6 different high schools, including current NBA player Michael Beasley.  Plus, over 50% of the 2013 recruiting class attended at least 2 high schools.

Statistics Playing Major Role in College Football Playoffs

The potential impact of stats on the playoff selection committee

In the above article, Sports Illustrated sought the recommendations of 5 college football and basketball "stats gurus" to get a better feel for how the college football playoff committee should go about choosing the four teams to compete in the 2014 national championship playoffs.  They discussed three primary themes:


1. The need for accountability and transparency. Although the BCS releases their rankings and scoring/point totals every week, the actual formula used in these calculations is proprietary.  I am in agreement with the 5 experts in calling for full transparency in the system.  However, this makes it difficult to include an "eye test" in the decision (whether this should be included is another debate).  My favorite quote:

"I doubt this will happen, but I think they need to have a non-voting data person in the room as well. Someone to help the members interpret ratings and other data sources, answer questions that are posed and hold the group accountable to information that is shared."

2.  Its about more than wins and losses.  Should other factors like injuries and margin of victory/defeat play into account?

"Of course, the danger of using advanced stats or ignoring head-to-head results is the committee might wind up producing a bracket that the majority of the public -- accustomed to seeing rankings ordered largely by team records -- rejects."

3.  Strength of schedule isn't what it seems.

"There are many ways to measure schedule strength, and many of them are valid. I like to use this example. Imagine two schedules. Schedule A consists of the six best teams in the country and the six worst. Schedule B consists of the 12 most average teams in the country. Which is tougher? Ask Alabama, and they'll obviously say Schedule A. Alabama would have a much easier time running the table against Schedule B. But ask the worst team in the country which one is easier, and they'll say the opposite. The worst team in the country would have a hell of a time winning a single game against Schedule B. ... So depending on who you are, you can perceive the exact same schedule of teams very differently."

College Football 2012 Wrap-up

This BCS bowl season, two teams, Wisconsin and Northern Illinois, were coached by interim coaches in their BCS bowl game after their head coach left the team to accept a new position.  There seems to be an increasing trend of coaches leaving their teams before a bowl game to accept a new coaching position.  I began wondering whether schools that are searching for a new head coach should try to scoop other coaches before the bowl games are completed, or if they should factor in the bowl game performance (maybe make the candidates feel some extra pressure to win)?  Schools tend to want to fill their coaching vacancies ASAP because this provides the new coach an extra month to put together his coaching staff and recruit.  But does this process of hiring coaches before the bowl game actually lead to better football success?

I chose to look at head coaches who lead their team to one of the BCS bowl games, then accepted a new college coaching position the following year.  While this leaves a small sample size (n=9), it is easier to evaluate the performance of these coaches because it is assumed that the new school is expecting the new coach to lead his new team to BCS bowls.  Here is a summary of the 9 coaches:

Coach	Previous Team	Old BCS Record*	Year	Last Bowl	New Team	Record	New BSC Record
Steve Spurrier	Florida	2-1	2001	W	South Carolina	66-37	0-0
Urban Meyer	Utah	1-0	2004	W	Florida	65-15**	3-0
Walt Harris	Pitt	0-1	2004	L	Stanford	6-17**	0-0
Rich Rodriguez	West Virginia	1-0	2007	W*	Michigan	15-22**	0-0
June Jones	Hawaii	0-1	2007	L	SMU	31-34	0-0
Brian Kelly	Cincinnati	0-1	2009	L*	Notre Dame	28-11	0-1
Randy Edsall	UConn	0-1	2010	L	Maryland	6-18	0-0
Bret Bielema	Wisconsin	0-2	2012	L*	Arkansas	-	-
Dave Doeren	Northern Ill.	0-0	2012	L*	NC State	-	-

* = Coach left team before BCS bowl game, so it was coached by interim coach. If the head coach left the school before the BCS bowl game, it is not reflected in his BCS record.

** = No longer with this team. Meyer retired and Harris and Rodriquez were fired. 

A few interesting gems from looking at this table:

• Only 3 of these 9 coaches won a BCS bowl game with their previous team (Spurrier, Meyer, Rodriguez).  
• Only 2 have taken their new teams to a BCS bowl game (Meyer, Kelly), with Meyer being the only coach to win a game (actually 3, including 2 national championships).
• The only coach to win a BCS bowl game with their new team (Meyer) had won a BCS bowl game with his previous team.
• 3 of the 4 teams coached by intermin coaches lost their bowl game, with West Virginia being the only exception.

Yes, programs that are hiring coaches have probably suffered some losing seasons and need time to rebuild, so these results could change in another year or 2.  Plus, this is a small sample size, so we would probably be better off by including all coaches who leave their teams, not just ones leaving after reaching a BCS bowl game.  In my opinion, schools that are hiring college football coaches are placing too much emphasis on reaching BCS bowl games and not enough on winning these games. Even if it is all about the money of BCS bowl games and not actually about winning, most of these big-name hires are struggling to take their new teams to a BCS bowl game.

If I were in charge of hiring a new football coach to turn around a struggling program and win national championships, here would be my one major piece of advice:

If you are serious about winning national championships, hire a coach that has actually won a BCS bowl game. If none of these coaches are available/interested, then don't settle for a coach who has taken his team to a BCS bowl game but lost - what makes you think he can do better next time (ahem, Brian Kelly)?  Save your money and take a chance by hiring a coach who hasn't been to a BCS bowl (but has preferably won other bowl games). You might just hire the next Les Miles (2-1 in BCS bowl games since 2005, including a national title).

Scheduleball

Scheduleball: Colorado State, Pitt exploit weaknesses of RPI

By now, everyone is aware of the impact of Moneyball (statistics!) on the MLB.  Due to the media firestorm surrounding Moneyball (aided by the catchy name), the perception seems to be that baseball GMs are the brainiest employees in professional sports.  Occasionally, I'll hear a story about an NFL or NBA GM who breaks the mold by applying analytics to improve their team's performance, but this isn't very common (although I imagine all pro teams are now employing at least a few data analysts).  

But I've NEVER heard a story about a college athletic director credited for improving/influencing his school's performance beyond the hiring of a high-profile coach ... until I read the above story.  I imagine that the main reason for this is because it is extremely rare.  You only hear about from the AD when its time to hire/fire a coach, respond to NCAA investigations, or build a new state-of-the-art athletic facility. This really doesn't make much sense, especially considering that all of the top universities have many great PhD-level statisticians on their payrolls.  While not all statisticians do sports-related research, all a university needs to do is simply buy out one of a professor's courses to get his/her expertise on how to apply a Moneyball-style approach to give their athletic teams as many advantages as possible ("buying out a course" = allow a professor to dedicate the time he/she would normally spend teaching a course to do some other research activity).  

I realize that this may ruffle some feathers, as many head coaches don't want to take advice from some academic wizard.  One option is to hire an AD who can do these sorts of analyses himself, and only try to change "off the field" decisions, such as scheduling, which is what the linked story above explains.  And as probably all coaches have bonuses built into their contracts for post-season appearances, what coach wouldn't want to do all he can to increase his likelihood that his team makes it into the playoffs (or bowl game)?  

If any university wants to take a chance and hire a statistician as their next AD to get an advantage over their competition, I'll be more than happy to interview :)

How accurate are football preseason polls?

I'm a few weeks late on this post, but I think its still worth blogging about.  Every year, the media (especially ESPN) makes such a huge deal about college preseason football polls.  Without any games yet to be played, these polls are little more than speculation.  I wanted to look into how accurate these polls are at choosing that season's national champion.  In this post, I will be using exclusively the AP poll preseason and final results, which can make a difference in years before the BCS when there could be multiple national champs based on the poll used.

This first plot shows the final ranking of preseason top 5 teams since 1990.  The bar furthest to the right shows the teams that were in the top 5 preseason poll but finished the year unranked.

 A few interesting notes:
1. 14 of the past 22 national champions were ranked in the preseason top 5 (I think the last winner outside the top 5 was Auburn led by then-unknown Cam Newton).
2. More national champs were ranked preseason #2 than preseason #1.  This is good news for Alabama who started this season ranked #2 behind USC (but who jumped to #1 after their first win).
3. Looking only at the preseason #1 teams (blue bars), they are more likely to finish the season ranked 3rd than any other rank.  Also, no preseason #1 has finished worse than #16 in the final polls.

Next, I wanted to look whether teams ranked higher in the preseason poll tended to be ranked higher at the end of the season.  A simple way to do this is to look at the median finish of the top 5 preseason teams.

Median Final Ranking since 1990

Preseason Rank	Median Final Rank
1	3
2	5
3	6.5
4	9.5
5	8

So although the national champions are not always ranked preseason #1, the top preseason teams in general finish higher in the standings than the other preseason teams.  The exception is that teams ranked #5 tend to finish the season ranked better than the #4 preseason team.  There could be some bias causing this result, as there needs to be some tie between teams with the same final season record, and this may be influenced by the preseason rankings.

Finally, I wanted to see how the final rankings of the previous season influence the preseason polls of the next season.  For example, do teams who finish the year #1 tend to be the top ranked preseason team the following year (even though 1/4 of the team likely graduated)?

This plot shows that the preseason top 5 teams tended to finish the previous season ranked highly.  We see that, since 1990, 9 of the 23 teams finishing the previous season #1 were the top ranked preseason team.  This is a somewhat questionable strategy, as only 2 teams have repeated as national champs since 1990: Nebraska in 1994-95 (who was not ranked preseason #1 in 1995) and USC in 2003-04.

In summary, while the top preseason team more often than not does not win the national championship, on average they finish the season ranked better than any other preseason team.