Econometric Model for Recruiting (73% accuracy)

[jwinslow]

Mercer.edu

Click above for list of predicted and actual outcomes. A pretty interesting model.

Currently, the model is predicting at a 73% accuracy rate for the committed players.

Welcome to the ?college football recruiting prediction model? website hosted by the Stetson School of Business and Economics at Mercer University. This website contains information about an econometric model that has been developed by three economists (Mike DuMond, Allen Lynch and Jennifer Platania) to predict the collegiate choices of high school football players.
Each year, on the first Wednesday in February, college coaches, administrators, and football fans eagerly await the choices of high school seniors as they sign ?letters of intent? with specific colleges. These letters of intent officially link top ranked high school football players with specific colleges and effectively determine the rosters of college football programs in years to come. The process of recruiting these players is highly competitive, as schools battle with one another to sign the best of the best in the world of high school football. Recruiting gurus attempt to forecast the choices of these high school athletes as college football fans desperately search the Internet for bits and pieces of information that might shed light on the choices of these teenage football players.

We were a bit surprised by the results. There were a number of factors that we thought would significantly impact the decision of the high school athlete that didn?t. For example, factors like the school?s graduation rate, the number of Bowl Championship Series (BCS) bowl appearances, the current roster depth at the recruited player?s position, the number of players from a specific college drafted by the NFL, and even the number of national championships won by a particular program don?t systematically influence the decisions of high school athletes. Surprised? So were we. What, then, does matter? As it turns out the following factors DO significantly impact the decision of high school athletes:

• Whether the athlete made an ?official visit? to a specific college
• Whether the school is in a BCS conference
• The distance from the high school athlete?s hometown to a specific school
• Whether the recruit is in the same state as a specific school
• The final AP Ranking of a specific school in the previous year of competition
• The number of conference titles a school has recorded in recent years
• Whether the school is currently under a ?bowl ban? for violating NCAA rules
• The current number of scholarship reductions a school faces for violating NCAA rules
• The size of the team?s stadium (measured in terms of seating capacity)
• Whether the school has an on-campus stadium
• The current age of the team?s stadium

So, in a nutshell, high school athletes prefer winning programs that are
close to home, are in possession of good physical facilities, and are in good
graces with the NCAA. Interestingly enough however, reduced scholarships increase the likelihood of choosing a particular school, holding all else constant. This is likely because reduced scholarships imply reduced competition for exposure and playing time in the future.

[Trevi]

This is likely because reduced scholarships imply reduced competition for exposure and playing time in the future.

Perhaps. Could also be a factor that fewer offers are given out in years with fewer openings?

[sandgk]

Predicting Terrelle Pryor to Penn State with a 35.9% probability.

Just hang in there Joe!

[rolemodel247]

guessing the easy ones is easy, in this class 12 of 14 of the kids we landed were absolute no brainers, everyone that usc has landed so far have been no brainers, i'd say that more than 73% of most recruiting classes are no brainers, maybe michigan and nd are exceptions

[smithlabs]

Originally Posted by sandgk

Predicting Terrelle Pryor to Penn State with a 35.9% probability.

Just hang in there Joe!

Assumption of an official visit made. GIGO

My gut feel is that the model would have predicted OSU without the official visit.

[calibuck]

Thanks Jwin. want to check this thing out. Stochastic modeling is big in the macroeconomic business, where these 'quants' work. Sensitizing the numerous variables to determine which ones are key to the end result is quite a bunch of work, but what award-winning papers are based on. Or economic pricing of a differentiated product. Which universities are, specifically football playing universities, same as bathroom soap.

I marvel at the work these people have put in to developing this model, and I'll probably delve into it to see how many variables are input. At first blush, the only item that seems NOT to be quantified is the ability of the football coach to connect with the player (and his parents) to establish that rapport and/or feeling of family. All great recruiters have this innate ability (Woody, Bo, Ara, Mack Brown, Petey Carroll, Jim Tressel, and others) to have the parents feel comfortable that their child will be cared for. I do see the correlation between distance and the ability to sign. Great post.

I'll wager that most all coaches have this type of analyses available to them on a more 'informal' check list, rather than a multi-formula stochastic simulation model on a computer.

[osugrad21]

CDiddy > Mercer