“And Why Should the People Listen to You?”

Comments: 1 Comment
Published on: November 26, 2012

Because, unlike other models, my model predicts per attempt NFL statistics using NCAA data.

[Author’s Note:  The non-technical reader is invited to skip this section as it will be filled with statistical jargon and  “academese”.  The technical reader is invited to submit any skepticism in the comments section]

The ultimate test of a quarterback model is its ability to take NCAA data and predict NFL statistics on a per attempt basis.  Predicting per attempt NFL statistics rather than total NFL stats is key here.  Predicting total NFL stats for quarterbacks isn’t difficult.  All one needs to know is draft order.  Players that get drafted higher tend to have higher total stats.  The thing is, the only reason that relationship exists is that players that get drafted higher get more playing time.  More playing time means more opportunities to run up attempts, completions, yardage, and touchdowns.  But if you look at per attempt statistics like Passer Rating, yards per attempt, etc., draft order shows no ability to predict NFL performance.  Quarterbacks drafted in the 6th round are just as likely to be successes as quarterbacks drafted in the 1st or 2nd round.

Our primary metric is Completions Away from Average (CAA; see The Concept for additional information).  The data necessary for calculating CAA has only been collected since 2005.  In addition, two years of historical data are required before estimates become stable.  Therefore, the data set includes NCAA CAA beginning in 2007 and NFL Passer Ratings beginning in 2008.

Total CAA for the quarterbacks’ NCAA careers were used as predictors in a regression equation [Author’s Note:  This will change the projections mentioned a few weeks ago, which were based on data from the 2012 season only.  It will also change our assessment of the 2011 NFL draft class.].  The criterion variable was NFL passer rating for the quarterback during his first three years on the league.  All quarterbacks that played for an FBS team and were drafted between 2008 and 2012 and started at least one NFL game were included in the data set.  Undrafted quarterbacks or quarterbacks that did not start an NFL game were not entered.  This gives us a set of 40 quarterbacks with complete data.  Data from the 2012 season was included up through Week 11.  One multivariate outlier was identified (see graph below), Colin Kaepernick and his crazy awesome game last week.  This data point was deleted for the analysis reported here.  We will revisit this deletion at the end of the season.

The regression table is shown below.  The highlights from the table are as follows.  Career CAA is a significant predictor of NFL passer rating during the first three years in the league, accounting for 12.3% of the variance.  In addition, for every addition CAA a quarterback accumulates during his NCAA career, a quarterback’s three year passer rating is expected to increase by 0.18

Variable

R2

F

B

t

Equation

.123

5.03

.03

Constant

66.70

21.87

Career CAA

0.18

2.24

.03

12.3% may not seem like much, but there are two reasons to be optimistic about that number.  First, no published analysis exists that shows NCAA statistics being able to predict per attempt statistics in the NFL.  Second, NFL passer rating is another of those statistics that is infected with the results of others.  The quarterback’s offensive system and talent of the receivers also factor into passer rating.  So, finding NCAA Career CAA predicting NFL passer rating three years out is likely getting at something meaningful for an individual quarterback.

So, why should the people listen to me?  Because the information presented here is useful and predictive of future performance at the next level.

1 Comment - Leave a comment
  1. […] project for the summer will be to connect these numbers to something more meaningful and concrete, like I have with quarterbacks.  Until then, we can just look at the nice pretty […]

Leave a Reply


Welcome , today is Sunday, November 19, 2017