Intelligence and Football: Testing for Differentials in Collegiate Quarterback Passing Performance and NFL Compens
by U.S. Sports Academy - The Sport Journal - http://thesportjournal.org
Intelligence and Football: Testing for Differentials in Collegiate
Quarterback Passing Performance and NFL Compensation
by U.S. Sports Academy - Saturday, March 05, 2005
http://thesportjournal.org/article/intelligence-and-football-testing-for-differentials-in-collegiatequarterback-passing-performance-and-nfl-compensation/
Submitted by: McDonald P. Mirabile
Abstract
This article presents an empirical analysis of the relationships between intelligence and both passing
performance in college and compensation in the National Football League (NFL). A group of 84 drafted
and signed quarterbacks from 1989 to 2004 was selected for the study. The author hypothesizes that
intelligence is the most important and perhaps most rewarded at this position, and a wide variety of
passing performance statistics are available to separate the effects of intelligence and ability. The OLSestimated models reveal no statistically significant relationship between intelligence and collegiate
passing performance. Likewise, the author finds no evidence of higher compensation in the NFL for
players with higher intelligence as measured by the Wonderlic Personnel Test administered at the NFL
Scouting Combine.
Introduction
Every February hundreds of collegiate football players gather in Indianapolis at the NFL’s scouting
Combine, a four-day event designed for NFL scouts to evaluate the talent of the year’s draft eligible
players. Many players likely to be drafted in the first round of the NFL draft will refrain from taking the
skills and agility tests in Indianapolis, and will schedule “pro days” at their university where they are
more comfortable with the atmosphere and expected results of their workouts. All prospects at the
Combine undergo X-rays and physicals to address current and past injuries. All players will also take a
12-minute test designed to measure intelligence, the Wonderlic Personnel Test.
First used by a handful of teams in the 1970s, the Wonderlic is a 50-question test designed to be taken in
12 minutes to measure the athlete’s general intelligence (ESPN, 2002; FairTest Examiner, 1995). The
score is calculated as the number of questions correctly answered in the allotted time. As a matter of
practice, most players do not answer all 50 questions in the time allotted. Wonderlic scores vary by
position, though NFL draftees have averaged a score of 19 over the last 20 years. A Wonderlic score of
20 indicates the test taker has an IQ of 100, which is the average intelligence (Wonderlic.com). The
Wonderlic website states that higher scores mean higher intelligence, and intelligence has an impact on
playing style and leadership, especially for quarterbacks. The accuracy of this contention will be
empirically tested in this article.
This article will also examine the intelligence in two additional models to determine relationship between
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Intelligence and Football: Testing for Differentials in Collegiate Quarterback Passing Performance and NFL Compens
by U.S. Sports Academy - The Sport Journal - http://thesportjournal.org
intelligence and a player’s rookie year compensation and the relationship between intelligence and where
an athlete is selected in the NFL draft. This article is particularly relevant in the modern draft era because
the millions of dollars spent scouting and signing draftees represent a significant investment by NFL
franchises. To the extent that intelligence has an effect on passing ability, NFL franchises may be willing
to reward players with such mental abilities. However, if no relationship exists between tested
intelligence and performance, then NFL franchises can better utilize resources by focusing on other
aspects of player evaluation.
Methodology and Data Sources
The player data for this study were collected from ESPN.com, various NFL draft prospect websites and
official university athletics sites. The data include information on 84 drafted NFL quarterbacks who
received rookie year salaries between 1989 and 2004. 1 However, due to the limited public availability of
Wonderlic scores prior to 1999, most of the quarterbacks used in this study were drafted in the last six
years. Although the test results are not officially released, in recent years the Wonderlic scores have been
available on the Internet at NFL.com for many players at the Combine. Salary data were obtained from
ESPN.com and USAToday.com between 2001 and 2004 and from USA Today newspaper clippings prior
to 2001.
Comparing the distribution of the data used in this study to the total current population of NFL
quarterbacks, the author finds a similar proportion of non-white quarterbacks (about 20 percent in each),
but a slightly higher proportion of Division 1A quarterbacks in the data (89 percent compared to 80
percent). Such comparisons are important as intelligence tests are frequently found to generate sizable
ethnic differences, and such biases could affect the results and interpretation of the model if the sample
data is not a representative subset of the true population of NFL quarterbacks (FairTest Examiner, 1995).
Modeling Intelligence and Collegiate Passing Performance
The first relationship this paper addresses is the relationship between intelligence and quarterback passing
performance. Using the same set of independent variables in each model, an equation is estimated for
each of the dependent variables to measure a quarterback’s passing performance, career passing
efficiency (Model I) and total offense per game (Model II). The quarterback’s best collegiate year in
terms of total offense per game is used in this analysis.
NFL scouts and coaches assign draft grades to players based on collegiate production and ability. In
particular, scouts highly value attributes such as height, quickness, arm strength, vision, leadership and
intelligence (CNN/SI, 1998). As such, we develop a model based on the expected contributions of these
characteristics (where quantifiable) to a quarterback’s passing performance.
We expect that height may have a positive relationship with passing performance. Taller players can
better read defenses, find receivers and avoid having passes deflected by defensive lineman. We expect
that a player’s quickness (lower 40-yard dash times) will have a positive relationship with total offense
but no effect on passing efficiency. Likewise, NFL scouts expect the quality of a quarterback’s offensive
peers to have a positive effect on his passing performance. The models include a DRAFTCLASS variable
to control for the general quality of the quarterback’s senior class. DRAFTCLASS is a count variable of
players drafted into the NFL during the quarterback’s senior year.
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Intelligence and Football: Testing for Differentials in Collegiate Quarterback Passing Performance and NFL Compens
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There are no a priori expectations for the relationship between intelligence (as measured by
WONDERLIC) and passing performance. Likewise, there are no a priori expectations for the relationship
between passing performance and Division 1A football. There are no a priori expectations for the
relationship between a quarterback’s race and his passing performance.
The models developed in this section are estimated by OLS without a constant. All dependent and
independent variables have been transformed and are centered on the mean of the observed variable to aid
in the interpretation of the marginal effects of each explanatory variable. In particular, all effects are for a
quarterback with characteristics at the mean, the values of which are shown in Table 1.
Table 1: Summary Statistics of Dependent and Independent Variables
Variable
HEIGHT (inches)
FORTY (seconds)
DRAFTCAST (# of
drafted offensive
teammates)
DRAFTCLASS (#
of drafted players
from team)
WONDERLIC
Division 1A, 1=yes
Race, 1=non-white
NCAA (career
NCAA passing
efficiency)
TOPGB (total
offense per game,
best year)
DRAFT
REALSAL
NFL ROOKIE
RATNG
Mean
74.80
4.84
3.08
Std. Dev.
1.45
0.18
2.20
Min
71.38
4.36
0.00
Max
77.63
5.37
7.00
3.69
2.50
1.00
14.00
25.45
0.89
0.20
135.91
7.13
0.31
0.40
12.09
10.00
0.00
0.00
104.35
42.00
1.00
1.00
168.82
273.57
64.94
109.36
527.20
108.76
769,863
69.06
82.77
808,343
27.86
1.00
30,515
8.80
250.00
2,735,854
140.20
As shown in Table 2, the hypothesized model for estimating passing performance does a considerably
better job explaining TOPGB than NCAA. In fact, the F Value for the Model I is not statistically
significant, suggesting that within the sample of players in this dataset, the model has no explanatory
power. This may be the case with a relatively homogenous group of individuals – because all players are
similar in ability levels, insignificant variation may exist to accurately estimate the model. This is not the
case in Model II where significant variation exists within the TOPGB variable, reflecting not only the
quality of the team and the opponents, but also the style of offensive attack.
The expected relationship between a player’s HEIGHT and his passing ability is not found in the passing
efficiency model (Model I), suggesting that the collegiate passing performances of this group of NFLcaliber quarterbacks do not vary with height. However, RACE is statistically significant in both models,
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Intelligence and Football: Testing for Differentials in Collegiate Quarterback Passing Performance and NFL Compens
by U.S. Sports Academy - The Sport Journal - http://thesportjournal.org
suggesting that non-white quarterbacks are better than their white peers in terms of passing efficiency and
total offense per game. In particular, non-white quarterbacks average 8.9 points higher in passing
efficiency and 44.8 more total offensive yards per game than their white peers. DRAFTCAST, the quality
of the quarterback’s offensive peers, as measured by the number of offensive teammates drafted during
his collegiate career, is statistically significant in the total offense per game model. This effect may reflect
the self-selection of better quarterbacks into the top collegiate programs known to produce many NFLcaliber prospects. DRAFTCAST is a count variable with a maximum value of seven. The expected
negative relationship is found because in the absence of other offense threats, the team will naturally rely
more on the abilities of the quarterback. The estimated coefficient has the interpretation that for each NFLcaliber offensive teammate, a quarterback will average 14 fewer total offensive yards per game.
The coefficients in Model I and Model II reveal no statistically significant relationship between a
quarterback’s Wonderlic score and his passing performance in college. It should be noted, however, that
considerable differences in both terminology and depth exist between collegiate and NFL playbooks, and
a quarterback’s intelligence may affect his passing performance in the NFL even if it does not in college.
Model V developed in the next section will test if a quarterback’s intelligence affects his NFL passing
efficiency during his rookie year.
Table 2: Passing Efficiency and Total Offense models
HEIGHT (inches)
FORTY (seconds)
DRAFTCAST (# of drafted
offensive teammates)
(0.8)
DRAFTCLASS (# of drafted
players from team)
(0.81)
WONDERLIC
Division 1A, 1=yes
Race, 1=non-white
Observations
F Value
R-squared
Adjusted R-squared
(Model I)
NCAA
0.439
(0.44)
4.57
(0.52)
0.621
(Model II)
TOPGB
-4.098
(0.84)
71.917
(1.68)*
-14.083
(3.73)***
0.545
0.419
(0.13)
0.043
(0.21)
-1.115
(0.66)
8.886
(2.17)**
84
1.37
0.11
0.03
0.366
(0.36)
4.99
(0.61)
44.836
(2.26)**
84
4.58***
0.29
0.23
Absolute value of t statistics in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
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Intelligence and Football: Testing for Differentials in Collegiate Quarterback Passing Performance and NFL Compens
by U.S. Sports Academy - The Sport Journal - http://thesportjournal.org
Modeling Intelligence and the NFL draft
This section focuses on the relationship between intelligence and quarterback draft position (Model III)
and compensation (Model IV). The player’s rookie year salary (REALSAL) is his first-year
compensation in 2004 dollars against the salary cap. Despite the fact that the structuring of contracts
varies greatly between first-round picks and all other selections, the player’s rookie year salary reflects
the team’s relative willingness to pay for a rookie quarterback given the availability of free agent
quarterbacks and the limits of the NFL salary cap and team-specific rookie cap. 2 In recent years, NFL
franchises have increasingly used incentive clauses, deferred and option bonuses in addition to traditional
signing bonuses to defer the cost of signing first-round draft picks. Such a structuring of contracts also
insulates the franchises against the risk inherent in both the evaluation of athlete’s abilities and the
likelihood of serious injury. The quarterback’s draft position (DRAFT) is his selection number in the
draft (e.g., a quarterback selected with the eighth choice in the second round (40th overall pick) would
have a draft position of 40.)
If reality does indeed reflect what the previous models suggest (that intelligence has no affect on passing
ability), then it is doubtful that a player’s Wonderlic score will affect the dependent variables – DRAFT
and REALSAL – in Model III and Model IV. To the extent that his past performance is indicative of his
true ability as a quarterback (and there is great debate on this issue), then the quarterback’s draft position
and rookie year salary should primarily be explained by themeasures of his collegiate passing
performance and the expected ease of his transition to the professional ranks. The models estimated
below reveal that only one of the two measures of collegiate passing performance, TOPGB, is statistically
significant in both Models III and IV.
The coefficients of the Models III and IV should be of opposite signs due to the inverse relationship
between draft position and a player’s salary. This is indeed observed in the comparison of the two models
as shown in Table 3. The signs of the coefficients generally reflect the a priori expectations, with some
interesting exceptions. Note that while quarterbacks benefit substantially from the number of collegiate
NFL-caliber offensive teammates in Model III and Model IV, Model IV suggest that franchises do make
efforts to account for the general quality of the player’s offensive (e.g., offensive cast teammates include
wide receivers, running backs, and tight ends, but exclude the offensive line) and defensive teammates as
reflected in the negative coefficient of DRAFTCLASS. Both DRAFTCAST and DRAFTCLASS
represent competing peer effects in the model. While the estimated DRAFTCAST coefficient is of similar
sign and significance in previous literature (Mirabile, 2004), it should be emphasized that the datasets for
this and the previous study were considerably different, in particular the latter was composed of both
drafted and non-drafted athletes.
Table 3: Draft, Salary, and NFL passing models
HEIGHT (inches)
FORTY (seconds)
DRAFTCAST (# of
(Model III)
DRAFT
-14.55
(2.36)**
200.83
(3.68)***
-12.04
(Model IV)
REALSAL
216,192
(3.99)***
-2,304,356
(4.81)***
128,819
(Model V)
NFL ROOKIE RATING
-4.19
(1.49)
22.98
(0.97)
-2.41
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Intelligence and Football: Testing for Differentials in Collegiate Quarterback Passing Performance and NFL Compens
by U.S. Sports Academy - The Sport Journal - http://thesportjournal.org
drafted offensive
teammates)
(2.24)**
DRAFTCLASS (# of
drafted players from
team)
(1.50)
WONDERLIC
Division 1A, 1=yes
Race, 1=non-white
TOPGB
NCAA
Observations
F Value
R-squared
Adjusted R-squared
(2.73)***
6.15
(0.94)
-80,140
-0.50
(2.22)**
-1.08
(0.85)
-39.30
(3.81)***
-6.47
(0.25)
-0.53
(3.27)***
-0.21
(0.27)
84
7.42***
0.47
0.41
(0.28)
-1409
-0.13
290396
(3.20)***
-273,860
-1.21
5,155
(3.63)***
12,598
(1.84)*
84
8.85***
0.51
0.46
-0.57
(0.96)
8.16
(1.64)
-2.89
(0.26)
-0.04
(0.48)
0.45
(1.16)
61
0.82
0.12
-0.03
Absolute value of t statistics in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
The coefficient on the quarterback’s Wonderlic score is not statistically significant, suggesting that NFL
franchises do not select smarter quarterbacks sooner or compensate them better than their peers, ceteris
paribus. The regression results show that quarterbacks are compensated not only for than their collegiate
passing performance, but for how the quarterback is expected to perform in the NFL. Note these
expectations take the form of significant coefficients for a player’s height, time in the 40-yard dash, and
level of past competition (Division 1A). Such traits are highly prized for rookie quarterbacks, whose
ultimate success is determined by their ability to adjust to the size and the speed of NFL opponents. The
conclusion from these coefficients is that either intelligence is not an important factor in drafting and
compensating rookie quarterbacks or that concerns about a quarterback’s intelligence raise flags which
are consistently investigated and subsequently lowered before the draft. Although the models revealed no
compensation for smarter players at the quarterback position, such compensation may indeed exist at
other positions where such a wide variety of performance statistics are not readily available.
As suggested previously, a quarterback’s intelligence may affect his passing performance in the NFL
even if it does not in college. Model V uses the same group of independent variables utilized in previous
models to explain the dependent variable, NFL ROOKIE PASSING, the quarterback’s NFL rookie
passing efficiency rating. The formula for passing efficiency in the NFL is different from its NCAA
counterpart, with NFL passing efficiency employing different scales and a capped system. Because many
rookie quarterbacks receive little or no playing time, this variable is not perfectly observed and could be
subject to significant measurement error. Only 61 of the 84 observations have observed passing efficiency
statistics during their rookie year. In fact, due to the wide variation in playing time among rookie
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Intelligence and Football: Testing for Differentials in Collegiate Quarterback Passing Performance and NFL Compens
by U.S. Sports Academy - The Sport Journal - http://thesportjournal.org
quarterbacks, the variance in this measure is quite large. The results show a negative but not statistically
significant relationship between passing efficiency in the NFL and intelligence as measured by the
Wonderlic test.
Discrimination in the NFL Draft
In this section, we will briefly address the literature’s history of NFL discrimination and test whether any
evidence of discrimination exists at the quarterback position within the developed models. As has been
noted in previous literature (Kahn, 1992), white athletes have historically benefited from a race premium.
However, using data from the 1996 season, Gius and Johnson (2000) found evidence of reverse
discrimination in the NFL with whites earning 10 percent less than their black peers, results they believe
were not previously found because prior investigations used data from the 1970s and 1980s.
We can utilize a group means t-test to determine whether the observed distributions of REALSAL and
DRAFT are statistically different for white and non-white quarterbacks. After employing t-test of each of
these variables, we can reject the hypothesis of equal means for DRAFT but not REALSAL. In particular
the mean DRAFT position for white quarterbacks was 117.3 (with a standard error of 10.2) and the mean
DRAFT position for non-white quarterbacks was 75 (with a standard error of 17.5). Although this result
is significant at the five percent level, given the relatively small sample size, we should be hesitant to
infer the existence of discrimination. Model III and Model IV are better able to test for evidence of
discrimination against non-white quarterbacks by controlling for all other differences between the two
groups. In fact, neither model reveals evidence of such discrimination directly, though this result may
change if the time period of the study were different.
Summary and Conclusions
The market for NFL rookie quarterbacks was examined between 1989 and 2004. Attempts to model
passing performance using player and team characteristics revealed statistically significant relationships
between a quarterback’s collegiate passing performance and his race and teammates. Intelligence, as
measured by the Wonderlic score, was statistically insignificant. Likewise, while expected relationships
were found between collegiate passing performance and NFL rookie year salary, the author found no
statistically significant relationship between intelligence and compensation or intelligence and draft
number after controlling for passing ability. Although the models revealed no compensation for smarter
players at the quarterback position, such compensation may indeed exist at other positions where such a
wide variety of performance statistics are not readily available. Future studies may endeavor to control for
more of the franchise- and league-specific factors that impact the drafting and compensation of collegiate
athletes.
This article presents empirical evidence that within the modern draft era, there exists no statistically
significant relationship between intelligence and quarterback performance at either the collegiate or
professional level. Likewise, more intelligent quarterbacks are neither selected earlier nor compensated
more for their mental abilities. Since no statistically significant relationship exists between tested
intelligence and performance within the data examined in this study, NFL franchises might better utilize
resources by focusing on other aspects of quarterback evaluation.
Notes
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Intelligence and Football: Testing for Differentials in Collegiate Quarterback Passing Performance and NFL Compens
by U.S. Sports Academy - The Sport Journal - http://thesportjournal.org
1. This distinction is made because there are groups of quarterbacks who are drafted but not signed, and
likewise a group of undrafted free agent quarterbacks who do sign NFL contracts in their rookie years.
The group analyzed in this paper is composed only of players who are both drafted and signed.
2. The rookie cap, the amount of salary cap dollars available to sign rookies, is determined by the number
and placement of each team’s draft selections in a given draft.
References
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(accessed March 7, 2005).
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(accessed March 7, 2005).
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8. Kahn, L.M. (1992) “The Effects of Race on Professional Football Players’ Compensation.”
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9. Mirabile, M. (2004) “The Peer Effect in the NFL Draft.” The Sport Supplement, 12(3).
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10. USA Today. (2005) “USATODAY.com – Football salaries database.” USAToday.com.
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Author Information
McDonald P. Mirabile
macmirabile@yahoo.com
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