Average IQ by Sport
One League Actually Collected Data. Here Is What It Showed.

0 Quick Answer

Updated August 16, 2026 by Structural. There is no dataset of IQ scores by sport. No sporting body administers standardised intelligence batteries, and the tables that circulate are assembled from anecdote, leaked individual results, and one league's screening test.

Direct answer: the exception is the Wonderlic Personnel Test, a twelve-minute, fifty-item cognitive screening instrument used at the American football scouting combine for decades. Aggregate results placed players close to the general working population average, with consistent differences between playing positions and no meaningful relationship to how well anybody subsequently played.

The more interesting research question has moved elsewhere. Studies of elite performance now examine executive function, meaning working memory, cognitive flexibility, and inhibitory control, rather than general ability. That literature has produced genuine findings, and they concern specific capacities rather than an IQ figure.

1 Why Almost No Data Exists

The absence is structural rather than accidental, and understanding why explains what the few available datasets are and are not.

Sporting organisations have no reason to collect it. Selection is based on athletic performance, which is directly observable and measured with far better instruments than any cognitive test. A club evaluating a player watches them play, times them, and measures physical attributes relevant to the sport. Cognitive ability adds nothing that observation of performance does not already capture.

Where cognitive assessment has been used, it has been for a specific purpose rather than general curiosity: predicting how quickly a player can learn a complex playbook, or screening for the ability to make decisions under time pressure in a role that demands it. Those are narrow questions, and they generate narrow instruments.

There are also legal and reputational reasons for caution. Cognitive testing in employment contexts carries legal exposure in most jurisdictions, and professional sport is employment. An organisation collecting such data creates records that can be challenged, leaked, or used against it, which is a strong disincentive when the data has no demonstrated selection value.

Individual athletes are also under no obligation to be tested and no organisation compels it in most sports. The results that reach the public are typically leaks rather than releases, which means the sample reaching public discussion is selected by whatever made a particular result newsworthy.

What all of this means is that any table listing average IQ by sport is a construction. The underlying data for most rows does not exist, and where it exists it is not an IQ measure.

2 The One Real Dataset

The Wonderlic Personnel Test is the exception, and its properties determine what can be concluded from it.

It is a fifty-item cognitive ability test administered in twelve minutes, covering verbal, numerical, and logical reasoning. It was developed as an employment screening instrument, is designed for group administration, and is scored simply as the number of items answered correctly. The severe time limit means almost nobody completes it, which makes it partly a speed measure as well as a reasoning measure, in the sense discussed in Why IQ Tests Are Timed.

It correlates substantially with general cognitive ability, which is what employment screening instruments are built to do, and it is not a clinical battery. It produces one number, has no domain structure, and cannot support the profile-level interpretation that a full assessment provides. Converting a Wonderlic score to an IQ figure requires assumptions about the relationship between two differently normed instruments, and published conversion tables should be treated as approximations.

Its use at the American football scouting combine ran for decades and produced the only large body of cognitive test results on elite athletes anywhere. The league did not publish individual scores, and results leaked consistently enough that aggregate patterns became widely known.

The test has since been dropped from the combine, replaced by an assessment tool designed for the specific demands of the sport rather than general cognitive screening. That decision is itself informative and is covered in section 5.

3 What the Scores Actually Showed

The headline result is the one that surprises people in both directions, and it is worth stating plainly.

Aggregate player scores sat close to the average for the general working population on which the instrument was normed. Elite professional athletes, as a group, performed at roughly the level of the ordinary employed adult.

That finding disappoints two opposing expectations simultaneously. It gives no support to the assumption that professional athletes are cognitively unremarkable, a stereotype with a long and unattractive history. It equally gives no support to claims that elite sport selects for exceptional general ability.

What it actually indicates is that general cognitive ability is not a strong selection filter for professional sport. The filters that operate are athletic, and they are extraordinarily severe: the fraction of players who reach the professional level in any major sport is minute. Those filters simply do not select on the dimension the Wonderlic measures, so the resulting population resembles the general population on it.

The individual results that circulated widely were mostly at the extremes, and this is a selection artefact in the reporting rather than a feature of the data. A player scoring at the ceiling and a player scoring very low both became stories. Players scoring near the middle, which was almost everybody, generated no coverage at all. Anybody forming an impression from remembered headlines has sampled the tails of a distribution and missed its centre entirely.

4 Differences Between Positions

The within-sport pattern is more informative than the overall average, and it is consistent enough to require explanation.

Positions requiring the assimilation of complex tactical information, most notably quarterback, along with offensive line positions and tight ends, produced higher average scores. Positions whose demands are more heavily physical and reactive, including running backs and several defensive positions, produced lower ones.

The obvious interpretation is that roles demanding more cognitive load select for cognitive ability. That is plausible and probably part of the story, and at least two other mechanisms are operating.

The first is that teams have historically used the score in evaluating certain positions and not others. If a low score damages a quarterback's draft position while being ignored for a running back, then selection into the position is partly driven by the test itself. The observed difference then partly reflects the use of the instrument rather than a pre-existing difference.

The second is that positions differ in the educational and developmental paths that lead to them, which introduces every confound that applies to any group comparison shaped by background rather than by the characteristic being measured.

The differences are also modest relative to the variation within any position group. Position groups overlap heavily, as group comparisons almost always do when the between-group difference is a fraction of the within-group spread. Individual players at every position span the full range.

5 Whether It Predicted Anything

This is the question that determined the test's fate, and the answer is the most useful finding in the whole dataset.

Research examining the relationship between combine cognitive test scores and subsequent professional performance has generally found little to no association. Analyses looking at playing statistics, career longevity, and success measures across positions have not found the score to predict how well players performed once in the league.

This is a genuinely informative null result rather than an absence of evidence. Cognitive ability is one of the better predictors of performance across a wide range of occupations, and the fact that it fails here tells you something specific about the job.

Two explanations account for it. The first is range restriction, the same issue examined in Average IQ by College Major. Every player at that level has already passed through filters on physical capability, technical skill, competitive experience, and coachability. Within such an extreme selected group, remaining variation on any single dimension predicts poorly, because the variation that matters has already been used up by the selection.

The second is that the ability the job requires is not the ability the instrument measures. Reading a defensive formation in under two seconds is a domain-specific perceptual and decision-making skill built through thousands of hours of exposure. A twelve-minute general reasoning test does not measure it, and there is no strong reason to expect it would.

The league's eventual replacement of the instrument with a sport-specific assessment reflects exactly this conclusion. When a general measure fails to predict, the response is to measure the specific thing instead.

6 What Does Correlate With Elite Performance

The research that has produced positive findings looks at narrower capacities than general ability, and it is worth setting out because it is the substantive answer to the question this page is about.

Work on elite footballers has examined executive function, meaning the set of capacities involved in flexible goal-directed behaviour: working memory, cognitive flexibility, and inhibitory control. Studies using standardised executive function batteries have found elite players performing above general population norms on these measures, and have reported associations between executive function performance and subsequent competitive success.

Why this succeeds where general ability screening failed is straightforward. Executive function is much closer to what the task demands. A player holding the positions of many moving people in mind while inhibiting an obvious but wrong action and switching plans as the situation changes is performing an executive function task in the technical sense. The measure and the demand are structurally matched.

The same logic applies across sports where anticipation and rapid decision-making under constraint are central, and there is an accumulating literature examining perceptual and cognitive expertise in athletes across disciplines.

Two caveats matter. Sample sizes in this literature are frequently small, because elite athletes are by definition rare and difficult to recruit, and small samples produce unstable estimates. And the direction of causation is not established: sport may develop these capacities, people with these capacities may be selected into elite sport, or both.

The structural point is the same one that runs through cognitive assessment generally. A measure predicts a criterion when the two share the ability being drawn on. Matching the measure to the demand is what makes the difference, and it is the same principle that governs whether training transfers, discussed in Can You Improve Your IQ?.

7 Expertise Is Not General Ability

The distinction underlying everything above deserves stating on its own, because it resolves most of the confusion about athletes and intelligence.

Elite performers in any domain display cognitive feats within that domain that look extraordinary from outside. A goalkeeper reading a shot, a point guard tracking nine other players, a batter picking up a delivery in a fraction of a second. These are genuine and impressive, and they are domain-specific.

The research on expertise has consistently found that such abilities do not generalise. Chess masters have exceptional memory for legal chess positions and ordinary memory for randomly arranged pieces, which was the finding that established the principle. The expertise lives in structured, domain-specific knowledge that makes meaningful patterns instantly recognisable, and it does nothing outside the domain where those patterns exist.

Athletic cognitive expertise works the same way. A player's ability to read a developing move rests on years of exposure to those specific patterns. It is real, it is trained, and it does not transfer to reasoning about unrelated material, which is what a general cognitive measure presents.

This is why the question the page title asks is poorly formed. Asking about the average IQ of a sport asks about general ability in a population selected for domain-specific expertise. The two are almost unrelated, and the answer is uninformative even where the data exists.

The point generalises beyond sport, which is worth noting because it applies to how anybody reads a cognitive score. Every person carries domain-specific expertise built over years in whatever they have done at length, and none of it appears on a general instrument. A cognitive assessment measures the general abilities that would help you acquire expertise in something new, not the accumulated structure of what you already know deeply. Somebody scoring at the population average may be world-class at something no test in existence measures.

The better question is what cognitive demands a given sport actually imposes, and that question has produced real findings, as section 6 describes.

8 The Stereotype Problem

This subject cannot be treated honestly without addressing why the question is asked as often as it is.

The assumption that athletic ability trades off against intellectual ability is culturally durable and has essentially no empirical support. The one substantial dataset places elite athletes near the population average, which is precisely what a null relationship predicts.

The assumption has also historically carried a racial dimension that is worth naming rather than talking around. Discussion of cognitive test results in American football has repeatedly been used to advance claims about players in ways that the actual data does not support, and any treatment of this topic that ignores that history is missing something important about why the question circulates.

The measurement facts are straightforward. Combine cognitive scores clustered near the population average, they showed modest position differences with several plausible explanations, and they failed to predict performance. None of that supports any generalisation about athletes as a group, and the failure to predict undermines the premise that the score identifies anything relevant about them at all.

The opposite overcorrection is also unhelpful. Claiming elite athletes are cognitively exceptional as a group is equally unsupported by the same data. The finding is a null one and the honest report of it is that the filters for professional sport do not operate on this dimension.

What athletes demonstrably possess is extraordinary domain-specific capability developed over many years, alongside the executive function findings in section 6. That is what the evidence supports, and it does not require inflating or deflating anything.

9 Chess, Esports, and the Boundary Cases

Two activities sit at the edge of the sport category and are frequently included in these tables, so they are worth addressing separately.

Chess is the most studied of all expertise domains and the source of the foundational findings in section 7. The relationship between chess skill and general cognitive ability is positive but considerably weaker than intuition suggests, and it weakens further among stronger players, which is the range restriction pattern again. Deliberate practice accounts for a substantial share of the variation in skill, and the memory advantages that define chess expertise are specific to meaningful chess positions.

Esports has attracted research interest in reaction time, attention, and decision-making under time pressure, and the same structure of findings is emerging: domain-specific perceptual and decision skills develop with practice, general ability is a weak predictor within the elite range, and transfer to unrelated tasks is limited.

Both cases illustrate the general point better than physical sports do, because both are unambiguously cognitive activities. If domain-specific expertise fails to reflect general ability even in activities that consist entirely of thinking, the expectation that it should do so in physical sport has no foundation at all.

They also illustrate why practice accumulates into something a test cannot see. A grandmaster has spent tens of thousands of hours building a structured representation of chess positions. That representation is what produces the performance, it is invisible to any general instrument, and no cognitive test administered to a grandmaster measures the thing that makes them a grandmaster.

10 Reaction Time, the One Genuine Overlap

There is a point where athletic capability and cognitive measurement genuinely touch, and it is worth setting out precisely because it is narrower than it first appears.

Reaction time has a long history in intelligence research. Simple reaction time, meaning responding as fast as possible to a single signal, correlates modestly with general cognitive ability. Choice reaction time, where the correct response depends on which of several signals appears, correlates more strongly, and the relationship gets stronger as the decision becomes more complex. Population-based cohort studies have established these relationships on large samples.

Athletes, particularly in fast interceptive sports, display extraordinary response speeds. The overlap is real: both a cognitive reaction time task and a batter facing a delivery involve detecting a signal and initiating a response under time pressure.

What breaks the equivalence is what the athletic version actually contains. An elite athlete's apparent reaction speed is dominated by anticipation rather than by raw response latency. A goalkeeper does not react to the ball leaving the boot, they begin moving from cues in the striker's approach, hips, and plant foot, before the contact happens. Research on interceptive sport has repeatedly found that expert advantage lies in earlier and better use of advance information rather than in faster elementary processing.

That is a trained perceptual skill built on domain-specific pattern knowledge, which puts it squarely in the expertise category of section 7 rather than in the general ability category. Two athletes with identical elementary reaction times will differ enormously in apparent speed on the field, and the difference is knowledge rather than hardware.

The measured overlap therefore holds for elementary reaction time and dissolves for the thing that makes athletes fast. This is the same pattern as everything else on this page: where a general measure and a performance demand share structure, they relate, and where the performance rests on domain-specific learning, they do not.

11 What Coaches Are Actually Screening For

Organisations that do use cognitive assessment are not looking for general intelligence, and understanding what they are looking for clarifies why a general instrument was a poor fit.

The recurring concern is learning rate. Professional playbooks in some sports are large and change weekly, and the practical question is how quickly a player can absorb new material and execute it correctly under pressure. That is closer to a working memory and learning-speed question than to a general ability question, and it is specific to certain roles.

A second concern is decision quality under load. Every sport has moments where a player must choose between options in a fraction of a second with incomplete information and physical exhaustion degrading everything. Organisations want to know how a player's decisions hold up as load increases, which is a question about the stability of performance rather than its peak.

A third is coachability, meaning whether a player adjusts their behaviour in response to instruction and feedback. This is arguably the most valuable of the three and is not a cognitive ability measure at all. It sits closer to personality and motivation, and no reasoning test addresses it.

None of these three is well captured by a twelve-minute general reasoning test, which is a coherent explanation for why the instrument predicted nothing. It was answering a question nobody was asking.

The replacement instruments used in professional sport are built around these specific demands, typically assessing learning, decision-making under pressure, and behavioural tendencies rather than general reasoning. Whether they predict better is an empirical question with limited public evidence, and the design logic is at least aimed at the right target.

12 Where the Circulating Tables Come From

Given that the data mostly does not exist, it is worth accounting for how the tables people find are assembled. There are four sources and none of them supports a group average.

Leaked individual scores. Almost entirely from the American football combine, reported when a result was extreme in either direction. Individual data points, selected for newsworthiness, from one sport, on a screening instrument. Extending them to a sport-wide average has no statistical basis.

Claimed scores from athletes in other sports. Self-reported, or attributed by media, with no verification of instrument, administration, or norms. These carry the same problems as any celebrity IQ claim: usually no source, frequently no test, and no way to check the standard deviation used.

Educational attainment used as a proxy. Some tables substitute the typical education level of a sport's athletes for cognitive data. This measures access, background, and the route into the sport far more than ability, and sports differ enormously in whether their pathway runs through universities.

Pure assertion. A considerable share of these tables have no stated source at all. The numbers appear, get copied across sites, and acquire apparent authority through repetition rather than through anybody having measured anything.

The practical test for any such table is to ask which instrument produced each row, when, on how many people, and against which norms. A table that cannot answer those questions for even one row is not reporting data. That test disqualifies essentially every version of this content in circulation, including the ones ranking twenty sports to one decimal place.

13 A Question Worth Asking Instead

If the interest behind this page is genuine, there is a version of it that data can answer, and it concerns individuals rather than groups.

The demands people describe in sport, holding multiple moving elements in mind, switching plans as situations change, and inhibiting an obvious response in favour of a better one, map onto identifiable domains. Working memory and processing speed in particular are measured directly by standard cognitive batteries, and they are the domains closest to what section 6 found to matter.

A domain profile therefore says something relevant that a composite does not. Somebody with high working memory and moderate crystallised knowledge has a different cognitive shape from somebody with the reverse, and the difference is the kind that shows up in fast-changing situations. This is the same argument that makes a profile more useful than a total score everywhere else, set out in Cognitive Domains.

ACIS reports six domains with percentiles and confidence intervals against a stated reference group, including working memory and processing speed as separate indices. It measures general cognitive domains rather than sport-specific expertise, which section 7 explains no general instrument can capture.

The limitations are the standard ones and are stated in the report: administration is unsupervised, conditions cannot be verified, and no institution is obliged to accept the result. It answers a question about your own cognitive profile, which is the only version of this question that has an answer.

14 FAQ: Cognitive Testing and Sport

15 Best Next Step

One league collected real data for decades. It showed athletes near the population average, modest position differences, and no relationship to performance, which is why the instrument was eventually dropped. The productive research has moved to executive function, where measure and demand actually match.

For the domain structure that makes such matching visible, read Cognitive Domains. For why group averages predict individuals poorly, read Average IQ by College Major. For why training transfers only when it matches the target ability, read Can You Improve Your IQ?. For your own profile, take the assessment.

16 Sources Behind This Page

Claims about combine testing and its predictive validity come from peer reviewed analyses. Claims about executive function and expertise come from the sports science and expertise literatures.

• Lyons, B.D., Hoffman, B.J. & Michel, J.W. (2009). Not much more than g? An examination of the impact of intelligence on NFL performance. Human Performance, 22(3), 225-245. Finds cognitive test scores at the combine to be a weak predictor of subsequent professional performance.
• Vestberg, T., Gustafson, R., Maurex, L., Ingvar, M. & Petrovic, P. (2012). Executive functions predict the success of top-soccer players. PLoS ONE, 7(4), e34731. Open access. Elite players outperform norms on executive function measures, with associations to subsequent competitive success.
• Vestberg, T., Reinebo, G., Maurex, L., Ingvar, M. & Petrovic, P. (2017). Core executive functions are associated with success in young elite soccer players. PLoS ONE, 12(2), e0170845. Open access. Replication and extension in a younger elite sample.
• Chase, W.G. & Simon, H.A. (1973). Perception in chess. Cognitive Psychology, 4(1), 55-81. The foundational demonstration that expert memory advantages are specific to meaningful domain configurations and vanish for random ones.
• Burgoyne, A.P., Sala, G., Gobet, F., Macnamara, B.N., Campitelli, G. & Hambrick, D.Z. (2016). The relationship between cognitive ability and chess skill: a comprehensive meta-analysis. Intelligence, 59, 72-83. Establishes the positive but moderate relationship and its attenuation among stronger players.
• Macnamara, B.N., Hambrick, D.Z. & Oswald, F.L. (2014). Deliberate practice and performance in music, games, sports, education, and professions: a meta-analysis. Psychological Science, 25(8), 1608-1618. How much of expert performance practice accounts for across domains including sport.
• Deary, I.J., Der, G. & Ford, G. (2001). Reaction times and intelligence differences: a population-based cohort study. Intelligence, 29(5), 389-399. Establishes the relationship between simple and choice reaction time and general cognitive ability on a large sample.
• Wonderlic. The publisher of the cognitive screening instrument used at the combine, including its design as an employment assessment rather than a clinical battery.
• McGrew, K.S. (2009). CHC theory and the human cognitive abilities project. Intelligence, 37(1), 1-10. The broad ability structure that determines when a measure and a performance demand are matched.
• American Educational Research Association, American Psychological Association & National Council on Measurement in Education. Standards for Educational and Psychological Testing. Requirements governing the use of cognitive tests in employment selection, including professional sport.
• United States Equal Employment Opportunity Commission. Employment tests and selection procedures. The legal framework that makes cognitive screening in employment contexts, including professional sport, legally sensitive.
• Kuncel, N.R. & Hezlett, S.A. (2007). Standardized tests predict graduate students' success. Science, 315(5815), 1080-1081. Why range restriction attenuates predictive relationships within heavily selected populations.
• Voncken, L., Albers, C.J. & Timmerman, M.E. (2019). Improving confidence intervals for normed test scores. Behavior Research Methods. Open access. Why differences between small selected groups carry wide uncertainty.