Rafael Nadal serving a ball during a tennis match.

“He’s heating up!”. “He’s on fire!”. “Is it the shoes?”. “He just got his degree from Dunking on U!”. Quotes from broadcaster Mike Breen during his animated commentary of the exhilarating 2016 NBA finals? No, a list of now-hackneyed catchphrases originally used in NBA Jam. In 1993, NBA Jam, the highest-earning arcade game of all-time, was released to arcades across the United States. Although it featured groundbreaking graphics and was the first video game officially licensed by the NBA, the game was famous for its numerous computer-generated taglines, which led to a cult following large enough to generate revenues exceeding 4 billion dollars in sales. Unfortunately, some behavioral economists credit these seemingly obscure catchphrases with the mass-dissemination of one of the biggest misconceptions in sports: the hot-handed fallacy. In sports of all varieties, numerous behavioral economics concepts — chiefly loss-aversion, anchoring, and the hot-handed fallacy — are responsible for skewed results, irrationality, and other psychological miscalculations, effects that can be corrected with the right approach.

In his recently released book, Brain Bugs: H ow the Brain’s Flaws Shape our Lives, UCLA neurologist Dean Buenomono explains loss-aversion through a study in which participants were given $50 and asked whether they would rather keep $30 or gamble with a 50/50 chance of keeping or losing the entire $50. In this initial situation, 43% of the participants decided to gamble. The participants were then asked whether they would rather lose $20 or gamble with a 50/50 chance of keeping the whole $50. Despite having identical circumstances to the first situations, 18% more participants desired to gamble when presented with the second situation. This simple study demonstrates loss-aversion, an anomaly where humans irrationally act differently in response to similar-sized gains or losses. Oddly, this irrational Human paradox of loss-aversion has also manifested itself in tennis. John Isner, the currently undisputed face of American tennis, has one of the most prolific serves in the game. In tennis, the serving player is given two opportunities to serve in bounds before being penalized. Isner, like most players, deliberately hits his first serve to showcase his power in an attempt to catch the returning player off-guard. While using his first serve, Isner’s serve is in bounds roughly 68% of the time and Isner wins 78% of points played off his first serve. However, if his first serve is no good, Isner resorts to his secondary service, which is in-bounds 90% of the time, but only results in a 50/50 chance of winning the point.1 If Isner uses a fast serve and then a slower serve, he will win 64.5% of points, Interestingly enough, if Isner were to use two fast, 140 mph serves consecutively, he would be liable to win 65.81% of points, a greater percent than he usually would. Isner’s choice to serve conservatively during his second serve illustrates his susceptibility to loss-aversion because his being bogged down by the possibility of losing a point due to a double fault, stops him from winning more points by employing two aggressive serves. A critic of this analysis may say that Isner is currently the best server in the game, and that this analysis does not apply to the average tennis pro. To address this concern, a more average tennis player could be examined. Taking the service statistics of Nick Kyrgios, a flamboyant, 21-year-old Australian tennis player, as an example, the results would be effectively the same. Kyrgios, whose 1st serve is in 65% of the time, wins 76% of his 1st service points.2 Accordingly, Kyrgios’s second serve is in 90% of the time and he only wins 53% of his 2nd service points. If Kyrgios uses the traditional method to serving (fast then slow) his will win 63.09% of his points. However, if he employs the modified method (essentially two first serves) he will win 64.32% of his points. Taking this analysis a step further, when the aggregate statistics of the top 20 players in the world (a diverse group of players that contains a range of serving techniques and skillsets), the new method yields an average increase of 1.12% in probability of winning the point.3 Given that this improved method to service works on both the game’s best servers and sub-par players, it is clear that this is a practice that should be given consideration by tennis coaches.

Similarly, loss aversion is markedly present in the actions of PGA golfers during their putts. In an extensive investigation conducted by Devin G. Pope, a University of Chicago faculty member, and Maurice Schweitzer, a Wharton School faculty member, 2.5 million putts from the PGA tour between 2004 and 2009 were analyzed in order to find the difference between a golfer putting for par and a golfer putting for a birdie. By the end of the inquiry, which analyzed the tendencies of the tour’s best golfers, it was found that a tremendous 83.9% of putts were holed when par was at stake and a measly 28.3% of putts were completed when a birdie was possible.4 Given that not all putts are of equal difficulty, the results of the study still overwhelmingly point to a golfer’s propensity towards assigning a par-saving putt and a birdie-saving putt, two strokes of identical value, different magnitudes of relative value. Aside from Pope’s study, analysis of 10 players (using statistics from the PGA tour)5, who are not currently ranked in the top 10 in the Tour, illustrates the same contention — that golfer’s give identical putts different implicit values, as illustrated in the table below.

The data illustrates that even golfers of a lower-caliber than those identified in Pope’s study, are susceptible to the same tendencies, with an average of a 23% differential between pars and birdies made. Considering that both puts have the same practical incentive, the difference in added pressure or relative value between them has no rational meaning, and is a clear disadvantage for any competitive golfer. Although it would be difficult to do, a possible

solution for this problem could be to reprogram the intrinsic connotations that golfers have in their minds on the green, which could only be facilitated through a tremendous amount of practice. Ironically, the only two PGA tour golfers who make more (or an identical value of) birdie putts than par putts, Luke Donald (Northwestern University)6 and Kevin Streelman (Duke University)7, are graduates from two top-25 ranked universities. Perhaps they took a few behavioral economics courses during their college years.

In a study performed by Daniel Kahneman and Amos Tversky (two high-profile behavioral economists), participants were presented with one of two possible mathematical questions that they would be required to tackle without the use of a calculator: what is the product of 1 x 2 x 3… x 8 or what is the product of 8 x 7 x 6… x 1. After tallying the results, Kahneman and Tversky found that the first question had an average response of 512 and the second question have an average response of 2000.8 Keeping in mind that the answer to the second question was on average 4 times as large as the first question, the two researches were able to discern that the reason for the immense difference between the two answer of the the two identical questioned lied in the question’s layout. The fact that the first question started with the smallest numbers in the sequence, caused the participants to immediately anchor their potential answers to smaller, seemingly more-viable options. The opposite is true for the participants who were presented with the second questions. Kahneman’s experiment exemplifies the Human tendency to rely too heavily on the first pieces of evidence given when making decisions. This cognitive phenomenon, referred to as the anchoring bias, is an innate behavioral tendency that’s far-reaching implications penetrate the sphere of professional sports, specifically the decisions of referees. In Scorecasting, a book written by The University

of Chicago’s Tobias Moskowitz, the impact that anchoring has on the decisions of referees is explained through the use of data from professional sporting events. For instance, the book utilizes a study conducted by a European University, where an Italian soccer club played 21 home games without spectators. The study found that the referees of the games called 23% less foulds and a whopping 70% less red cards.9 This study illustrates the pressure referees face due to the presence of spectators, who often yell at referees to make calls in favor of their teams. The animated screaming of the fans present the referees with an anchor to make their judgements off of because the camaraderie of the home team’s fan base is the first thing that a referee sees and hears. This initial basis is bound to affect the referee’s call because it difficult for a referee to completely block out the wishes of the 70,000+ fans around him/her. The anchoring bias caused by the enthusiasts of the home team can be seen across the professional sports spectrum: the home team wins 54% of games in the MLB, 63% of games in the English Premier League, and 69% of NCAA Basketball games. This research typifies the sweeping effect that spectators have on referees and the calls they make, possibly hinting at the need for greater use of computer-based referee systems or remotely refereed sporting events, as they would be virtually unsusceptible to the anchor-bias caused by spectators and the home-field advantage.

The Hot-handed Fallacy is perhaps the most eminent behavioral economics concepts relating to sports. In essence, the fallacy states that a person or athlete who has achieved success randomly is categorically more likely to achieve success in the future. This intrinsically-human, false assumption is often a mistake sports analysts make during predictions. A notable example of this fallacy lies in the results of Super Bowl XLII, where the New York Giants beat the previously undefeated New England Patriots, who analysts predicted would win by 12 points. This controversial result authenticates that prior instances of success do not necessarily have an effect on the future. The Hot-handed Fallacy was first debunked in an experiment conducted by Thomas Gilovich of Cornell University. In his study, Gilovich sampled the opinions of hundreds of spectators at a Cornell basketball game and found that 96% of the attendees thought that “after having made a series of shots in a row, a player is more likely than normal to make his or her next shot.” However, after conducting a controlled experiment with the Cornell Varsity Basketball team and sifting through years worth of NBA shooting records, Gilovich found no evidence supporting the views of the spectators. For instance, Gilovich found that Larry Bird’s free-throw percentage (during the 1980–82 seasons) after missing his first attempt was 91%, and his free-throw percentage after making his first shot was 88%.10 The fact that Larry Bird, one of the mostadept NBA players of all time, shot better after missing his first shot, invalidates the Hot-hand Fallacy. A false belief that has materialized itself in the misinformed comments of easy-going spectators and accomplished sports commentators alike, the Hot-hand fallacy is perhaps the most identifiable behavioral economics concept in sports. Although there is no definitive solution to the hot-handed fallacy, it could be helpful to instruct sports commentators and video game designers to stop referring to players being “on a roll” or “on fire”.

Whether it is tennis, golf, basketball, or even the referees who enforce the rules, behavioral economics concepts are deeply entwined in every aspect of sports, and their effects are striking. That fact that it is nearly impossible to watch an NFL playoff game without seeing the referee making a questionable call in favor of the home team or watch an NBA game without hearing the commentator reference the hot-handed fallacy or watch Phil Mickelson miss an easy putt for a birdie during the British Open, illustrates the incredible effect these concepts have on sports. Nonetheless, despite having been ingrained in many athletes, many of these issues have simple and effective solutions. Computer-based referee systems, a greater understanding of the hot-handed fallacy, and small shifts in strategic mindsets, can all be employed to ensure that the future of sports will be more equitable and competitive in the future.