Behavioural Economics & Sports Data

By David Butler

From time to time I get inquiries from students who are studying and researching concepts important to behavioural economics in the context of sport. This entry might be a help in getting started on the nexus.  The short list of five biases/fallacies and readings below is the largely created from email correspondences over the past few years. In time, hopefully I can flesh this out, creating a more detailed taxonomy and readings list for students. Part I below limits the concepts and readings to judgment and decision-making research.

It is important to note two points. The content below looks toward general behavioural concepts as the starting point and while some of the references here are old, they still represent important contributions. Secondly, the usual disclaimer applies -  the list definitely does not intend to provide an exhaustive account of all concepts studied or papers available.

Part I

Sport often offers a valuable domain to study the economics and psychology of decision making due to data accessibility (labour market data such as productivity and, at times, wage rates), methodological advantages (repeated but autonomous decision making occurs in well-defined environments) natural incentives (commonly monetary rewards are high) and the fact that sports stars have had an extensive opportunity to learn.

A good place to start considering a general connection between behavioural economics and sport in light of these advantages would be to consult the relatively recent paper by Pope and Schweitzer (2011) which asks Is Tiger Woods loss averse?

Pope, D. G., & Schweitzer, M. E. (2011). Is Tiger Woods loss averse? Persistent bias in the face of experience, competition, and high stakes. The American Economic Review, 101(1), 129-157.

Following on from this, here are brief and simplified explanations accompanied by some readings for specific biases/fallacies where sports data is used to investigate decision-making.  

1. The Conjunction Fallacy

The conjunction rule states that if one conjunctive event is composed of two primary events, the probability of this single event occurring cannot be greater than probability of either one of the two primary events occurring independently. A breach of this rule was most notably observed in Kahneman and Tversky’s  ‘Linda problem’ where the authors contend that choices can be obscured by a representativeness heuristic – a cognitive mechanism used to make probability judgments under uncertainty.   

Erceg, N., & Galić, Z. (2014). Overconfidence bias and conjunction fallacy in predicting outcomes of football matches. Journal of Economic Psychology, 42, 52-62.

Nilsson, H., & Andersson, P. (2010). Making the seemingly impossible appear possible: Effects of conjunction fallacies in evaluations of bets on football games. Journal of Economic Psychology, 31(2), 172-180.

2. The End-of-Day Effect

This bias occurs when individuals choose bets that have a lower probability of occurring but higher payoff in the later stages of a round of gambling. Prospect theory can accommodate this bias if gamblers form reference points in regards to their profit making - this reference profit is commonly zero. In the context of horse racing, If gamblers are incurring high loses by the last race of the day they can prefer to substitute away from gambling on favourites, choosing horses that have lower likelihood of wining in an effort to return to the reference point of zero

Ali, M. M. (1977). Probability and utility estimates for racetrack bettors. Journal of political Economy, 85(4), 803-815.

McGlothlin, W. H. (1956). Stability of choices among uncertain alternatives. The American Journal of Psychology, 604-615.

3. The Hot-Hand Fallacy

The hot-hand fallacy is a mistaken belief that if an individual successfully achieves an objective, this causes a greater chance of additional success in that activity for the short term future. The name for the term is derived from basketball, where fans and player alike often believe that their chances of success - scoring another basket - are higher following a previous score rather than a miss. It seems like a cottage industry has sprung up on this topic. A place to start is the review paper by Bar-Eli., Avugos, and Raab.

Bar-Eli, M., Avugos, S., & Raab, M. (2006). Twenty years of “hot hand” research: Review and critique. Psychology of Sport and Exercise, 7(6), 525-553.

4. The Sunk Cost Fallacy

A sunk cost fallacy or escalation effect is committed when a decision-maker holds constant or increases their commitment to a particular choice, despite marginal costs exceeding marginal benefits. When more efficient alternative choices are available, decision makers maintain a choice that associated costs cannot be recovered. Simply put, people irrationally cry over spilt milk.

Borland, J., Lee, L., & Macdonald, R. D. (2011). Escalation effects and the player draft in the AFL. Labour Economics, 18(3), 371-380.

Camerer, C. F., & Weber, R. A. (1999). The econometrics and behavioral economics of escalation of commitment: a re-examination of Staw and Hoang’s NBA data. Journal of Economic Behavior & Organization, 39(1), 59-82.

Staw, B. M., & Hoang, H. (1995). Sunk costs in the NBA: Why draft order affects playing time and survival in professional basketball. Administrative Science Quarterly, 474-494.

5. The Winner’s Curse

The winner’s curse is the tendency for individuals to overbid in common value auctions when information is not complete. This idea was originally conceptualized in light of auctions for oil reserves in the Mexican Gulf. Winning bids in an auction environment can exceed the value of the asset purchased or can produce returns that are less than expected.

Burger, J. D., & Walters, S. J. (2008). The existence and persistence of a winner's curse: new evidence from the (baseball) field. Southern Economic Journal, 232-245.

Cassing, J., & Douglas, R. W. (1980). Implications of the auction mechanism in baseball's free agent draft. Southern Economic Journal, 110-121.

Kahn, L. M. (1993). Free agency, long-term contracts and compensation in Major League Baseball: Estimates from panel data. The Review of Economics and Statistics, 157-164.