Volume 19, Issue 3

Mindset can shape sports performance, but these effects can be difficult to detect empirically. We use data from high school sprinters to explore mindset effects on 100 m finishing times and find that headwinds hamper performance more than can be attributed to the physics of wind resistance alone. These (implied) psychological effects of wind on sprint times are stronger for girls than for boys. Having established the presence of mindset-based slack in physical performance, we then test whether sprint times changed in the wake of Matthew Boling’s record-breaking sprint in 2019 that, after going viral on social media, potentially boosted self-efficacy among high school sprinters. Using 2018 and 2019 high school track meets in California, we observe notable changes in average sprinter performance for certain types of athletes in specific wind conditions after Boling’s race that did not occur in the previous season. These results control for many observable variables, correct for multiple hypothesis testing, and use entropy balancing weights to ensure statistical comparability between the two years. We detect differences in this ‘Boling effect’ based on the predicted racial composition of teams and the predicted race of athletes, which is relevant given the racial angle of coverage of the record-setting run. We posit vicarious self-efficacy as a plausible explanation for these difference-in-differences patterns. Pronounced heterogeneity in these results demonstrates some of the complexities and nuances of mindset effects even in settings where performance is easily quantified. Subtle contextual and salience cues appear to mediate the impact of vicarious self-efficacy beliefs on performance.

In recent years, the game of football has made a shift towards being more quantitative. With the advent of charting and tracking data, player evaluation is able to be studied from several different angles. In this paper, we build and refine two novel metrics: Bite Distance Under Expected (BDUE) and Ground Covered Over Expected (GCOE) for the evaluation of linebackers in the National Football League (NFL). Here, we show that these metrics are heavily correlated with each other, which demonstrates the trade-off linebackers have to make between being aggressive against the run and being effective when the opposing offense is using play-action. We also show that these metrics are more stable than those in the public space. Finally, we show how these metrics measure deception by opposing offenses.

We analyze the impact of psychological pressure on performance with over 5500 handball penalties thrown in either the decisive stage or the rest of the game during matches of the 2019/2020 season in the first three German handball leagues. Contrary to the choking under pressure phenomenon, most of the analyzed players perform best when it matters the most. The positive effect of pressure on performance is highest when the score is even or when the thrower’s team is trailing. We control for gender and psychological traits assessed with a survey. In our sample, female players score with a higher probability than male players. The positive impact of pressure is not significantly higher for female players.

In this study we analyse data from world cup cross-country skiing sprint elimination tournaments for men and women in 2015–2020. Instead of being assigned a quarterfinal according to a seeding scheme, prequalified athletes choose themselves in sequential order in which of the five quarterfinals to compete. Due to a time constraint on the day the competition is held, the recovery time between the elimination heats varies. This implies a clear advantage for the athlete to race in an early rather than in a late quarterfinal to maximize the probability of reaching the podium. The purpose of the paper is to analyse the athletes’ choices facing the trade-off between recovery time and expected degree of competition when choosing in which quarterfinal to compete. We find empirical support for the prediction that higher ranked athletes from the qualification round prefer to compete in early quarterfinals, despite facing expected harder competition. Nevertheless, our results also suggest that athletes underestimate the value of choosing an early quarterfinal. In addition, we propose a seeding scheme capturing the fundamental disparity across quarterfinals using the estimates from alogistic regression model.

We introduce a non-standard generalization of the Elo rating system for competitions involving two or more participants. The new system can be understood as an online estimation algorithm for the parameters of a Plackett–Luce model which can be used to make probabilistic forecasts for the results of future competitions. The system’s distinguishing feature is the way it treats competitions as sequences of elimination-type rounds that sequentially identify the worst competitors rather than sequences of selection-type rounds that identify the best. The significance of this important modelling choice is discussed and its consequences are explored. Finally, our generalized Elo system’s predictive power is demonstrated using data from Formula One racing.