nep-spo New Economics Papers
on Sports and Economics
Issue of 2024‒09‒09
three papers chosen by
Humberto Barreto, DePauw University


  1. Competitive Recruiting Imbalances Between NCAA Conferences By Adam Houston; Peter A. Groothuis; Dennis Guignet
  2. The proponents of the European Football Super League have switched from a proposal suggesting that permanent members self-govern their (almost) closed competition to a proposal maintaining the concept of self-governance by the participating clubs but now advocating participation on the basis of sporting merit. Can self-governance be realistically introduced at the top of the football pyramid without closing this top? The paper explains why this is not the case and how the new proposal is a closed league in disguise, which is likely to trigger the same value creation problems as an openly closed league. By Egon Franck
  3. Is the ‘Swift Effect’ fact or folklore? A Quasi-Experimental Investigation into Taylor Swift's Influence on American football performance By Smoliga, James M; Sawyer, Kathryn E

  1. By: Adam Houston; Peter A. Groothuis; Dennis Guignet
    Abstract: The National Collegiate Athletic Association’s (NCAA) Division I Football Bowl Subdivision is divided into ten conferences. In the last few years there have been significant conference realignments as many schools have changed conferences. Using a novel dataset of football player recruitment from 2014-2023 at 118 different FBS university programs, we analyze the distribution of recruitment athletic talent across teams and conferences. While most larger universities in “Power Five” conferences recruit a similar number of five, four, and threestar recruits, we find that universities in the Southeastern Conference enjoy greater recruitment success, even after controlling for athletic program success. In comparison, we find that smaller universities in “Group of Five” conferences all are at a disadvantage, recruiting fewer highly rated players. Our analysis suggests that conference affiliation is one of the major drivers of talent recruitment. Such recruitment imbalances yield broader implications because football team has been found to be associated with broader university success in terms of the quality and quantity of student applications, admissions, and endowment. Key Words: Sports, Football, Recruiting, NCAA, Collegiate Athletics, Competitive Balance
    JEL: Z29 Z28 I20
    Date: 2024
    URL: https://d.repec.org/n?u=RePEc:apl:wpaper:24-16
  2. By: Egon Franck (Department of Business Administration, University of Zurich)
    Keywords: Outcome Bias, European Football Super League, Self-governance, Closed leagues
    JEL: D02 D23 D71 L83
    Date: 2024–08
    URL: https://d.repec.org/n?u=RePEc:zrh:wpaper:403
  3. By: Smoliga, James M (Tufts University School of Medicine); Sawyer, Kathryn E
    Abstract: Taylor Swift’s present at National Football League (NFL) games was reported to have a causal effect on the performance of Travis Kelce and the Kansas City Chiefs. However, this has not been validated through a robust statistical analysis. Therefore, the purpose of this study was to critically assess whether Taylor Swift's game attendance influenced: 1) Travis Kelce’s football performance, and 2) Kansas City Chiefs' game outcomes in the 2023 American football season. METHODS: A quasi-experimental study with propensity score matching was employed. Chiefs’ pregame Elo score was identified as a confounding factor which influence Kelce’s performance during the pre-Swift era (2014-2022 season). Each Chiefs game from the Swift era (2023 season) were matched to five games from the pre-Swift era by Chiefs’ pregame Elo. Linear mixed effects models were then used to determine how Swift’s presence or absence in Swift-era games influence Kelce’s performance, relative to historical data. Kelce’s yards was the dependent variable, random factor was each “matched set” of six games (5 pre-Swift era, 1 Swift era), and Chiefs pre-game Elo was entered as a covariate. Two models were developed: 1) Swift present (n=13 Swift era games, matched to 65 pre-Swift era games); and 2) Swift absent (n=6 Swift era games, 30 pre-Swift era game). Additionally, a binary logistic regression model was developed to determine if Swift’s presence influenced the Chief’s game outcomes, relative to historical averages. RESULTS: Kelce's performance was similar between the Swift (2023 season, 70.5 yards) and pre-Swift (2014-2022 seasons, 73.9 yards) eras. Linear mixed effects models revealed that Kelce achieved an extra mean 7.1 (95% confidence interval: -12.7, 26.9) yards per game when Swift was in attendance (n=13 games in the Swift era), compared to matched games from the pre-Swift era however this was not statistically significant (p=0.476). When Swift was absent from games (n=6 in the Swift era), Kelce’s performance changed by -28.6 (-69.4, 12.3) yard per game, compared to matched games from the pre-Swift era – again not statistically significant (p=0.163). Swift’s attendance did not significantly increase the Chief’s likelihood of winning [odds ratio = 1.32 (0.33, 5.34), p=0.692]. DISCUSSION: The weak statistical evidence that spawned the concept of the “Swift effect” is rooted in a constellation of fallacies common to scientific and medical research –including attribution bias, unjustified mechanisms, inadequate sampling, emphasis on surrogate outcomes, and inattention to comparative effectiveness. Clinicians and researchers must be vigilant to avoid falling victim to the “Swift effect, ” since failure to scrutinize available evidence can lead to acceptance of unjustified theories and negatively impact clinical decision-making.
    Date: 2024–08–08
    URL: https://d.repec.org/n?u=RePEc:osf:osfxxx:ujws7

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