Lead Us Not into Tanktation: A Simulation Modelling Approach to Gain Insights into Incentives for Sporting Teams to Tank

• Published in: PloS one Vol. 8; no. 11; p. e80798
• Main Authors: Tuck, Geoffrey N., Whitten, Athol R.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 29.11.2013; Public Library of Science (PLoS)
• Subjects: Aging; Algorithms; Athletes; Athletic drafts & trades; Athletic recruitment; Computer Simulation; Economics; Equilibrium; Fisheries; Humans; Incentives; Models, Theoretical; Players; Productivity; Professional baseball; Professional basketball; Simulation; Sport fishing; Sports; Sports injuries; Stochasticity; Success; Team size
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0080798

Annual draft systems are the principal method used by teams in major sporting leagues to recruit amateur players. These draft systems frequently take one of three forms: a lottery style draft, a weighted draft, or a reverse-order draft. Reverse-order drafts can create incentives for teams to deliberately under-perform, or tank, due to the perceived gain from obtaining quality players at higher draft picks. This paper uses a dynamic simulation model that captures the key components of a win-maximising sporting league, including the amateur player draft, draft choice error, player productivity, and between-team competition, to explore how competitive balance and incentives to under-perform vary according to league characteristics. We find reverse-order drafts can lead to some teams cycling between success and failure and to other teams being stuck in mid-ranking positions for extended periods of time. We also find that an incentive for teams to tank exists, but that this incentive decreases (i) as uncertainty in the ability to determine quality players in the draft increases, (ii) as the number of teams in the league reduces, (iii) as team size decreases, and (iv) as the number of teams adopting a tanking strategy increases. Simulation models can be used to explore complex stochastic dynamic systems such as sports leagues, where managers face difficult decisions regarding the structure of their league and the desire to maintain competitive balance.