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JQAS Highlights: Fantasy Football, Basketball, Tennis, Designing Tournaments Featured in March Issue

1 April 2016 108 views No Comment
Mark E. Glickman, JQAS Editor-in-Chief


Thinkstock photo. The March issue of JQAS features an article asking: “Is There a Pythagorean Theorem for Winning in Tennis?”

Thinkstock photo. The March issue of JQAS features an article asking “Is There a Pythagorean Theorem for Winning in Tennis?”

The March 2016 issue (volume 12, issue 1) of the Journal of Quantitative Analysis in Sports (JQAS) consists of four articles with applications to fantasy football, basketball, tennis, and the optimal design of tournaments.

“An Analytical Approach for Fantasy Football Draft and Lineup Management” by Adrian Becker and Xu Andy Sun is the Editor’s Choice article for this issue and available for free download for 12 months. The article develops and investigates a methodology for selecting lineups in fantasy NFL football that is optimized for winning an entire NFL season. The approach uses historical data to construct player and team performance predictions, and then builds a mixed integer programming model that uses the predictions to guide draft selections and weekly lineup management. The approach is demonstrated on lineup picks for several NFL seasons.

“Bayesian Optimal Design of Fixed Knockout Tournament Brackets” by Jonathan Hennessy and Mark Glickman extends published work by the second author to construct knockout tournaments that globally optimize a specified utility function given partial information about players’ strengths. The paper discusses Monte Carlo estimates of the expected utility and demonstrates a simulated annealing algorithm to optimize the expected utility over the space of candidate tournaments. The paper focuses mainly on designing tournaments that maximize the probability the best player wins the tournament, but also considers other utility functions such as maximizing the probability the best two players meet in the final round of the tournament.

“Modeling and Forecasting the Outcomes of NBA Basketball Games” by Hans Manner develops a state-space model for predicting NBA basketball outcomes. The model accounts for home-court advantage and instances when teams play back-to-back games. The framework includes a model component that addresses team-specific heteroscedasticity. The results of the modeling approach are demonstrated on NBA game outcomes from 2006–2014 and compared to the betting market’s point spreads.

Finally, “Is There a Pythagorean Theorem for Winning in Tennis?” by Stephanie Kovalchik investigates the appropriateness of Bill James’ “Pythagorean theorem” in baseball for measuring tennis win frequency. The paper investigates the application of the Pythagorean theorem to 27 candidate measures of tennis performance based on results from competitive tennis from 2004–2014. The paper also investigates the Pythagorean theorem applied simultaneously to all measures by developing a logit-linear regression model in which the transformed candidate measures are the predictors. The author finds that converted break points has the best relationship with future winning frequency within the Pythagorean theorem framework.

These articles are available to all members of the Section on Statistics in Sports and on a subscription basis from the JQAS website. Also, prospective authors can find the journal’s aims and scope, as well as manuscript submission instructions, on the website.

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