The June 2015 issue (volume 11, issue 2) of the Journal of Quantitative Analysis in Sports (JQAS) features four articles with applications to baseball, soccer, volleyball, and cycling. The issue showcases a variety of sports applications, as well as a diverse set of statistical and modeling approaches typical of JQAS manuscripts.
“openWAR: An Open Source System for Evaluating Overall Player Performance in Major League Baseball” by Benjamin Baumer, Shane Jensen, and Gregory Matthews is the Editor’s Choice article for this issue and available for free download for 12 months. The article describes an alternative and more principle approach to WAR (wins above replacement), a proprietary measure used for baseball player evaluation. The authors develop the openWAR measure through a model for conservation of runs, which tracks the changes in the number of expected runs scored and actual runs scored resulting from each in-game hitting event. The procedure is demonstrated on recent major league baseball data to measure player performance.
“Multi-Day Bicycle Tour Route Generation” by Katherine Payne and Moshe Dror describes a procedure for constructing bicycle routes based on cyclists’ perceived exertion. The authors propose to construct multi-day bicycle routes by converting potential routes into strongly connected directed graphs representing the topology of the road map. A heuristic is proposed to solve the combinatorial optimization problem for identifying the optimal path based on minimizing perceived exertion. The procedure is demonstrated on an example multi-day tour route in California.
“Prediction of Major International Soccer Tournaments Based on Team-Specific Regularized Poisson Regression: An Application to the FIFA World Cup 2014” by Andreas Groll, Gunther Schauberger, and Gerhard Tutz introduces an approach to inferring soccer team strengths based on penalized Poisson regression. In addition to exploring models with ordinary ridge and Lasso penalties for team covariate effects, the authors consider group Lasso penalties that shrink team-specific attack and defense parameters to zero. The authors demonstrate their approach on predictions in the 2014 FIFA World Cup.
Finally, “A Linear Model for Estimating Optimal Service Error Fraction in Volleyball” by Tristan Burton and Scott Powers examines strategic elements for optimal volleyball serves. The authors build a model of a server’s aggressiveness as a function of the server’s ace probability, error probability, and the probability the opponent wins a point when receiving conditional on the serve being nonterminal. From this model, the authors construct an algorithm to optimize a server’s aggressiveness that would lead to greatest point-scoring potential. The approach is demonstrated on two volleyball data sets.
These articles are available on a subscription basis from the JQAS website. Prospective authors can find the journal’s aims and scope, as well as manuscript submission instructions, there also.
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