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You are here: Home / Additional Features / Journal Highlights / Journal of Quantitative Analysis in Sports Highlights / JQAS Highlights: Baseball, Soccer, American Football, Downhill Skiing in September Issue

JQAS Highlights: Baseball, Soccer, American Football, Downhill Skiing in September Issue

October 1, 2015 Leave a Comment

Mark E. Glickman, JQAS Editor-in-Chief

    The September 2015 issue (volume 11, issue 3) of the Journal of Quantitative Analysis in Sports (JQAS) features five articles with applications to baseball, soccer, American football, and downhill skiing. The issue highlights the breadth and diversity of methodological approaches toward sports applications that has made JQAS the flagship outlet for statistical research applied to sports.

    “The Implied Volatility of a Sports Game” by Nicholas Polson and Hal Stern is the Editor’s Choice article for this issue, and is available for free download 12 months after the issue is published. The article develops a method to assess the time-varying volatility of a within-game point score difference based on the pre-game point spread and the money-line odds, which are continuously updated during the game. The method is demonstrated to assess the volatility at various moments during Super Bowl XLVII, which can lead to improved probability estimates of the final game outcome.

    Mark Glickman and Jonathan Hennessy develop a model for competitors in multi-entry games that acknowledges that competitors’ abilities may be changing over time in “A Stochastic Rank-Ordered Logit Model for Rating Multi-Competitor Games and Sports.” The approach relies on a state-space framework for game outcomes and competitor abilities. The authors describe both a fully Bayesian and approximate Bayesian analysis of their model and apply their approach to the results of women’s Alpine downhill skiing data.

    Jared Cross and Dana Sylvan develop an approach to producing heat maps that accurately estimate baseball batting proficiency as a function of pitch location in “Modeling Spatial Batting Ability Using a Known Covariance Matrix.” Their method models batting success as a function of location through a spatial Gaussian field with an accurate and realistic covariance model to characterize spatial dependence. They demonstrate their approach to the batting patterns of several elite players.

    In “Rethinking the FIFA World Cup Final Draw,” Julien Guyon examines features of the current draw procedure and derives an approach to improve the existing method. In particular, he focuses on developing an approach that improves ability balance in the draw, fairness to the better teams, and uniformity of the draw distribution. He concludes the article with a proposed tractable draw procedure that could be used by FIFA.

    Finally, Lars Magnus Hvattum is concerned with measuring the effect of playing surface on a soccer team’s ability in “Playing on Artificial Turf May Be an Advantage for Norwegian Soccer Teams.” He addresses this question by examining the improvement in home-field advantage by teams that switch from natural grass fields to artificial turf and accounting for team strength through a variation of the Elo rating system. He concludes that artificial turf, on average, increases home-field advantage, though not necessarily the strength of the home team itself.

    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.

    Filed Under: Journal of Quantitative Analysis in Sports Highlights Tagged With: ASA, Journal of Quantitative Analysis in Sports, JQAS

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