Journal of Quantitative Analysis in Sports (J Quant Anal Sports )

Publisher: Berkeley Electronic Press


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    Journal of Quantitative Analysis in Sports website
  • Other titles
    Journal of quantitative analysis in sports
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    Document, Periodical, Internet resource
  • Document type
    Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Berkeley Electronic Press

  • Pre-print
    • Author can archive a pre-print version
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    • Author can archive a post-print version
  • Conditions
    • On non-commercial authors personal website, non-commercial authors open-access university and employers institutional repository and non-commercial authors course website
    • PubMed and Europe PMC after 12 months (automatic for several journals)
    • Publisher copyright and source must be acknowledged
    • Publisher's version/PDF may be used
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Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Multiple models are discussed for ranking teams in a league and introduce a new model called the Oracle method. This is a Markovian method that can be customized to incorporate multiple team traits into its ranking. Using a foresight prediction of NFL game outcomes for the 2002–2013 seasons, it is shown that the Oracle method correctly picked 64.1% of the games under consideration, which is higher than any of the methods compared, including ESPN Power Rankings, Massey, Colley, and PageRank.
    Journal of Quantitative Analysis in Sports 06/2014; 10(2):183-196.
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    ABSTRACT: This paper proposes a multiple-membership generalized linear mixed model for ranking college football teams using only their win/loss records. The model results in an intractable, high-dimensional integral due to the random effects structure and nonlinear link function. We use recent data sets to explore the effect of the choice of integral approximation and other modeling assumptions on the rankings. Varying the modeling assumptions sometimes leads to changes in the team rankings that could affect bowl assignments.
    Journal of Quantitative Analysis in Sports 03/2014; 8(3).
  • [Show abstract] [Hide abstract]
    ABSTRACT: The standard metric for American football field goal kickers is simply the percentage of attempts successfully converted. Due to variance in distance of attempts and other conditions (weather, altitude, defense, etc.), we argue that field goal percentage is an insufficient measure of kicker performance. Using three seasons of NFL data, we construct a multivariate logistic regression model for the success probability of a given attempt. This leads naturally to metrics in which a kicker’s performance is compared to model expectations, if a replacement-level player was attempting the same kicks. Player salaries correlate only weakly with our measures of field goal kicking success. We find that those kickers selected to the Pro Bowl and All-Pro teams were rather mediocre by our metrics, over the seasons studied. The relative difficulty of kicking in various stadiums is also considered. Finally, we discuss the degree to which field goal kicking is a skill that can be maintained over multiple seasons.
    Journal of Quantitative Analysis in Sports 02/2014; 10(1):49-66.
  • [Show abstract] [Hide abstract]
    ABSTRACT: We consider the modeling of individual batting performance in one-day international (ODI) cricket by using a batsman-specific hidden Markov model (HMM). The batsman-specific number of hidden states allows us to account for the heterogeneous dynamics found in batting performance. Parallel sampling is used to choose the optimal number of hidden states. Using the batsman-specific HMM, we then introduce measures of performance to assess individual players via reliability analysis. By classifying states as either up or down, we compute the availability, reliability, failure rate and mean time to failure for each batsman. By choosing an appropriate classification of states, an overall prediction of batting performance of a batsman can be made. The classification of states can also be modified according to the type of game under consideration. One advantage of this batsman-specific HMM is that it does not require the consideration of unforeseen factors. This is important since cricket has gone through several rule changes in recent years that have further induced unforeseen dynamic factors to the game. We showcase the approach using data from 20 different batsmen having different underlying dynamics and representing different countries.
    Journal of Quantitative Analysis in Sports 01/2014;
  • Journal of Quantitative Analysis in Sports 01/2014;
  • Journal of Quantitative Analysis in Sports 01/2014; 10(3).
  • Journal of Quantitative Analysis in Sports 01/2014; 10(2).
  • David J. Irons, Stephen Buckley, Tim Paulden
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    ABSTRACT: Sports ranking systems are often viewed as inadequate for judging the quality of the teams or players involved. Meanwhile, statistical models have been shown to produce more accurate ratings for those competitors, based on their ability to forecast future results. However, whilst predictive power is a desirable property of any official ranking system, these systems must also be fair, transparent and insensitive to bias. Additional requirements may also be required, such as promoting major tournaments and deciding seedings. By considering rankings for ATP tennis players, we propose that statistical models can be used to improve the existing ranking system, in such a way that the resulting rankings are fair and usable by the governing body. In many cases, there is a trade-off between predictive power and other desirable properties, and so compromise is required to produce a system that can be implemented successfully.
    Journal of Quantitative Analysis in Sports 01/2014; 10(2).
  • Journal of Quantitative Analysis in Sports 01/2014; 10:37-48.
  • Journal of Quantitative Analysis in Sports 01/2014; 10(2).
  • Journal of Quantitative Analysis in Sports 01/2014; 10(2).
  • Journal of Quantitative Analysis in Sports 01/2014; 10(2).
  • Scott D. Grimshaw, Scott J. Burwell
    Journal of Quantitative Analysis in Sports 01/2014; 10(3).
  • James Graham, John Mayberry
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    ABSTRACT: We present a notational analysis of offensive tactics commonly employed in elite men’s water polo and address three questions related to this objective: which tactics are most effective?, which tactical performance indicators best classify the winning team?, and how accurate are predictive models based on these performance indicators? We define a new statistic, Efficiency Rating, which quantifies the importance of a tactic via a weighted average of direct and indirect goals generated by its use. By this measure, direct shot is the most efficient even strategy despite being employed far less frequently than centre or perimeter tactics. We address our second question by measuring the effect size of winning over losing teams for 25 tactical variables and find that exclusion conversion rate is the most effective discriminatory statistic in both close and unbalanced games, correctly classifying almost 90% of all contests. To address our third question, we develop and apply a simple Binomial model based on goals generated per play which correctly predicts all eight games in the medal round of the 2012 Men’s Olympics from preliminary rounds. Success probabilities are computed based on a weighted average of offensive and defensive efficiency with an optimal weight that favors defense.
    Journal of Quantitative Analysis in Sports 01/2014; 10(1).
  • [Show abstract] [Hide abstract]
    ABSTRACT: The UEFA Champions League Round of 16 is characterized by restrictions that prevent teams from the same preliminary group and the same nations from matches against each other. Together with the draw procedure currently employed by UEFA, this leads to odd probabilities: in 2012/2013, there were more outcomes of the draw with German Schalke 04 facing Ukrainian Shakhtar Donetsk than there were results where they were matched with Galatasaray Istanbul. In contrast, the probability of Schalke being drawn against Galatasaray exceeded that of playing Shakhtar. We show that this strange effect is due to the group restriction and the mechanism used by UEFA for the draw. Additionally, we provide procedures with which UEFA could produce adequate probabilities for the draw.
    Journal of Quantitative Analysis in Sports 08/2013; 9(3):249-270.
  • [Show abstract] [Hide abstract]
    ABSTRACT: The desire to promote healthier and more environmentally conscious methods of commuting has generated increased interest in professional and recreational bicycling in recent years. One of the most important factors cyclists consider when riding is the amount of exertion they will perceive on a given path. In this paper, we build and test a model of the perceived exertion of different categories of cyclists on a daily path within a long bicycle tour. We first propose an additive formula for calculating the perceived exertion of cyclists on component parts of a tour and then present the results of a survey designed to verify the accuracy of the model. Distance, elevation gain, average percent grade, maximum percent grade, and cyclists’ level of expertise are shown to be significant predictors of perceived exertion (p<0.005). Repeated measures analysis indicated that 109 of the 120 perceived exertion levels produced by our model fit the reported perceived exertion levels of the 242 avid cyclists who participated in the validation survey.
    Journal of Quantitative Analysis in Sports 05/2013; 9(2):203-216.