Journal of Quantitative Analysis in Sports Impact Factor & Information

Publisher: De Gruyter

Current impact factor: 0.00

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Website Journal of Quantitative Analysis in Sports website
Other titles Journal of quantitative analysis in sports
ISSN 1559-0410
OCLC 62324796
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

De Gruyter

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Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: The widespread proliferation of and interest in bracket pools that accompany the National Collegiate Athletic Association Division I Men’s Basketball Tournament have created a need to produce a set of predicted winners for each tournament game by people without expert knowledge of college basketball. Previous research has addressed bracket prediction to some degree, but not nearly on the level of the popular interest in the topic. This paper reviews relevant previous research, and then introduces a rating system for teams using game data from that season prior to the tournament. The ratings from this system are used within a novel, four-predictor probability model to produce sets of bracket predictions for each tournament from 2009 to 2014. This dual-proportion probability model is built around the constraint of two teams with a combined 100% probability of winning a given game. This paper also performs Monte Carlo simulation to investigate whether modifications are necessary from an expected value-based prediction system such as the one introduced in the paper, in order to have the maximum bracket score within a defined group. The findings are that selecting one high-probability “upset” team for one to three late rounds games is likely to outperform other strategies, including one with no modifications to the expected value, as long as the upset choice overlaps a large minority of competing brackets while leaving the bracket some distinguishing characteristics in late rounds.
    Journal of Quantitative Analysis in Sports 03/2015; 11(1). DOI:10.1515/jqas-2014-0047
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    ABSTRACT: Predicting the outcome of a single sporting event is difficult; predicting all of the outcomes for an entire tournament is a monumental challenge. Despite the difficulties, millions of people compete each year to forecast the outcome of the NCAA men’s basketball tournament, which spans 63 games over 3 weeks. Statistical prediction of game outcomes involves a multitude of possible covariates and information sources, large performance variations from game to game, and a scarcity of detailed historical data. In this paper, we present the results of a team of modelers working together to forecast the 2014 NCAA men’s basketball tournament. We present not only the methods and data used, but also several novel ideas for post-processing statistical forecasts and decontaminating data sources. In particular, we highlight the difficulties in using publicly available data and suggest techniques for improving their relevance.
    Journal of Quantitative Analysis in Sports 03/2015; 11(1). DOI:10.1515/jqas-2014-0056
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    ABSTRACT: Recently, the surge of predictive analytics competitions has improved sports predictions by fostering data-driven inference and steering clear of human bias. This article details methods developed for Kaggle’s March Machine Learning Mania competition for the 2014 NCAA tournament. A submission to the competition consists of outcome probabilities for each potential matchup. Most predictive models are based entirely on measures of overall team strength, resulting in the unintended “transitive property.” These models are therefore unable to capture specific matchup tendencies. We introduce our novel nearest-neighbor matchup effects framework, which presents a flexible way to account for team characteristics above and beyond team strength that may influence game outcomes. In particular we develop a general framework that couples a model predicting a point spread with a clustering procedure that borrows strength from games similar to a current matchup. This results in a model capable of issuing predictions controlling for team strength and that capture specific matchup characteristics.
    Journal of Quantitative Analysis in Sports 03/2015; 11(1). DOI:10.1515/jqas-2014-0054
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    Journal of Quantitative Analysis in Sports 03/2015; 11(1):1-3. DOI:10.1515/jqas-2015-0013
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    ABSTRACT: Volleyball coaches are frequently forced to address the question of athlete service errors as a part of their overall service strategy. This is usually done in an ad hoc fashion with an arbitrarily selected maximum allowable service error fraction or maximum allowable service error-to-ace ratio. In this article, an analysis of service outcomes leads to a mathematical expression for the point-scoring fraction in terms of service ace fraction, service error fraction, and opponent modified sideout fraction. These parameters are assumed to be monotonic functions of an athlete or team’s serving aggressiveness and a linear model for the service error-to-ace ratio is used to close the point-scoring optimization problem. The model provides estimates of the optimal service error fraction for individual athletes based on their service ace fraction and the opponent modified sideout fraction against the server overall and also when restricted to only serves that led to perfect passes. Case studies of the Bay to Bay 17 Black Boys’ USAV Juniors team and the Brigham Young University Men’s NCAA Division I team are used to demonstrate the application of the model and standard errors for the predicted optimal service error fractions are calculated with bootstrap resampling.
    Journal of Quantitative Analysis in Sports 01/2015; DOI:10.1515/jqas-2014-0087
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    ABSTRACT: In this paper, we describe a procedure for constructing bicycle routes of minimal perceived exertion over a multi-day tour for cyclists of different levels of expertise. Given a cyclist’s origin, destination, selected points of interest she/he wants to visit, and a level of cycling expertise, this procedure generates a multi-day bicycle tour as a collection of successive daily paths that begin and end at overnight accommodations. The objective is to minimize the total perceived exertion. We demonstrate the implementation of this procedure on an example multi-day tour route in California and present the results of a survey designed to evaluate the daily paths constructed. Repeated measures analysis indicated that 108 of the 120 perceived exertion ratings of the routes generated by our method fit the reported perceived exertion levels of 175 avid cyclists who participated in an evaluation survey.
    Journal of Quantitative Analysis in Sports 01/2015; DOI:10.1515/jqas-2014-0071
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    ABSTRACT: We show that a classical model for soccer can also provide competitive results in predicting basketball outcomes. We modify the classical model in two ways in order to capture both the specific behavior of each National collegiate athletic association (NCAA) conference and different strategies of teams and conferences. Through simulated bets on six online betting houses, we show that this extension leads to better predictive performance in terms of profit we make. We compare our estimates with the probabilities predicted by the winner of the recent Kaggle competition on the 2014 NCAA tournament, and conclude that our model tends to provide results that differ more from the implicit probabilities of the betting houses and, therefore, has the potential to provide higher benefits.
    Journal of Quantitative Analysis in Sports 01/2015; DOI:10.1515/jqas-2014-0055
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    ABSTRACT: An absorbing Markov chain was used to model the 2012 PGA Tour Golf Season. Expected number of steps until absorption was used to establish expected scores for different locations (fairway, primary rough, green, etc.) and distances from the hole. Strokes gained analysis was then performed to evaluate the quality of each shot hit by players on the 2012 PGA Tour. Skill rankings were developed, tradeoffs between distance and accuracy were assessed, and player strategy was analyzed for playing par 5s.
    Journal of Quantitative Analysis in Sports 12/2014; 10(4). DOI:10.1515/jqas-2014-0043
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    ABSTRACT: We analyze the 2008 World Fly Fishing Championships data to examine two issues: (I) changes to scoring rules are proposed so that catching bigger fish is no longer a disadvantage; and (II) the relative role of chance versus competitor skill in determining the competition outcomes is investigated. For (I), a new quadratic polynomial formula for the number of points awarded for a fish of a certain length meant that the competitor who caught the biggest fish in one of the rivers was no longer disadvantaged, during the 20-min period it took to land the fish, compared to those anglers who caught many small fish. For (II), it was found that an angler A, who is actually better than angler B, has an approximate probability of 8.5% of having, overall, a worse score than angler B. By increasing the number of fishing sessions from five to seven, the probability of misclassification drops to about 7%. Other topics, such as the advantages of the proposed formula and the various fishing strategies, are also discussed.
    Journal of Quantitative Analysis in Sports 12/2014; 10(4). DOI:10.1515/jqas-2013-0124
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    ABSTRACT: The NHL has realigned its conferences and divisions, and starting with the 2013–2014 season the Eastern Conference features 16 teams and the Western Conference features 14. Yet because there are eight playoff spots available in both conferences, teams in the West have a 57% probability of making the playoffs, compared to just 50% for teams in the East. As a result we should expect that, on average, the last team to make the playoffs in the West will have a worse record than the last playoff team in the East. We call the difference in points earned by the 8th seed in each conference the “conference gap.” The purpose of this paper is to estimate the expected size of the conference gap under the new alignment. Using tens of thousands of simulated seasons, we demonstrate that the conference gap will be, on average, 2.74 points, meaning that Eastern Conference teams hoping to make the playoffs will have to win 1–2 games more than Western Conference playoff-hopefuls. We also show the 9th place team in the Eastern Conference has a better record than the 8th place Western team twice as often as the 9th best Western team has a better record than the East’s 8th best. Our findings inform questions about competitive balance and equity in the NHL.
    Journal of Quantitative Analysis in Sports 09/2014; 10(3). DOI:10.1515/jqas-2013-0125
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    ABSTRACT: Every basketball player takes and makes a unique spatial array of shots. In recent years, technology to measure the coordinates of these constellations has made analysis of them possible, and the possibility exists for distinguishing between different shooters at a level of spatial detail finer than the entire basketball court. This paper addresses the challenge of characterizing and visualizing relative spatial shooting effectiveness in basketball by developing metrics to assess spatial variability in shooting. Several global and local measures are introduced and formal tests are proposed to enable the comparison of shooting effectiveness between players, groups of players, or other collections of shots. We propose an empirical Bayesian smoothing rate estimate that uses a novel local spatial neighborhood tailored for basketball shooting. These measures are evaluated using data from the 2011 to 2012 NBA basketball season in three distinct ways. First we contrast nonspatial and spatial shooting metrics for two players from that season and then extend the comparison to all players attempting at least 250 shots in that season, rating them in terms of shooting effectiveness. Second, we identify players shooting significantly better than the NBA average for their shot constellation, and formally compare shooting effectiveness of different players. Third, we demonstrate an approach to map spatial shooting effectiveness. In general, we conclude that these measures are relatively straightforward to calculate with the right input data, and they provide distinctive and useful information about relative shooting ability in basketball. We expect that spatially explicit basketball metrics will be useful additions to the sports analysis toolbox.
    Journal of Quantitative Analysis in Sports 09/2014; 10(3). DOI:10.1515/jqas-2013-0094
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    ABSTRACT: Yearly, the top National Collegiate Athletic Association (NCAA), Division I, men’s basketball teams compete for the national championship, in what is commonly referred to as “March Madness.” Teams are eligible for the tournament when they either win their conference tournament or are invited by a NCAA selection committee. Various factors influence the committee’s decision. Of primary importance is the perceived strength of a team; however, the possible measures used to assess a team’s strength can vary widely. These metrics are of particular interest for teams on the borderline or “on the bubble” of tournament inclusion. Using historical data, we assess which metrics play the most substantial roles in predicting tournament inclusion. Additionally, we determine guidelines for constructing a team’s schedule that are based on these metrics to enhance the chance of being selected for the tournament.
    Journal of Quantitative Analysis in Sports 09/2014; 10(3). DOI:10.1515/jqas-2013-0080
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    ABSTRACT: This paper models the TV audience for NFL games in a market without a local team. The model is estimated using all NFL games shown in the Salt Lake City market over the last 10 years. Team popularity varies season to season, with fans preferring high-scoring close games between good teams. The primary motivation of the model was to advise the local station in week-to-week selection of high TV audience games from the slate of FOX games. In 2013 the most popular team was the San Francisco 49ers and the local station broadcast more of their games than any other team. While the predictions offer modest discrimination between popular games, the predicted error precision must be reduced to compete with local station expertise. Reviewing the prediction performance in 2013 reveals insight into strengths and weaknesses of predictive analytics in business decisions.
    Journal of Quantitative Analysis in Sports 09/2014; 10(3). DOI:10.1515/jqas-2014-0015
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    ABSTRACT: Modeling and prediction of ice hockey match results are not as widely examined areas as modeling and prediction of association football match results. It is assumed that match results in football and ice hockey can be modeled by the bivariate Poisson distribution or by some modification of this distribution. The aim of this paper is to explore the possibility of using models derived for football match results also for ice hockey match results and to propose some modifications of these models. A new model based on alternative definition of the bivariate Poisson distribution is presented. The models are tested on historical data from the highest-level ice hockey league in the Czech Republic between the years 1999 and 2012.
    Journal of Quantitative Analysis in Sports 09/2014; 10(3). DOI:10.1515/jqas-2013-0129