Journal of Quantitative Analysis in Sports最新文献

Improving the aggregation and evaluation of NBA mock drafts 改进 NBA 模拟选秀的汇总和评估

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Journal of Quantitative Analysis in Sports Pub Date : 2024-08-22 DOI: 10.1515/jqas-2023-0100

Jared D. Fisher, Colin Montague

{"title":"Improving the aggregation and evaluation of NBA mock drafts","authors":"Jared D. Fisher, Colin Montague","doi":"10.1515/jqas-2023-0100","DOIUrl":"https://doi.org/10.1515/jqas-2023-0100","url":null,"abstract":"If professional teams can accurately predict the order of their league’s draft, they would have a competitive advantage when using or trading their draft picks. Many experts and enthusiasts publish forecasts of the order players are drafted into professional sports leagues, known as mock drafts. Using a novel dataset of mock drafts for the National Basketball Association (NBA), we explore mock drafts’ ability to forecast the actual draft. We analyze authors’ mock draft accuracy over time and ask how we can reasonably aggregate information from multiple authors. For both tasks, mock drafts are usually analyzed as ranked lists, and in this paper, we propose ways to improve on these methods. We propose that rank-biased distance is the appropriate error metric for measuring accuracy of mock drafts as ranked lists. To best combine information from multiple mock drafts into a single consensus mock draft, we also propose a combination method based on the ideas of ranked-choice voting. We show that this method provides improved forecasts over the standard Borda count combination method used for most similar analyses in sports, and that either combination method provides a more accurate forecast across seasons than any single author.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"195 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142185558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A basketball paradox: exploring NBA team defensive efficiency in a positionless game 篮球悖论：探索无位置比赛中 NBA 球队的防守效率

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Journal of Quantitative Analysis in Sports Pub Date : 2024-08-16 DOI: 10.1515/jqas-2024-0010

Charles South

{"title":"A basketball paradox: exploring NBA team defensive efficiency in a positionless game","authors":"Charles South","doi":"10.1515/jqas-2024-0010","DOIUrl":"https://doi.org/10.1515/jqas-2024-0010","url":null,"abstract":"In the last decade, the offensive and defensive philosophies employed by teams in the National Basketball Association (NBA) have changed substantially. As a result, most players can no longer be classified into only one of the five traditional positions (PG, SG, SF, PF, C) and instead spend a percentage of their playing time at multiple positions, making positional data compositional. Further, given the desirability for versatile players, an argument can be made that traditional positions themselves are archaic. Using data from the 2016–17, 2017–18, and 2018–19 seasons, I explore how Bayesian hierarchical models can be used to estimate team defensive strength in three ways. First, only considering players classified by their majority traditional position. Second, by using compositional traditional positional data. Third, using compositional data from modern positions (archetypes) defined by fuzzy k-means clustering. I find that the fuzzy k-means approach leads to a modest improvement in both the root mean squared error and median 95 % posterior predictive interval width for the test data, and, more importantly, identifies 11 modern archetypes that, when combined, are correlated with team win total and adjusted team defensive rating. The modern archetype compositions can be used by stakeholders to better understand team defensive strength.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"25 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142185559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Success factors in national team football: an analysis of the UEFA EURO 2020 国家队足球的成功因素：对 2020 年欧洲杯的分析

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Journal of Quantitative Analysis in Sports Pub Date : 2024-07-20 DOI: 10.1515/jqas-2023-0026

Vincent Renner, Konstantin Görgen, Alexander Woll, Hagen Wäsche, Melanie Schienle

{"title":"Success factors in national team football: an analysis of the UEFA EURO 2020","authors":"Vincent Renner, Konstantin Görgen, Alexander Woll, Hagen Wäsche, Melanie Schienle","doi":"10.1515/jqas-2023-0026","DOIUrl":"https://doi.org/10.1515/jqas-2023-0026","url":null,"abstract":"Identifying success factors in football is of sporting and economic interest. However, research in this field for national teams and their competitions is rare despite the popularity of teams and events. Therefore, we analyze data for the UEFA EURO 2020 and, for comparison purposes, the previous tournament in 2016. To mitigate the challenges of perceived multicollinearity and a small sample size, and to identify the relevant variables, we apply the ‘LASSO Cross-fitted Stability-Selection’ algorithm. This approach involves iterative splitting of data, with variables chosen via a ‘least absolute shrinkage and selection operator’ (LASSO) model (Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. J. Roy. Stat. Soc. B 58: 267–288) on one half of the observations, while coefficients are estimated on the other half. Subsequently, we inspect the frequency of selection and stability of coefficient estimation for each variable over the repeated samples to identify factors as relevant. By that, we are able to differentiate generally valid success factors such as the market value ratio from on-field variables whose importance is tournament-dependent, e.g. the tackles attempted. As the latter is connected to a team’s tactics, we conclude that their observed relevance is correlated to the results of the linked playing style in the specific tournaments. We also show the changing effect of these playing-styles on success across tournaments.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"37 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141737664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An empirical Bayes approach for estimating skill models for professional darts players 估计职业飞镖运动员技能模型的经验贝叶斯方法

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2024-07-13 DOI: 10.1515/jqas-2023-0084

Martin B. Haugh, Chun Wang

引用次数: 0

A comprehensive survey of the home advantage in American football 美式橄榄球主场优势综合调查

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Journal of Quantitative Analysis in Sports Pub Date : 2024-07-09 DOI: 10.1515/jqas-2024-0016

Luke Benz, Thompson Bliss, Michael Lopez

引用次数: 0

Improving NHL draft outcome predictions using scouting reports 利用球探报告改进国家冰球联盟选秀结果预测

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Journal of Quantitative Analysis in Sports Pub Date : 2024-06-26 DOI: 10.1515/jqas-2024-0047

Hubert Luo

引用次数: 0

A generative approach to frame-level multi-competitor races 框架级多人竞赛的生成方法

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Journal of Quantitative Analysis in Sports Pub Date : 2024-05-24 DOI: 10.1515/jqas-2023-0091

Tyrel Stokes, Gurashish Bagga, Kimberly Kroetch, Brendan Kumagai, Liam Welsh

{"title":"A generative approach to frame-level multi-competitor races","authors":"Tyrel Stokes, Gurashish Bagga, Kimberly Kroetch, Brendan Kumagai, Liam Welsh","doi":"10.1515/jqas-2023-0091","DOIUrl":"https://doi.org/10.1515/jqas-2023-0091","url":null,"abstract":"Multi-competitor races often feature complicated within-race strategies that are difficult to capture when training data on race outcome level data. Models which do not account for race-level strategy may suffer from confounded inferences and predictions. We develop a generative model for multi-competitor races which explicitly models race-level effects like drafting and separates strategy from competitor ability. The model allows one to simulate full races from any real or created starting position opening new avenues for attributing value to within-race actions and performing counter-factual analyses. This methodology is sufficiently general to apply to any track based multi-competitor races where both tracking data is available and competitor movement is well described by simultaneous forward and lateral movements. We apply this methodology to one-mile horse races using frame-level tracking data provided by the New York Racing Association (NYRA) and the New York Thoroughbred Horsemen’s Association (NYTHA) for the Big Data Derby 2022 Kaggle Competition. We demonstrate how this model can yield new inferences, such as the estimation of horse-specific speed profiles and examples of posterior predictive counterfactual simulations to answer questions of interest such as starting lane impacts on race outcomes.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"44 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141145809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

No cheering in the background? Individual performance in professional darts during COVID-19 背景中没有欢呼声？COVID-19 期间职业飞镖的个人表现

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Journal of Quantitative Analysis in Sports Pub Date : 2024-04-15 DOI: 10.1515/jqas-2022-0036

Finn Spilker, Marius Ötting

引用次数: 0

Career path clustering of elite soccer players among European Big-5 nations utilizing Dynamic Time Warping 利用动态时间扭曲对欧洲五大联赛国家精英足球运动员的职业道路进行分类

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Journal of Quantitative Analysis in Sports Pub Date : 2024-04-04 DOI: 10.1515/jqas-2023-0080

Viktor Wolf, Ralf Lanwehr, Marcel Bieschke, Daniel Leyhr

{"title":"Career path clustering of elite soccer players among European Big-5 nations utilizing Dynamic Time Warping","authors":"Viktor Wolf, Ralf Lanwehr, Marcel Bieschke, Daniel Leyhr","doi":"10.1515/jqas-2023-0080","DOIUrl":"https://doi.org/10.1515/jqas-2023-0080","url":null,"abstract":"Prior clustering approaches of soccer players have employed a variety of methods based on various data categories, but none of them have focused on clustering by career paths characterized through a time series analysis of yearly performance quality. Therefore, this study aims to propose a methodology how a career path can be represented as a time series of a player’s seasonal qualities and then be clustered with players that have a similar career path. The underlying data focuses on soccer players from the five largest European soccer nations (Big-5). This allows for the identification of different types of career paths of players and the investigation of significant disparities between career paths among the Big-5 nations. In line with our proposed methodological approach, we identified and interpreted 13 different clusters of player career paths. These range from the cluster with the highest player quality scores to the pattern comprising players with the weakest scores. Further, the detected clusters show significant differences regarding variables of soccer players’ early career phase in adolescence (e.g., age of debut in professional soccer, years spent in a youth academy). The presented approach might represent a first step for stakeholders in soccer to get an objective insight in players’ career by utilizing mainly freely available data sources.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"61 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatial roles in hockey special teams 冰球特别小组的空间作用

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Journal of Quantitative Analysis in Sports Pub Date : 2024-04-04 DOI: 10.1515/jqas-2023-0019

Jonathan Arsenault, Margaret Cunniff, Eric Tulsky, James Richard Forbes

{"title":"Spatial roles in hockey special teams","authors":"Jonathan Arsenault, Margaret Cunniff, Eric Tulsky, James Richard Forbes","doi":"10.1515/jqas-2023-0019","DOIUrl":"https://doi.org/10.1515/jqas-2023-0019","url":null,"abstract":"Special teams (i.e. power play and penalty kill) situations play an outsized role in determining the outcome of ice hockey games. Yet, quantitative methods for characterizing special teams tactics are limited. This work focuses on team structure and player deployment during in-zone special teams possessions. Leveraging player and puck tracking data from the National Hockey League (NHL), a framework is developed for describing player positioning during 5-on-4 power play and 4-on-5 penalty kill possessions. More specifically, player roles are defined directly from the player tracking data using non-negative matrix factorization, and every player is allocated a unique role at every frame of tracking data by solving a linear assignment problem. Team formations naturally arise through the combination of roles occupied in a frame. Roles that vary on a per-frame basis allow for a fine-grained analysis of team structure. This property of the roles-based representation is used to group together similar power play possessions using latent Dirichlet allocation, a topic modelling technique. The concept of assignments, which remain constant over an entire possession, is also introduced. Assignments provide a more stable measure of player positioning, which may be preferable when assessing deployment over longer periods of time.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"45 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0