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Journal of Quantitative Analysis in Sports最新文献

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A parametric family of Massey-type methods: inference, prediction, and sensitivity 梅西型方法的参数族:推理、预测和灵敏度
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-07-27 DOI: 10.1515/jqas-2019-0071
E. Bozzo, P. Vidoni, Massimo Franceschet
{"title":"A parametric family of Massey-type methods: inference, prediction, and sensitivity","authors":"E. Bozzo, P. Vidoni, Massimo Franceschet","doi":"10.1515/jqas-2019-0071","DOIUrl":"https://doi.org/10.1515/jqas-2019-0071","url":null,"abstract":"Abstract We study the stability of a time-aware version of the popular Massey method, previously introduced by Franceschet, M., E. Bozzo, and P. Vidoni. 2017. “The Temporalized Massey’s Method.” Journal of Quantitative Analysis in Sports 13: 37–48, for rating teams in sport competitions. To this end, we embed the temporal Massey method in the theory of time-varying averaging algorithms, which are dynamic systems mainly used in control theory for multi-agent coordination. We also introduce a parametric family of Massey-type methods and show that the original and time-aware Massey versions are, in some sense, particular instances of it. Finally, we discuss the key features of this general family of rating procedures, focusing on inferential and predictive issues and on sensitivity to upsets and modifications of the schedule.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"4 1","pages":"255 - 269"},"PeriodicalIF":0.8,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78343712","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
Frontmatter
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-06-25 DOI: 10.1515/jqas-2020-frontmatter2
{"title":"Frontmatter","authors":"","doi":"10.1515/jqas-2020-frontmatter2","DOIUrl":"https://doi.org/10.1515/jqas-2020-frontmatter2","url":null,"abstract":"","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"35 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75262081","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
What will we unlearn next? The implications of Lopez (2020) 接下来我们会忘记什么?洛佩兹的含义(2020)
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-05-29 DOI: 10.1515/jqas-2020-0056
Samuel L. Ventura
{"title":"What will we unlearn next? The implications of Lopez (2020)","authors":"Samuel L. Ventura","doi":"10.1515/jqas-2020-0056","DOIUrl":"https://doi.org/10.1515/jqas-2020-0056","url":null,"abstract":"Lopez (2020) demonstrates clearly how the lack of precise, high-quality data can lead to imprecise results or analyses. In particular, this paper shows that once you know the precise distance to the first down line (“yards to go”) rather than just the integer-valued distances provided in the NFL’s play-by-play data, the decisions made by coaches are more closely in line with what we would expect from rational, data-driven decision-makers in their situation. However, from anNFL team’s perspective, it is unclear if player-tracking data was necessary to help individual coaches in this particular case. Could NFL teams and coaches make approximately the same decisions from a model trained on only play-by-play data, but evaluated in real-time with more precise inputs for yards to go? Fourth-down decisions are typically analyzed with expected points models and/or win probability models (Romer 2006). When making fourth-down decisions, analysts contend that NFL teams should input their current game situation into one of these models (including information such as the down, distance, yard line, score differential, time remaining, etc), and analyze the output. If the model’s computed win probability for a given situation is maximized by “going for it,” the coach should leave the offense on the field; if win probability is maximized by punting, the coach should elect to punt; and if it is maximized by attempting a field goal, the coach should put his field goal unit on the field. Yurko, Horowitz andVentura (2019) provide a detailed explanation of how to build expected points and win probability models, but briefly, the expected points model is a linear model (specifically, a multinomial logistic regression model), and the win probability model is a generalized additive model. Importantly, although only integer-valueddistances (“yards to go”) areprovided in the","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"149 ","pages":"81 - 83"},"PeriodicalIF":0.8,"publicationDate":"2020-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jqas-2020-0056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72419915","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
Distributed lag models to identify the cumulative effects of training and recovery in athletes using multivariate ordinal wellness data 使用多元有序健康数据的分布滞后模型来识别运动员训练和恢复的累积效应
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-05-18 DOI: 10.1515/jqas-2020-0051
Erin M. Schliep, Toryn L. J. Schafer, Matt J. Hawkey
{"title":"Distributed lag models to identify the cumulative effects of training and recovery in athletes using multivariate ordinal wellness data","authors":"Erin M. Schliep, Toryn L. J. Schafer, Matt J. Hawkey","doi":"10.1515/jqas-2020-0051","DOIUrl":"https://doi.org/10.1515/jqas-2020-0051","url":null,"abstract":"Abstract Subjective wellness data can provide important information on the well-being of athletes and be used to maximize player performance and detect and prevent against injury. Wellness data, which are often ordinal and multivariate, include metrics relating to the physical, mental, and emotional status of the athlete. Training and recovery can have significant short- and long-term effects on athlete wellness, and these effects can vary across individual. We develop a joint multivariate latent factor model for ordinal response data to investigate the effects of training and recovery on athlete wellness. We use a latent factor distributed lag model to capture the cumulative effects of training and recovery through time. Current efforts using subjective wellness data have averaged over these metrics to create a univariate summary of wellness, however this approach can mask important information in the data. Our multivariate model leverages each ordinal variable and can be used to identify the relative importance of each in monitoring athlete wellness. The model is applied to professional referee daily wellness, training, and recovery data collected across two Major League Soccer seasons.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"85 2 1","pages":"241 - 254"},"PeriodicalIF":0.8,"publicationDate":"2020-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89955979","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
Profiting from overreaction in soccer betting odds 从足球博彩赔率的过度反应中获利
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-05-04 DOI: 10.1515/jqas-2019-0009
E. Wheatcroft
{"title":"Profiting from overreaction in soccer betting odds","authors":"E. Wheatcroft","doi":"10.1515/jqas-2019-0009","DOIUrl":"https://doi.org/10.1515/jqas-2019-0009","url":null,"abstract":"Abstract Betting odds are generally considered to represent accurate reflections of the underlying probabilities for the outcomes of sporting events. There are, however, known to be a number of inherent biases such as the favorite-longshot bias in which outsiders are generally priced with poorer value odds than favorites. Using data from European soccer matches, this paper demonstrates the existence of another bias in which the match odds overreact to favorable and unfavorable runs of results. A statistic is defined, called the Combined Odds Distribution (COD) statistic, which measures the performance of a team relative to expectations given their odds over previous matches. Teams that overperform expectations tend to have a high COD statistic and those that underperform tend to have a low COD statistic. Using data from twenty different leagues over twelve seasons, it is shown that teams with a low COD statistic tend to be assigned more generous odds by bookmakers. This can be exploited and a sustained and robust profit can be made. It is suggested that the bias in the odds can be explained in the context of the “hot hand fallacy”, in which gamblers overestimate variation in the ability of each team over time.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"139 1","pages":"193 - 209"},"PeriodicalIF":0.8,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78433311","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: 2
Understanding draws in Elo rating algorithm 理解借鉴了Elo评级算法
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-05-04 DOI: 10.1515/jqas-2019-0102
L. Szczecinski, Aymen Djebbi
{"title":"Understanding draws in Elo rating algorithm","authors":"L. Szczecinski, Aymen Djebbi","doi":"10.1515/jqas-2019-0102","DOIUrl":"https://doi.org/10.1515/jqas-2019-0102","url":null,"abstract":"Abstract This work is concerned with the interpretation of the results produced by the well known Elo algorithm applied in various sport ratings. The interpretation consists in defining the probabilities of the game outcomes conditioned on the ratings of the players and should be based on the probabilistic rating-outcome model. Such a model is known in the binary games (win/loss), allowing us to interpret the rating results in terms of the win/loss probability. On the other hand, the model for the ternary outcomes (win/loss/draw) has not been yet shown even if the Elo algorithm has been used in ternary games from the very moment it was devised. Using the draw model proposed by Davidson in 1970, we derive a new Elo-Davidson algorithm, and show that the Elo algorithm is its particular instance. The parameters of the Elo-Davidson are then related to the frequency of draws which indicates that the Elo algorithm silently assumes games with 50% of draws. To remove this assumption, often unrealistic, the Elo-Davidson algorithm should be used as it improves the fit to the data. The behaviour of the algorithms is illustrated using the results from English Premier League.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"50 1","pages":"211 - 220"},"PeriodicalIF":0.8,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75284690","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: 13
Jumping on the bandwagon? Attendance response to recent victories in the NBA 赶时髦?上座率对最近NBA胜利的反应
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-04-24 DOI: 10.17632/H9RX475N8J.2
Ercio Muñoz, Jiadi Chen, Milan Thomas
{"title":"Jumping on the bandwagon? Attendance response to recent victories in the NBA","authors":"Ercio Muñoz, Jiadi Chen, Milan Thomas","doi":"10.17632/H9RX475N8J.2","DOIUrl":"https://doi.org/10.17632/H9RX475N8J.2","url":null,"abstract":"Abstract This article studies whether a recent victory impacts attendance at sports events. We apply a regression discontinuity design to estimate the local average treatment effect of a win on the attendance of subsequent games in professional basketball. Using National Basketball Association data from seasons 1980–81 to 2017–18, we find that home team fan bases react to recent outcomes, with an increase in attendance of approximately 425 attendants (a 3% boost) following a close win relative to a close loss. The increment is approximately one-eighth of a recent estimate of the superstar effect. We do not find an attendance effect when the visiting team has a recent victory, which provides evidence against the existence of externalities. The positive fan base response to narrow home wins relative to narrow losses suggests that recent luck is rewarded in sporting attendance. We discuss possible mechanisms and document a gradual decline in the attendance response that coincides with the rise of alternative means for viewing games and secondary markets for tickets.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"31 1","pages":"161 - 170"},"PeriodicalIF":0.8,"publicationDate":"2020-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72828314","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: 2
Frontmatter
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-03-26 DOI: 10.1515/jqas-2020-frontmatter1
{"title":"Frontmatter","authors":"","doi":"10.1515/jqas-2020-frontmatter1","DOIUrl":"https://doi.org/10.1515/jqas-2020-frontmatter1","url":null,"abstract":"","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"108 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2020-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87580312","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 Variance Gamma model for Rugby Union matches 橄榄球联盟比赛的方差伽玛模型
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-03-24 DOI: 10.1515/jqas-2019-0088
J. Fry, Oliver Smart, Jean-Philippe Serbera, B. Klar
{"title":"A Variance Gamma model for Rugby Union matches","authors":"J. Fry, Oliver Smart, Jean-Philippe Serbera, B. Klar","doi":"10.1515/jqas-2019-0088","DOIUrl":"https://doi.org/10.1515/jqas-2019-0088","url":null,"abstract":"Abstract Amid much recent interest we discuss a Variance Gamma model for Rugby Union matches (applications to other sports are possible). Our model emerges as a special case of the recently introduced Gamma Difference distribution though there is a rich history of applied work using the Variance Gamma distribution – particularly in finance. Restricting to this special case adds analytical tractability and computational ease. Our three-dimensional model extends classical two-dimensional Poisson models for soccer. Analytical results are obtained for match outcomes, total score and the awarding of bonus points. Model calibration is demonstrated using historical results, bookmakers’ data and tournament simulations.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"93 1","pages":"67 - 75"},"PeriodicalIF":0.8,"publicationDate":"2020-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88403908","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: 2
Template matching route classification 模板匹配路由分类
IF 0.8
Journal of Quantitative Analysis in Sports Pub Date : 2020-03-11 DOI: 10.1515/jqas-2019-0051
Mitch Kinney
{"title":"Template matching route classification","authors":"Mitch Kinney","doi":"10.1515/jqas-2019-0051","DOIUrl":"https://doi.org/10.1515/jqas-2019-0051","url":null,"abstract":"Abstract This paper details a route classification method for American football using a template matching scheme that is quick and does not require manual labeling. Pre-defined routes from a standard receiver route tree are aligned closely with game routes in order to determine the closest match. Based on a test game with manually labeled routes, the method achieves moderate success with an overall accuracy of 72% of the 232 routes labeled correctly.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"103 1","pages":"133 - 142"},"PeriodicalIF":0.8,"publicationDate":"2020-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73051430","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: 2
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