Journal of Quantitative Analysis in Sports最新文献_第9页

Algorithmically deconstructing shot locations as a method for shot quality in hockey 基于算法解构的冰球击球位置分析方法

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-10-10 DOI: 10.1515/jqas-2020-0012

Devan G. Becker, D. Woolford, C. Dean

{"title":"Algorithmically deconstructing shot locations as a method for shot quality in hockey","authors":"Devan G. Becker, D. Woolford, C. Dean","doi":"10.1515/jqas-2020-0012","DOIUrl":"https://doi.org/10.1515/jqas-2020-0012","url":null,"abstract":"Abstract Spatial point processes have been successfully used to model the relative efficiency of shot locations for each player in professional basketball games. Those analyses were possible because each player makes enough baskets to reliably fit a point process model. Goals in hockey are rare enough that a point process cannot be fit to each player’s goal locations, so novel techniques are needed to obtain measures of shot efficiency for each player. A Log-Gaussian Cox Process (LGCP) is used to model all shot locations, including goals, of each NHL player who took at least 500 shots during the 2011–2018 seasons. Each player’s LGCP surface is treated as an image and these images are then used in an unsupervised statistical learning algorithm that decomposes the pictures into a linear combination of spatial basis functions. The coefficients of these basis functions are shown to be a very useful tool to compare players. To incorporate goals, the locations of all shots that resulted in a goal are treated as a “perfect player” and used in the same algorithm (goals are further split into perfect forwards, perfect centres and perfect defence). These perfect players are compared to other players as a measure of shot efficiency. This analysis provides a map of common shooting locations, identifies regions with the most goals relative to the number of shots and demonstrates how each player’s shot location differs from scoring locations.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82534789","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

An iterative Markov rating method 一种迭代马尔可夫评级方法

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-10-05 DOI: 10.1515/jqas-2019-0070

Stephen Devlin, T. Treloar, Molly Creagar, S. Cassels

引用次数: 0

TRAP: a predictive framework for the Assessment of Performance in Trail Running 陷阱:在越野跑性能评估的预测框架

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-09-30 DOI: 10.1515/JQAS-2020-0013

Riccardo Fogliato, N. L. Oliveira, Ronald Yurko

{"title":"TRAP: a predictive framework for the Assessment of Performance in Trail Running","authors":"Riccardo Fogliato, N. L. Oliveira, Ronald Yurko","doi":"10.1515/JQAS-2020-0013","DOIUrl":"https://doi.org/10.1515/JQAS-2020-0013","url":null,"abstract":"Abstract Trail running is an endurance sport in which athletes face severe physical challenges. Due to the growing number of participants, the organization of limited staff, equipment, and medical support in these races now plays a key role. Monitoring runner’s performance is a difficult task that requires knowledge of the terrain and of the runner’s ability. In the past, choices were solely based on the organizers’ experience without reliance on data. However, this approach is neither scalable nor transferable. Instead, we propose a firm statistical methodology to perform this task, both before and during the race. Our proposed framework, Trail Running Assessment of Performance (TRAP), studies (1) the assessment of the runner’s ability to reach the next checkpoint, (2) the prediction of the runner’s expected passage time at the next checkpoint, and (3) corresponding prediction intervals for the passage time. We apply our methodology, using the race history of runners from the International Trail Running Association (ITRA) along with checkpoint and terrain-level information, to the “holy grail” of ultra-trail running, the Ultra-Trail du Mont-Blanc (UTMB) race, demonstrating the predictive power of our methodology.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73494087","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

Measuring competitive balance in sports 衡量体育竞技平衡

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Journal of Quantitative Analysis in Sports Pub Date : 2020-09-29 DOI: 10.1515/jqas-2020-0006

Matthew Doria, B. Nalebuff

{"title":"Measuring competitive balance in sports","authors":"Matthew Doria, B. Nalebuff","doi":"10.1515/jqas-2020-0006","DOIUrl":"https://doi.org/10.1515/jqas-2020-0006","url":null,"abstract":"Abstract In order to make comparisons of competitive balance across sports leagues, we need to take into account how different season lengths influence observed measures of balance. We develop the first measures of competitive balance that are invariant to season length. The most commonly used measure, the ASD/ISD or Noll-Scully ratio, is biased. It artificially inflates the imbalance for leagues with long seasons (e.g., MLB) compared to those with short seasons (e.g., NFL). We provide a general model of competition that leads to unbiased variance estimates. The result is a new ordering across leagues: the NFL goes from having the most balance to being tied for the least, while MLB becomes the sport with the most balance. Our model also provides insight into competitive balance at the game level. We shift attention from team-level to game-level measures as these are more directly related to the predictability of a representative contest. Finally, we measure competitive balance at the season level. We do so by looking at the predictability of the final rankings as seen from the start of the season. Here the NBA stands out for having the most predictable results and hence the lowest full-season competitive balance.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85137780","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: 3

The relative roles of skill and luck within 11 different golfer populations 技术和运气在11个不同高尔夫球手群体中的相对作用

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-09-25 DOI: 10.1515/JQAS-2019-0028

Richard J. Rendleman

引用次数: 3

Modeling time loss from sports-related injuries using random effects models: an illustration using soccer-related injury observations 使用随机效应模型模拟运动相关损伤的时间损失:使用足球相关损伤观察的插图

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-09-25 DOI: 10.1515/JQAS-2019-0030

C. Avinash, DiPietro Loretta, Young Heather, Elmi Angelo

{"title":"Modeling time loss from sports-related injuries using random effects models: an illustration using soccer-related injury observations","authors":"C. Avinash, DiPietro Loretta, Young Heather, Elmi Angelo","doi":"10.1515/JQAS-2019-0030","DOIUrl":"https://doi.org/10.1515/JQAS-2019-0030","url":null,"abstract":"In assessments of sports-related injury severity, time loss (TL) is measured as a count of days lost to injury and analyzed using ordinal cut points. This approach ignores various athlete and event-specific factors that determine the severity of an injury. We present a conceptual framework for modeling this outcome using univariate random effects count or survival regression. Using a sample of US collegiate soccer-related injury observations, we fit random effects Poisson and Weibull Regression models to perform “severity-adjusted” evaluations of TL, and use our models to make inferences regarding the recovery process. Injury site, injury mechanism and injury history emerged as the strongest predictors in our sample. In comparing random and fixed effects models, we noted that the incorporation of the random effect attenuated associations between most observed covariates and TL, and model fit statistics revealed that the random effects models (AICPoisson = 51875.20; AICWeibull-AFT = 51113.00) improved model fit over the fixed effects models (AICPoisson = 160695.20; AICWeibull-AFT = 53179.00). Our analyses serve as a useful starting point for modeling how TL may actually occur when a player is injured, and suggest that random effects or frailty based approaches can help isolate the effect of potential determinants of TL.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82611389","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: 1

The influence of field size, goal size and number of players on the average number of goals scored per game in variants of football and hockey: the Pi-theorem applied to team sports 场地大小、球门大小和球员人数对足球和曲棍球比赛每场平均进球数的影响:pi定理在团队运动中的应用

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-09-21 DOI: 10.1515/JQAS-2020-0009

J. Blondeau

{"title":"The influence of field size, goal size and number of players on the average number of goals scored per game in variants of football and hockey: the Pi-theorem applied to team sports","authors":"J. Blondeau","doi":"10.1515/JQAS-2020-0009","DOIUrl":"https://doi.org/10.1515/JQAS-2020-0009","url":null,"abstract":"Abstract In this paper, we investigate the correlation between the main physical characteristics of eight variants of football and hockey (such as field size, goal size, player velocity, ball velocity, player density, and game duration) and the resulting average numbers of goals scored per game. To do so, the Pi-theorem in physics is extended to sport science and a non-dimensional parameter of interest is defined. It is based on the ratio between the duration of the game and the order of magnitude of the time needed to cross the midfield, which depends on the average velocity of the ball and the players, the player density and the size of the goals. An excellent correlation is found between the proposed parameter and the average number of goals scored per game during recent international competitions. Using the derived correlation, the effect of any modification of the main characteristics of football and hockey (and their variants) on the scoring pace can be assessed. For instance, it can be predicted that decreasing the length of football fields by 20 m would raise the average number of goals scored to 3.6 (±0.6) per game, versus the 2.6 goals scored during the most recent men’s World Cup.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74968437","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: 1

Smart kills and worthless deaths: eSports analytics for League of Legends 聪明的杀戮和毫无价值的死亡:《英雄联盟》电子竞技分析

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-09-21 DOI: 10.1515/jqas-2019-0096

Philip Z. Maymin

{"title":"Smart kills and worthless deaths: eSports analytics for League of Legends","authors":"Philip Z. Maymin","doi":"10.1515/jqas-2019-0096","DOIUrl":"https://doi.org/10.1515/jqas-2019-0096","url":null,"abstract":"Abstract Vast data on eSports should be easily accessible but often is not. League of Legends (LoL) only has rudimentary statistics such as levels, items, gold, and deaths. We present a new way to capture more useful data. We track every champion’s location multiple times every second. We track every ability cast and attack made, all damages caused and avoided, vision, health, mana, and cooldowns. We track continuously, invisibly, remotely, and live. Using a combination of computer vision, dynamic client hooks, machine learning, visualization, logistic regression, large-scale cloud computing, and fast and frugal trees, we generate this new high-frequency data on millions of ranked LoL games, calibrate an in-game win probability model, develop enhanced definitions for standard metrics, introduce dozens more advanced metrics, automate player improvement analysis, and apply a new player-evaluation framework on the basic and advanced stats. How much does an individual contribute to a team’s performance? We find that individual actions conditioned on changes to estimated win probability correlate almost perfectly to team performance: regular kills and deaths do not nearly explain as much as smart kills and worthless deaths. Our approach offers applications for other eSports and traditional sports. All the code is open-sourced.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83284203","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: 19

Swing shift: a mathematical approach to defensive positioning in baseball 挥棒移位:棒球中防守位置的数学方法

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-09-15 DOI: 10.1515/jqas-2020-0027

Elizabeth L. Bouzarth, B. Grannan, John M Harris, A. Hartley, K. Hutson, E. Morton

{"title":"Swing shift: a mathematical approach to defensive positioning in baseball","authors":"Elizabeth L. Bouzarth, B. Grannan, John M Harris, A. Hartley, K. Hutson, E. Morton","doi":"10.1515/jqas-2020-0027","DOIUrl":"https://doi.org/10.1515/jqas-2020-0027","url":null,"abstract":"Abstract Defensive repositioning strategies (shifts) have become more prevalent in Major League Baseball in recent years. In 2018, batters faced some form of the shift in 34% of their plate appearances (Sawchik, Travis. 2019. “Don’t Worry, MLB–Hitters Are Killing The Shift On Their Own.” FiveThirtyEight, January 17, 2019. Also available at fivethirtyeight.com/features/dont-worry-mlb-hitters-are-killing-the-shift-on-their-own/). Most teams use a shift that overloads one side of the infield and adjusts the positioning of the outfield. In this work we describe a mathematical approach to the positioning of players over the entire field of play without the limitations of traditional positions or current methods of shifting. The model uses historical data for individual batters, and it leaves open the possibility of fewer than four infielders. The model also incorporates risk penalties for positioning players too far from areas of the field in which extra-base hits are more likely. This work is meant to serve as a decision-making tool for coaches and managers to best use their defensive assets. Our simulations show that an optimal positioning with three infielders lowered predicted batting average on balls in play (BABIP) by 5.9% for right-handers and by 10.3% for left-handers on average when compared to a standard four-infielder placement of players.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91187229","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: 15

A contextual analysis of crossing the ball in soccer 足球传中球的语境分析

IF 0.8

Journal of Quantitative Analysis in Sports Pub Date : 2020-09-09 DOI: 10.1515/jqas-2020-0060

Lucas Y. Wu, Aaron Danielson, X. J. Hu, T. Swartz

引用次数: 3