This paper presents a framework for evaluating the financial consequences of player transfers as seen from a club’s perspective. To this end, an objective player rating model is designed based on players’ contribution towards creating a positive goals differential for their team. A regression model is then applied to predict match outcomes as a function of the players involved in a match. Finally, Monte Carlo simulation is used to predict the final league standings and the financial gains obtained as a function of sporting success. The framework is illustrated on player transfers from the 2014-2015 English Premier League season.
{"title":"Modelling the financial contribution of soccer players to their clubs","authors":"Olav Drivenes Sæbø, L. M. Hvattum","doi":"10.3233/JSA-170235","DOIUrl":"https://doi.org/10.3233/JSA-170235","url":null,"abstract":"This paper presents a framework for evaluating the financial consequences of player transfers as seen from a club’s perspective. To this end, an objective player rating model is designed based on players’ contribution towards creating a positive goals differential for their team. A regression model is then applied to predict match outcomes as a function of the players involved in a match. Finally, Monte Carlo simulation is used to predict the final league standings and the financial gains obtained as a function of sporting success. The framework is illustrated on player transfers from the 2014-2015 English Premier League season.","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-170235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124242","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}
{"title":"Factors influencing scoring in the NBA Slam Dunk Contest","authors":"J. Barber, Evan S. Rollins","doi":"10.3233/JSA-190242","DOIUrl":"https://doi.org/10.3233/JSA-190242","url":null,"abstract":"","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"9 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-190242","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124551","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}
During the 2017–18 season, the National Basketball Association (NBA) began a three-year pilot program to allow corporate sponsors’ logo patches on game jerseys. Considering this, there is little evidence on how international and domestic NBA fans would respond to this new initiative. Accordingly, we conducted an online experiment to investigate the effects of market-, team-, manufacturer-, and individual-related factors on fans’ perceptions toward various potential NBA jersey sponsors. We developed 180 fictitious press releases that informed participants about their favorite team coming to terms on a sponsorship deal with a specific corporation. This resulted in the creation of 360 graphic renderings of sponsored NBA team jerseys as research stimuli. We utilized a crowdsourcing platform to collect the data (N = 621). Overall, our findings provide useful and actionable insights for managers to understand what may impact fans’ reactions to the NBA’s new pilot sponsorship program.
{"title":"Fans’ responses to the National Basketball Association’s (NBA) pilot jersey sponsorship program: An experimental approach","authors":"D. Kwak, S. Pradhan","doi":"10.3233/JSA-180250","DOIUrl":"https://doi.org/10.3233/JSA-180250","url":null,"abstract":"During the 2017–18 season, the National Basketball Association (NBA) began a three-year pilot program to allow corporate sponsors’ logo patches on game jerseys. Considering this, there is little evidence on how international and domestic NBA fans would respond to this new initiative. Accordingly, we conducted an online experiment to investigate the effects of market-, team-, manufacturer-, and individual-related factors on fans’ perceptions toward various potential NBA jersey sponsors. We developed 180 fictitious press releases that informed participants about their favorite team coming to terms on a sponsorship deal with a specific corporation. This resulted in the creation of 360 graphic renderings of sponsored NBA team jerseys as research stimuli. We utilized a crowdsourcing platform to collect the data (N = 621). Overall, our findings provide useful and actionable insights for managers to understand what may impact fans’ reactions to the NBA’s new pilot sponsorship program.","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-180250","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124169","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}
{"title":"What was lost? A causal estimate of fourth down behavior in the National Football League","authors":"D. Yam, Michael J. Lopez","doi":"10.3233/JSA-190294","DOIUrl":"https://doi.org/10.3233/JSA-190294","url":null,"abstract":"","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-190294","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124733","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}
This study establishes the k index to measure the level of dynamic competitive balance (CB) in a sports league. It also introduces the concept of memory span in measuring dynamic CB. The k index reflects the contemporaneous level of dynamic CB at each season in the history of a league as equivalent to that of a league where k teams have equal chances of winning the title. All seasons of selected European and South American domestic soccer leagues, continental soccer cups, and those of the NBA were analyzed with respect to their k index. 5
{"title":"A metric to measure dynamic competitive balance with respect to prize concentration","authors":"F. D’Ottaviano","doi":"10.3233/JSA-180323","DOIUrl":"https://doi.org/10.3233/JSA-180323","url":null,"abstract":"This study establishes the k index to measure the level of dynamic competitive balance (CB) in a sports league. It also introduces the concept of memory span in measuring dynamic CB. The k index reflects the contemporaneous level of dynamic CB at each season in the history of a league as equivalent to that of a league where k teams have equal chances of winning the title. All seasons of selected European and South American domestic soccer leagues, continental soccer cups, and those of the NBA were analyzed with respect to their k index. 5","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-180323","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124912","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}
N. D. Pifer, Timothy D. DeSchriver, T. Baker, James J. Zhang
Every March a sample of the top Division I men’s basketball programs in the National Collegiate Athletic Association (NCAA) gather to compete in March Madness, a grueling single elimination tournament that captures the attention of millions of viewers and shines a prominent spotlight on the 68 teams that are competing for college basketball’s national championship. Interspersed amongst the numerous financial incentives that exist for each university, and the millions of dollars that are wagered on brackets and bets, are the suggestions of media members, coaches, and players as to which factors are important to teams in their quest for success. One common suggestion argues that player experience provides a benefit to teams as they attempt to handle the pressure and maintain their composure amidst one of the most hectic postseasons in all of sport. However, there have been few studies conducted to analyze the effects that the two primary categories of player experience (i.e., prior postseason experience and class rank) have on the performances of March Madness teams. Therefore, this study sought to test the validity of the assumption by using a series of empirical models to analyze player performance and experience data from the 693 games that took place during the 2007 to 2017 March Madness tournaments. The findings suggest that simply having a higher class rank than an opponent offers no discernible advantage at any stage of the competition, but that possessing more prior March Madness experience may significantly improve a team’s margin of victory in the later rounds. 8
{"title":"The advantage of experience: Analyzing the effects of player experience on the performances of March Madness Teams","authors":"N. D. Pifer, Timothy D. DeSchriver, T. Baker, James J. Zhang","doi":"10.3233/JSA-180331","DOIUrl":"https://doi.org/10.3233/JSA-180331","url":null,"abstract":"Every March a sample of the top Division I men’s basketball programs in the National Collegiate Athletic Association (NCAA) gather to compete in March Madness, a grueling single elimination tournament that captures the attention of millions of viewers and shines a prominent spotlight on the 68 teams that are competing for college basketball’s national championship. Interspersed amongst the numerous financial incentives that exist for each university, and the millions of dollars that are wagered on brackets and bets, are the suggestions of media members, coaches, and players as to which factors are important to teams in their quest for success. One common suggestion argues that player experience provides a benefit to teams as they attempt to handle the pressure and maintain their composure amidst one of the most hectic postseasons in all of sport. However, there have been few studies conducted to analyze the effects that the two primary categories of player experience (i.e., prior postseason experience and class rank) have on the performances of March Madness teams. Therefore, this study sought to test the validity of the assumption by using a series of empirical models to analyze player performance and experience data from the 693 games that took place during the 2007 to 2017 March Madness tournaments. The findings suggest that simply having a higher class rank than an opponent offers no discernible advantage at any stage of the competition, but that possessing more prior March Madness experience may significantly improve a team’s margin of victory in the later rounds. 8","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-180331","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124532","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}
Using data from 1,199 matches containing 10,933 ends in the Canadian Men’s Curling Championships, we developed both a three-dimensional empirical state space model and three-dimensional homogeneous and heterogeneous Markov models to estimate win probabilities throughout a curling match. The Markovian win probabilities were derived from the observed scoring probabilities using recursive logic. These win probabilities allowed us to answer questions regarding optimal curling strategy. When presented with the choice to score 1 point or blanking an end, we conclude that teams holding the hammer should choose to blank the end in most situations. Looking at empirical results of conceded matches, we conclude that concession behavior is consistent with a psychological win probability threshold of 2.57%. However, we also find that teams frequently concede when their win probability at time of concession is, in fact, much higher than this threshold. This is true particularly after the 9th end, suggesting that teams are conceding matches when they have up to a 15% chance of winning.
{"title":"An analysis of curling using a three-dimensional Markov model","authors":"Paul Brenzel, W. Shock, Harvey Yang","doi":"10.3233/JSA-180279","DOIUrl":"https://doi.org/10.3233/JSA-180279","url":null,"abstract":"Using data from 1,199 matches containing 10,933 ends in the Canadian Men’s Curling Championships, we developed both a three-dimensional empirical state space model and three-dimensional homogeneous and heterogeneous Markov models to estimate win probabilities throughout a curling match. The Markovian win probabilities were derived from the observed scoring probabilities using recursive logic. These win probabilities allowed us to answer questions regarding optimal curling strategy. When presented with the choice to score 1 point or blanking an end, we conclude that teams holding the hammer should choose to blank the end in most situations. Looking at empirical results of conceded matches, we conclude that concession behavior is consistent with a psychological win probability threshold of 2.57%. However, we also find that teams frequently concede when their win probability at time of concession is, in fact, much higher than this threshold. This is true particularly after the 9th end, suggesting that teams are conceding matches when they have up to a 15% chance of winning.","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-180279","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124705","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}
Paragraph 29a of the official ITF Rules of Tennis sets a limit of 20 seconds for the time players can take between points. This study investigates the prevalence of violations of this rule, the corresponding umpire’s behavior and factors that influence the inter-point time in general. Regression analysis of 3475 serves of the 2016 Australian Open Men’s Singles tournament showed an autonomous influence on the variance of the inter-point for the serving player, the duration of the previous rally, the service game, the current scoring streak and the importance of the point. The average time between points was 21.5 seconds and time rule violations were found for 58.5% of the serves. Only two (0.1%) of these rule violations were penalized by the umpire, with the punished incidents occurring after 23.5 and 25.6 seconds, representing the 65.9th and the 78.1th percentile respectively of the detected inter-point times. Thus, we concluded that the current rule is not just applied too lax but also capriciously. Based on the detected influences on the time between points we suggest various adaptions of the rule, e.g. a dynamic time limit based on the duration of the previous rally, as well as ways to improve the enforcement of the rule, e.g. technological officiating aids.
{"title":"A closer look at the prevalence of time rule violations and the inter-point time in men’s Grand Slam tennis","authors":"Otto Kolbinger, Simon Großmann, M. Lames","doi":"10.3233/JSA-180277","DOIUrl":"https://doi.org/10.3233/JSA-180277","url":null,"abstract":"Paragraph 29a of the official ITF Rules of Tennis sets a limit of 20 seconds for the time players can take between points. This study investigates the prevalence of violations of this rule, the corresponding umpire’s behavior and factors that influence the inter-point time in general. Regression analysis of 3475 serves of the 2016 Australian Open Men’s Singles tournament showed an autonomous influence on the variance of the inter-point for the serving player, the duration of the previous rally, the service game, the current scoring streak and the importance of the point. The average time between points was 21.5 seconds and time rule violations were found for 58.5% of the serves. Only two (0.1%) of these rule violations were penalized by the umpire, with the punished incidents occurring after 23.5 and 25.6 seconds, representing the 65.9th and the 78.1th percentile respectively of the detected inter-point times. Thus, we concluded that the current rule is not just applied too lax but also capriciously. Based on the detected influences on the time between points we suggest various adaptions of the rule, e.g. a dynamic time limit based on the duration of the previous rally, as well as ways to improve the enforcement of the rule, e.g. technological officiating aids.","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"35 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-180277","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124641","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}
Millions of people play daily fantasy sports in the hopes of winning money. The two largest daily fantasy sports companies, FanDuel® and DraftKings® process billions of dollars in entry fees every year. Recently, daily fantasy sports have landed in a tense political climate and some states have declared these activities as gambling because they are games of chance. If daily fantasy sports are games of chance, then every strategy should perform equally well. A study of FanDuel®’s NFL® contests provides statistically significant evidence that a participant’s fantasy score is not based upon chance. Another study spent $85 to enter 35 DraftKings® MLB Double Up contests with randomly selected teams. All 35 entries lost and the odds of this occurring, if these contests are chance, is 1 in 312,681,518. These odds are less likely than winning the Powerball lottery with a single ticket. Thus, daily fantasy sports are not games of chance, and the authors recommend that these contests should not be considered gambling.
{"title":"Are daily fantasy sports gambling?","authors":"T. Easton, S. Newell","doi":"10.3233/JSA-180240","DOIUrl":"https://doi.org/10.3233/JSA-180240","url":null,"abstract":"Millions of people play daily fantasy sports in the hopes of winning money. The two largest daily fantasy sports companies, FanDuel® and DraftKings® process billions of dollars in entry fees every year. Recently, daily fantasy sports have landed in a tense political climate and some states have declared these activities as gambling because they are games of chance. If daily fantasy sports are games of chance, then every strategy should perform equally well. A study of FanDuel®’s NFL® contests provides statistically significant evidence that a participant’s fantasy score is not based upon chance. Another study spent $85 to enter 35 DraftKings® MLB Double Up contests with randomly selected teams. All 35 entries lost and the odds of this occurring, if these contests are chance, is 1 in 312,681,518. These odds are less likely than winning the Powerball lottery with a single ticket. Thus, daily fantasy sports are not games of chance, and the authors recommend that these contests should not be considered gambling.","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-180240","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124470","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}
Given the high stakes nature of NCAA athletics, it has become increasingly important for coaches to recruit athletes who can compete and make substantive contributions to a team’s success. The purpose of this study was to develop an analytic to predict the time it would take a high school female shot putter to contribute a score at the NCAA Championship meet based on her personal best high school performance. Performance data from high school and college performances were collected from NCAA women’s shot putters, who completed their eligibility from 2012–2017 (N = 63), and graphed to construct a trend line which plotted the top shot put performance of each individual from high school (y) against their best result from each of four or five years in collegiate competition (x). Strong correlations were found between high school and collegiate performance for the first three years of collegiate competition with statistical significance achieved at p < 0.0001. The correlation progressively decreased with each year of collegiate competition with years four and five of collegiate eligibility demonstrating a diminished statistical significance at p < 0.05. Minimum high school performances were calculated in order to produce a statistically significant result that could score for each place at the NCAA meet for a given amount of years competing in NCAA Division I track and field. The results provide track and field coaches with the first analytical model that can assist in determining a high school recruit’s ability to contribute valuable points at the most important competitions. 6
{"title":"A development model to guide the recruiting of female shot putters at the NCAA Division I Championship level","authors":"D. Babbitt","doi":"10.3233/JSA-180275","DOIUrl":"https://doi.org/10.3233/JSA-180275","url":null,"abstract":"Given the high stakes nature of NCAA athletics, it has become increasingly important for coaches to recruit athletes who can compete and make substantive contributions to a team’s success. The purpose of this study was to develop an analytic to predict the time it would take a high school female shot putter to contribute a score at the NCAA Championship meet based on her personal best high school performance. Performance data from high school and college performances were collected from NCAA women’s shot putters, who completed their eligibility from 2012–2017 (N = 63), and graphed to construct a trend line which plotted the top shot put performance of each individual from high school (y) against their best result from each of four or five years in collegiate competition (x). Strong correlations were found between high school and collegiate performance for the first three years of collegiate competition with statistical significance achieved at p < 0.0001. The correlation progressively decreased with each year of collegiate competition with years four and five of collegiate eligibility demonstrating a diminished statistical significance at p < 0.05. Minimum high school performances were calculated in order to produce a statistically significant result that could score for each place at the NCAA meet for a given amount of years competing in NCAA Division I track and field. The results provide track and field coaches with the first analytical model that can assist in determining a high school recruit’s ability to contribute valuable points at the most important competitions. 6","PeriodicalId":53203,"journal":{"name":"Journal of Sports Analytics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JSA-180275","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70124187","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}
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