Abstract We present a mathematical modeling framework for roster construction of a Major League Soccer (MLS) expansion team. The model seeks to construct the best squad feasible under league salary rules, while balancing present value, potential value, and future cap flexibility. Player acquisition decisions, as well as allocation of salary, targeted allocation money (TAM), general allocation money (GAM), and designated player slots, are determined simultaneously by a mixed-integer programming model. We demonstrate the model’s functionality in constructing a hypothetical expansion roster and propose a number of extensions.
{"title":"A roster construction decision tool for MLS expansion teams","authors":"Zachary J. Smith, J. Bickel","doi":"10.1515/jqas-2021-0041","DOIUrl":"https://doi.org/10.1515/jqas-2021-0041","url":null,"abstract":"Abstract We present a mathematical modeling framework for roster construction of a Major League Soccer (MLS) expansion team. The model seeks to construct the best squad feasible under league salary rules, while balancing present value, potential value, and future cap flexibility. Player acquisition decisions, as well as allocation of salary, targeted allocation money (TAM), general allocation money (GAM), and designated player slots, are determined simultaneously by a mixed-integer programming model. We demonstrate the model’s functionality in constructing a hypothetical expansion roster and propose a number of extensions.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87977853","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}
Abstract The ATP finals is the concluding tournament of the tennis season since its initiation over 50 years ago. It features the 8 best players of that year and is often considered to be the most prestigious event in the sport other than the 4 grand slams. Unlike any other professional tennis tournament, it includes a round-robin stage where all players in a group compete against each other, making it a unique testbed for examining performance under forgiving conditions, where losing does not immediately result in elimination. Analysis of the distribution of final group standings in the ATP Finals for singles from 1972 to 2021 reveals a surprising pattern, where one of the possible and seemingly likely outcomes almost never materializes. The present study uses a model-free, optimization approach to account for this distinctive phenomenon by calculating what match winning probabilities between players in a group can lead to the observed distribution. Results show that the only way to explain the empirical findings is through a “paradoxical” balance of power where the best player in a group shows a vulnerability against the weakest player. We discuss the possible mechanisms underlying this result and their implications for match prediction, bettors, and tournament organization.
{"title":"A peculiar phenomenon and its potential explanation in the ATP tennis tour finals for singles","authors":"Itamar Lerner","doi":"10.1515/jqas-2022-0043","DOIUrl":"https://doi.org/10.1515/jqas-2022-0043","url":null,"abstract":"Abstract The ATP finals is the concluding tournament of the tennis season since its initiation over 50 years ago. It features the 8 best players of that year and is often considered to be the most prestigious event in the sport other than the 4 grand slams. Unlike any other professional tennis tournament, it includes a round-robin stage where all players in a group compete against each other, making it a unique testbed for examining performance under forgiving conditions, where losing does not immediately result in elimination. Analysis of the distribution of final group standings in the ATP Finals for singles from 1972 to 2021 reveals a surprising pattern, where one of the possible and seemingly likely outcomes almost never materializes. The present study uses a model-free, optimization approach to account for this distinctive phenomenon by calculating what match winning probabilities between players in a group can lead to the observed distribution. Results show that the only way to explain the empirical findings is through a “paradoxical” balance of power where the best player in a group shows a vulnerability against the weakest player. We discuss the possible mechanisms underlying this result and their implications for match prediction, bettors, and tournament organization.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72385703","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}
Abstract This paper examines how the Kelly criterion, a strategy for maximizing the expected log-growth of capital through informed betting, can be applied to non-mutually exclusive bets. These are bets where there is no one-to-one correspondence between the bets and the possible outcomes of the game. This type of situation is common in horse racing, where multiple types of bets are available for a single race. The paper begins by providing a theoretical overview of the Kelly betting strategy and then discusses how it can be extended to non-mutually exclusive bets. A new formulation of the fractional Kelly strategy, which involves betting a fixed fraction of the amount suggested by the Kelly criterion, is also presented for this type of scenario.
{"title":"Kelly criterion and fractional Kelly strategy for non-mutually exclusive bets","authors":"Benjamin P. Jacot, Paul V. Mochkovitch","doi":"10.1515/jqas-2020-0122","DOIUrl":"https://doi.org/10.1515/jqas-2020-0122","url":null,"abstract":"Abstract This paper examines how the Kelly criterion, a strategy for maximizing the expected log-growth of capital through informed betting, can be applied to non-mutually exclusive bets. These are bets where there is no one-to-one correspondence between the bets and the possible outcomes of the game. This type of situation is common in horse racing, where multiple types of bets are available for a single race. The paper begins by providing a theoretical overview of the Kelly betting strategy and then discusses how it can be extended to non-mutually exclusive bets. A new formulation of the fractional Kelly strategy, which involves betting a fixed fraction of the amount suggested by the Kelly criterion, is also presented for this type of scenario.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75650977","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}
Abstract The existence (or not) of the hot hand in sport continues to attract the attention of economists and psychologists. The paper presents analysis to test the belief prevalent in golfing circles that golfers go in and out of form quickly, while ‘class’ remains relatively constant. By going in and out of form, the golfer is effectively experiencing a longer-run hot hand: one can speculate that periods of confidence breed good performance. To test for the existence of ‘form’, we present a new application of the Ornstein–Uhlenbeck model and use it to identify both a golfer’s class and form when modelling golf scores. The findings suggest that short-term form does exist in golf and that this hot hand lasts for about four weeks.
{"title":"‘Form is temporary, class is permanent’: identifying a longer-term hot hand in golf","authors":"R. Baker, Ian G. McHale","doi":"10.1515/jqas-2022-0051","DOIUrl":"https://doi.org/10.1515/jqas-2022-0051","url":null,"abstract":"Abstract The existence (or not) of the hot hand in sport continues to attract the attention of economists and psychologists. The paper presents analysis to test the belief prevalent in golfing circles that golfers go in and out of form quickly, while ‘class’ remains relatively constant. By going in and out of form, the golfer is effectively experiencing a longer-run hot hand: one can speculate that periods of confidence breed good performance. To test for the existence of ‘form’, we present a new application of the Ornstein–Uhlenbeck model and use it to identify both a golfer’s class and form when modelling golf scores. The findings suggest that short-term form does exist in golf and that this hot hand lasts for about four weeks.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86453532","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}
Abstract Statistical analysis in competitive sport is an important tool for developing strategy and seeking competitive advantages. However, for complex team sports such as Australian Rules Football, major limitations occur when using possession event data for game analysis. First, focusing on counting possession events does not capture the impact of off-the-ball actions such as ground positioning of other players. Second, it is difficult to determine the extent that an event is due to either team’s relative proficiency or skill. Third, there is limited possession event data available from each match and modelling efforts often have low statistical power. Here we reinterpret event data into positional systems and utilise pairwise performance metrics to understand the relative team proficiency in each of these states. These metrics can then be used to construct transition probabilities between states for future games, and ultimately, absorbing probabilities of goal states. Our approach effectively predicts match outcomes using team ratings for forward, midfield and defensive systems and is sufficiently interpretable to support strategic decision-making by coaching departments in the Australian Football League (AFL).
{"title":"Modelling Australian Rules Football as spatial systems with pairwise comparisons","authors":"Anton Andreacchio, N. Bean, Lewis Mitchell","doi":"10.1515/jqas-2021-0035","DOIUrl":"https://doi.org/10.1515/jqas-2021-0035","url":null,"abstract":"Abstract Statistical analysis in competitive sport is an important tool for developing strategy and seeking competitive advantages. However, for complex team sports such as Australian Rules Football, major limitations occur when using possession event data for game analysis. First, focusing on counting possession events does not capture the impact of off-the-ball actions such as ground positioning of other players. Second, it is difficult to determine the extent that an event is due to either team’s relative proficiency or skill. Third, there is limited possession event data available from each match and modelling efforts often have low statistical power. Here we reinterpret event data into positional systems and utilise pairwise performance metrics to understand the relative team proficiency in each of these states. These metrics can then be used to construct transition probabilities between states for future games, and ultimately, absorbing probabilities of goal states. Our approach effectively predicts match outcomes using team ratings for forward, midfield and defensive systems and is sufficiently interpretable to support strategic decision-making by coaching departments in the Australian Football League (AFL).","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72969644","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}
Abstract The availability of large databases of athletic performances offers the opportunity to understand age-related performance progression and to benchmark individual performance against the World’s best. We build a flexible Bayesian model of individual performance progression whilst allowing for confounders, such as atmospheric conditions, and can be fitted using Markov chain Monte Carlo. We show how the model can be used to understand performance progression and the age of peak performance in both individuals and the population. We apply the model to both women and men in 100 m sprinting and weightlifting. In both disciplines, we find that age-related performance is skewed, that the average population performance trajectories of women and men are quite different, and that age of peak performance is substantially different between women and men. We also find that there is substantial variability in individual performance trajectories and the age of peak performance.
{"title":"Bayesian modelling of elite sporting performance with large databases","authors":"J. Griffin, Laurentiu C. Hinoveanu, J. Hopker","doi":"10.1515/jqas-2021-0112","DOIUrl":"https://doi.org/10.1515/jqas-2021-0112","url":null,"abstract":"Abstract The availability of large databases of athletic performances offers the opportunity to understand age-related performance progression and to benchmark individual performance against the World’s best. We build a flexible Bayesian model of individual performance progression whilst allowing for confounders, such as atmospheric conditions, and can be fitted using Markov chain Monte Carlo. We show how the model can be used to understand performance progression and the age of peak performance in both individuals and the population. We apply the model to both women and men in 100 m sprinting and weightlifting. In both disciplines, we find that age-related performance is skewed, that the average population performance trajectories of women and men are quite different, and that age of peak performance is substantially different between women and men. We also find that there is substantial variability in individual performance trajectories and the age of peak performance.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72628696","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 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.
{"title":"Jumping on the bandwagon? Attendance response to recent victories in the NBA","authors":"Ercio Munoz, Jiadi Chen, Milan Thomas","doi":"10.1515/jqas-2020-0092","DOIUrl":"https://doi.org/10.1515/jqas-2020-0092","url":null,"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":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138518606","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}
Abstract As a baseball game progresses, batters appear to perform better the more times they face a particular pitcher. The apparent drop-off in pitcher performance from one time through the order to the next, known as the Time Through the Order Penalty (TTOP), is often attributed to within-game batter learning. Although the TTOP has largely been accepted within baseball and influences many managers’ in-game decision making, we argue that existing approaches of estimating the size of the TTOP cannot disentangle continuous evolution in pitcher performance over the course of the game from discontinuities between successive times through the order. Using a Bayesian multinomial regression model, we find that, after adjusting for confounders like batter and pitcher quality, handedness, and home field advantage, there is little evidence of strong discontinuity in pitcher performance between times through the order. Our analysis suggests that the start of the third time through the order should not be viewed as a special cutoff point in deciding whether to pull a starting pitcher.
随着棒球比赛的进行，击球手面对特定投手的次数越多，表现就越好。投手表现从一次到下一次的明显下降，被称为“时间到顺序惩罚”(time through The order Penalty，简称TTOP)，通常归因于游戏中的击球手学习。尽管TTOP在很大程度上已被棒球界所接受，并影响了许多经理人在比赛中的决策，但我们认为，现有的估计TTOP大小的方法无法将投手在比赛过程中表现的连续演变与连续时间之间的不连续性区分开来。使用贝叶斯多项式回归模型，我们发现，在调整了诸如击球手和投手素质，手性和主场优势等混杂因素后，投手表现在不同时间之间通过顺序几乎没有很强的不连续性的证据。我们的分析表明，在决定是否拉先发投手时，第三次开始不应被视为一个特殊的截止点。
{"title":"A Bayesian analysis of the time through the order penalty in baseball","authors":"Ryan S. Brill, Sameer K. Deshpande, A. Wyner","doi":"10.1515/jqas-2022-0116","DOIUrl":"https://doi.org/10.1515/jqas-2022-0116","url":null,"abstract":"Abstract As a baseball game progresses, batters appear to perform better the more times they face a particular pitcher. The apparent drop-off in pitcher performance from one time through the order to the next, known as the Time Through the Order Penalty (TTOP), is often attributed to within-game batter learning. Although the TTOP has largely been accepted within baseball and influences many managers’ in-game decision making, we argue that existing approaches of estimating the size of the TTOP cannot disentangle continuous evolution in pitcher performance over the course of the game from discontinuities between successive times through the order. Using a Bayesian multinomial regression model, we find that, after adjusting for confounders like batter and pitcher quality, handedness, and home field advantage, there is little evidence of strong discontinuity in pitcher performance between times through the order. Our analysis suggests that the start of the third time through the order should not be viewed as a special cutoff point in deciding whether to pull a starting pitcher.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81663623","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}
Abstract The FIFA Women’s World Cup tournament consists of a group stage and a knockout stage. We identify several issues that create competitive imbalance in the group stage. We use match data from all Women’s World Cup tournaments from 1991 through 2019 to empirically assess competitive imbalance across groups in each World Cup. Using least squares, we determine ratings for all teams. For each team, we average the ratings of the opponents in the group to calculate group opponents rating. We find that the range in group opponents rating varies between 2.5 and 4.5 goals indicating substantial competitive imbalance. We use logistic regression to quantify the impact of imbalance on the probability of success in the Women’s World Cup. Specifically, our estimates show that one goal less in group opponents rating can increase the probability of reaching the quarterfinal by 33%. We discuss several policy recommendations to reduce competitive imbalance at the Women’s World Cup.
{"title":"Quantifying the impact of imbalanced groups in FIFA Women’s World Cup tournaments 1991–2019","authors":"Michael A. Lapré, Elizabeth M. Palazzolo","doi":"10.1515/jqas-2021-0052","DOIUrl":"https://doi.org/10.1515/jqas-2021-0052","url":null,"abstract":"Abstract The FIFA Women’s World Cup tournament consists of a group stage and a knockout stage. We identify several issues that create competitive imbalance in the group stage. We use match data from all Women’s World Cup tournaments from 1991 through 2019 to empirically assess competitive imbalance across groups in each World Cup. Using least squares, we determine ratings for all teams. For each team, we average the ratings of the opponents in the group to calculate group opponents rating. We find that the range in group opponents rating varies between 2.5 and 4.5 goals indicating substantial competitive imbalance. We use logistic regression to quantify the impact of imbalance on the probability of success in the Women’s World Cup. Specifically, our estimates show that one goal less in group opponents rating can increase the probability of reaching the quarterfinal by 33%. We discuss several policy recommendations to reduce competitive imbalance at the Women’s World Cup.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88487746","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}
Abstract Competitive balance in a football league is extremely important from the perspective of economic growth of the industry. Many researchers have earlier proposed different measures of competitive balance, which are primarily adapted from standard economic theory. However, these measures fail to capture the finer nuances of the game. In this work, we discuss a new framework which is more suitable for a football league. First, we present a mathematical proof of a theoretically optimal situation where a football league becomes perfectly balanced. Next, a goal based index for competitive balance is developed. We present relevant theoretical results and show how the proposed index can be used to formally test for the presence of imbalance. The methods are implemented on the data from the top five European leagues, and it shows that the new approach can be helpful in explaining the changes in the seasonal competitive balance of the leagues. Further, using panel data models, we show that the proposed index is more suitable to analyze the variability in total revenues of the football leagues. We also discuss how the methods can be easily extended to develop other goal-based indices under different modeling assumptions.
{"title":"A goal based index to analyze the competitive balance of a football league","authors":"S. Deb","doi":"10.1515/jqas-2021-0015","DOIUrl":"https://doi.org/10.1515/jqas-2021-0015","url":null,"abstract":"Abstract Competitive balance in a football league is extremely important from the perspective of economic growth of the industry. Many researchers have earlier proposed different measures of competitive balance, which are primarily adapted from standard economic theory. However, these measures fail to capture the finer nuances of the game. In this work, we discuss a new framework which is more suitable for a football league. First, we present a mathematical proof of a theoretically optimal situation where a football league becomes perfectly balanced. Next, a goal based index for competitive balance is developed. We present relevant theoretical results and show how the proposed index can be used to formally test for the presence of imbalance. The methods are implemented on the data from the top five European leagues, and it shows that the new approach can be helpful in explaining the changes in the seasonal competitive balance of the leagues. Further, using panel data models, we show that the proposed index is more suitable to analyze the variability in total revenues of the football leagues. We also discuss how the methods can be easily extended to develop other goal-based indices under different modeling assumptions.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86799945","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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