Proceedings of Mathsport international 2017 conference

Proceedings of MathSport International 2017 Conference, held in the Botanical Garden of the University of Padua, June 26-28, 2017. MathSport International organizes biennial conferences dedicated to all topics where mathematics and sport meet. Topics include: performance measures, optimization of sports performance, statistics and probability models, mathematical and physical models in sports, competitive strategies, statistics and probability match outcome models, optimal tournament design and scheduling, decision support systems, analysis of rules and adjudication, econometrics in sport, analysis of sporting technologies, financial valuation in sport, e-sports (gaming), betting and sports

A truncated mean-parameterised Conway-Maxwell-Poisson model for the analysis of Test match bowlers

A truncated, mean-parameterized Conway-Maxwell-Poisson model is developed to handle under- and overdispersed count data owing to individual heterogeneity. The truncated nature of the data allows for a more direct implementation of the model than is utilized in previous work without too much computational burden. The model is applied to a large dataset of Test match cricket bowlers, where the data are in the form of small counts and range in time from 1877 to the modern day, leading to the inclusion of temporal effects to account for fundamental changes to the sport and society. Rankings of sportsmen and women based on a statistical model are often handicapped by the popularity of inappropriate traditional metrics, which are found to be flawed measures in this instance. Inferences are made using a Bayesian approach by deploying a Markov Chain Monte Carlo algorithm to obtain parameter estimates and to extract the innate ability of individual players. The model offers a good fit and indicates that there is merit in a more sophisticated measure for ranking and assessing Test match bowlers

Ranking International Limited-Overs Cricket Teams using a Weighted, Heteroskedastic Logistic Regression with Beta Distributed Outcomes

A regression-based ranking method is developed and applied to international lin1ited-overs cricket, using a database of matches played between September 1999 and December 2007. The stn1cture employed is a generalised linear model with logistic link function and beta distributed outcomes and is used to estimate team strength parameters which in turn yield ranking scores. The outcome variable for the regression is a newly proposed measure of the margin of victory based on the Duckwo1ih-Lcwis methodology. The model uses Weibull weighting to discount the impact of matches played in the past and incorporates a heteroskedastic structure to account for the potentially skewing effects of uncom1nonly large victories. Finally, the model is flexible enough to allow exan1ination of the effects of other factors such as home ground advantage

The Indian Premier League: What are the factors that determine player value?

This paper examines and tries to estimate the importance of various characteristics that go into attributing specific dollar values to cricketers. The auction process employed in the Indian Premier League enables one to associate players with specific monetary values and this paper uses various performance criteria to assess what the key variables are towards creating a highly valued cricket player. This paper finds that various batting statistics are of significance in addition to the age and nationality of players

Data visualization and toss related analysis of IPL teams and batsmen performances

Sports play a very significant role in the development of the human persona. Getting involved in games like Cricket and other various sports help us to build character, discipline, confidence and physical fitness. Indian Premier League, IPL provides the most successful form of cricket as it gives opportunities to young and talented players to show case their talents on various pitch. Decision-makers are the utmost customers for all fundamentals in the sports analytics framework. Sports analytics has been a smash hit in shaping success for many players and teams in various sports. Sports analytics and data visualization can play a crucial role in selecting the best players for a team. This paper is about the Toss Related analysis and the breadth of data visualization in supporting the decision makers for identifying inherent players for their teams