Introduction. In cricket, the evaluation of individual player performance has been based on measures such as batting and bowling averages. These statistics are used to quantify the batting and bowling performance of cricketers, but there are no statistics for measuring the performance of fielders. This paper introduces a measure that can be used to assess the fielding performance of cricketers. Method. Various factors that are considered important in fielding are quantified to scores based on the ball-by-ball information of a match for each cricketer. The fielding points of each ball are then combined to calculate the total fielding points of a cricketer in a given match. All the fielding points are then added in order to obtain total fielding points of a cricketer up to a given match. Average fielding points are obtained by dividing the total fielding score by the number of matches played. Data. To demonstrate these measures, the first ODI match of India against Zimbabwe played on 11th June, 2016, is examined. Conclusion. The recommended measures can be used to quantify the fielding performances of cricketers for a series of matches, whether it is ODI or Twenty20 cricket. They make it possible to assess the average fielding performance of each player. Individual fielding performance scores can then be aggregated to measure the overall fielding performance of a team.
Cricket is the second most watched sport in the world after soccer, and enjoys a multi-million dollar industry.There is remarkable interest in simulating cricket and more importantly in predicting the outcome of cricket match which is played in three formats namely test match, one day international and T20 match. The complex rules prevailing in the game, along with the various natural parameters affecting the outcome of a cricket match present significant challenges for accurate prediction. Several diverse parameters, including but not limited to cricketing skills and performances, match venues and even weather conditions can significantly affect the outcome of a game. There are number of research paper on pre-match prediction of cricket match. Many papers on building a prediction model that takes in historical match data as well as the instantaneous state of a match, and predict match results. We know in the cricket match with shorter version match result keep on changing every ball. So, it is important to predict the outcome of the match on every ball. In this paper, I have developed a model that predicts match result on every ball played. Using Duckworth-Lewis formula match outcome will be predicted for live match. For every ball bowled a probability is calculated and probability figure is plotted. For betting industry this model and the probability figure will be very useful for bettor in deciding which team to on and how much to bet.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.