پیش بینی احتمال پیروزی در کریکت بین المللی یک روز: یک مدل رگرسیون لجستیک پویا  In-play forecasting of win probability in One-Day International cricket: A dynamic logistic regression model

1. Introduction Unlike soccer, American football and tennis, relatively little work has been published on forecasting in cricket. This seems especially strange given that there are known to be huge betting markets for cricket. The work that has been done on forecasting in cricket has largely been concerned with pre-match forecasting. However, in recent times, the growth in the popularity of in-play betting in all sports, where punters place bets during a game (or match), has meant that models that enable forecasts to be made as the game progresses are in high demand. Cricket is a sport that lends itself particularly to in-play betting: unlike soccer, for example, the discrete nature of the game means that bookmakers and punters alike have ample opportunities tobe active in markets during the game, and as such, cricket attracts extremely large in-play betting volumes. For example, the total amount bet during a typical major OneDay International (ODI) involving Pakistan or India is in the order of $1bn (according to a personal communication from a betting industry insider in 2013). In this paper, we present an in-play forecasting model for One-Day International cricket, and use the model to estimate the probability of victory for a team at any moment during a game. Of course, betting is not the only use of a forecasting model. A forecasting model like that presented here could be used for several purposes. Team coaches may use in-play forecasting probabilities to assess the merits of various different strategies or to analyse player and team performances. In addition, the media could use the model to identify key moments in a match and enhance the television coverage further. Previous work in One-day International (ODI) cricket has focussed largely on the problem of resetting targets in limited overs cricket following interruptions to play.