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Setting Final Target Score in T-20 Cricket Match by the Team Batting First

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Setting Final Target Score in T-20 Cricket Match by the Team Batting First Journal of Sports Analytics 6 (2020) 205–213 205 DOI 10.3233/JSA-200397 IOS Press Setting final target score in T-20 cricket match by the team batting first Durga Prasad Venkata Modekurti Department of Sciences, Indian Institute of Information Technology Design and Manufacturing Kurnool, Kurnool, Andhra Pradesh, India Abstract. The purpose of this paper is to develop a deterministic model for setting the target in T-20 Cricket by the team batting first. Mathematical tools were used in model development. Recursive function and secondary data statistics of T-20 cash rich cricket tournament Indian Premier League (IPL) such as runs scored in different stages, fall wickets in different stages, and type of pitch are used in developing the model. This model was tested at 120 matches held IPL 2016 and 2017. This model had been proved effective by comparing with the models developed earlier. This model can be a useful tool to the stakeholders like coach and captain of the team for adopting better strategy at any stage of the match. For future research, this model can be useful in framing a regulation work by policy makers at both national and international cricket board by deriving the target score during interruptions. Keywords: Deterministic model, mathematical tools, T-20 cricket, target score 1. Introduction factor in deciding the winner of the match. This may be due to the fact that there may exist uncertainty in Cricket is one of the most popular sports in the setting a right target for the team batting second. The world. Mostly this game is played in commonwealth team batting first will try to score as many runs as countries as it is originated in UK. It is a game possible in their 20 overs in order to set a target. The played between two teams of eleven players each. team batting second has an advantage of knowing With the advent of optimal modeling in sports, the exact target and of course their strengths as well setting the target score in T-20 cricket game has been as opposition bowling strengths. They need to chase considered as a challenging problem. The game of the target in order to win the game. For years while cricket is played in three formats – Test Matches, watching limited overs cricket, we have seen pro- ODIs and T20 s. This paper focusses research on T20 jected scores at different intervals being displayed on matches, the most popular format of the game in the television screens. Projected scores are completely recent times by developing a mathematical model based on runs scored and looking at different totals for setting the final target score of an Indian Premier at the end of an innings, using various run rates. Such League (IPL) cricket match for a team batting first. projected scores can also guide the batting/bowling In an IPL tournament there are 8 teams playing and side in changing their tactics in the remaining overs each team play with remaining all teams two times. for winning the match. The Duckworth-Lewis model All league matches are held at one of the team’s (1998) and the Clarke model (2006) bring out the home venue. For certain matches, home pitches may findings that the total score is strongly affected by the not play a bigger role but toss plays as a crucial stage and state of the match, i.e. the wickets and the overs remaining. They recommend their projected ∗Corresponding author: Durga Prasad Venkata Modekurti, scores as the ideal levels that the team should attain Visiting Faculty, Department of Sciences, Indian Institute of in the match for success and winning. Information Technology Design and Manufacturing Kurnool, IPL is a very popular tournament supported by Jagannathagattu Hill, Kurnool 518007, Andhra Pradesh, India. E-mail: [email protected]. Board of control for cricket in India (BCCI). Players ISSN 2215-020X/20/$35.00 © 2020 – IOS Press and the authors. All rights reserved This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC 4.0). 206 D.P.V. Modekurti / Setting final target score in T-20 cricket match participating in the tournament are from India as well dicting match outcomes through multiple regression as from other countries but limited to few players. and used Duckworth–Lewis approach to the gen- eration of runs in case of interruption of the ODI matches. Davis Jack, et al. (2015) developed simula- 2. Related work tor for T20 cricket matches using a probabilities of the batsman, the bowler, the number of overs consumed, In the recent past, many researchers have home team advantage, target score (for second inning applied tools related to mathematics, Statistics and team) and number of wickets fall. operations research in sports viz. (Sphicas, G.P., While Kalgotra Pankuch, et al. (2013) developed et al., 1976), (Croucher, J.S., 1982), (Hayes, M., et al., several predictive models for selection of players for 1984), (Clarke, S.R., 1988), (Duckworth, F.C., et al., Indian Premier League (IPL) based on performances 1998). In the last two research papers it relates to and they have validated it through comparing mis- one day cricket matches where each team will play classification rate for the optimal model, although, maximum 50 overs. Clarke, S.R. (1988) had used this model assist to decision makers during auction optimal scoring rates to define a strategy for the team of players for team to set their salaries, and Satao whereas Duckworth et al. (1998) has been innovated Preeti, et al. (2016) built a system that it could be a formula applicable to interrupted matches. Lat- predicted score of the T20 cricket players by using ter’s work is meant for policy makers of international k-means clustering algorithm. For a different game cricket council to regulate the rules for the game in like basketball, Lutz Dwight (2012) and Cheng Ge, case of interruptions of the game due to weather or et al. (2016) have contributed in developing models. some other external disturbances. Many researchers Sharp et al. (2011) described method of player per- later have extended, reviewed or even modified these formances based on their abilities and then used an works to other form of cricket viz T-20. integer programming to determine the optimal team Munir Fahad, et al. (2015) illustrated forecasting based on player’s performance in twenty20 cricket. system based on the data of previous matches played Passi and Pandey (2018) predicted run scored by bats- between teams to predict results whilst T20 match men and wicket taken by bowlers which were based is in progress. For example a decision can be taken on players stats and characteristics, and obtained high during the match like the right players to send for bat- prediction accuracy using random forest classifier ting or right bowlers go for bowl in middle of game among other classifiers in ODI. When T20 match by using the tools multiple regression and decision results were predicted by Prakash Deep, et al. (2016) tree predictive algorithms. Shah Parag (2017) used whose modeling the individual players’ potential into Duckworth-Lewis method to predict winning team cumulative batting and bowling scores through Deep while match was in progress. Clarke S. R. and Nor- Performance Index (Prakash Deep, 2016). Also, dur- man J. M. (1998) have tried to found out optimal ing the second innings a model gives outcome of policy and value of objective function using simple the match regards to winning at the end of each dynamic programming for the weak batsman with over represented by Viswanatha S. et al. (2017). An aim of maximize number of balls for longer partner- explored that an optimized model based on features ship in the match and gave him strike at the second of team and players for the prediction T20 cricket last or last ball of the over by taking run because better match results and was preeminent outperformed a batsman could score runs to the first ball of new over. gambling industry benchmark (Kampakis Stylianos Ananda B. W. Manage, et al. (2013) analyzed per- and Thomas William, 2015). Modeling hazard func- formance of T20 cricket world cup players based on tion through Bayesian analysis used batsmen career runs, wickets and combinations of it means that con- statistics to make prediction of cricketers who would sidering the attempting innings and throwing overs in have batting abilities of the next opening Test match the tournament. (Stevenson and Brewer, 2017). Also, Sharma (2013) Tim B. Swartz, et al. (2009) developed a simula- and Shah (2017) established that batting capabilities tion methodology and Bayesian latent variable model have been dominated over bowling capabilities of which provide batting outcome probabilities enable T20 cricket using factor analysis. Bhattacharjee, et to determine optimal strategies during innings and al. (2016) proposed method to find effect of power team to easily investigate outcomes from making play overs in T20 match outcomes and identified that changes in order of batting and bowling in the ODI. for better team performance in batting and bowling Bailey, M.J. and Clarke, S.R. (2006) established pre- skills which leads to winning the match. Duckworth D.P.V. Modekurti / Setting final target score in T-20 cricket match 207 and Lewis (1998) introduced a method for setting over a span of 47 days. During the last 10 editions revised fairer target for team batting second in cricket of IPL matches, international T-20 matches between matches that are shortened due to weather interrup- two nations held so far since from inception and T-20 tions through available team resources as such overs world cup matches, it was observed that a challeng- and wickets, given scored from any combination ing question often arises to every coach of the team of these resources to win.
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