TY - GEN
T1 - An analysis of best player selection key performance indicator
T2 - International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015
AU - Khandelwal, Mayank
AU - Prakash, Jayant
AU - Pradhan, Tribikram
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - IPL is the most celebrated T20 cricket festival in the world in which 8 teams give their best to reach the top team in the tournament. In such a contest there are various players from different nationalities playing for different teams. As we know that only a certain amount of players can play one match, so there is a problem for team management to choose the best combination of players for the match. In this paper, we are calculating the Most Valuable Player (MVP) by using a novel approach, decision tree is used to classify the players into various classes. Further, bipartite cover is used for selection of bowlers, variance analysis is used to find the similarity among players. Finally, genetic algorithm is used to select the best playing eleven. After selecting the best players, we are predicting individual strike rates with total team scores. This paper is going to give them a solution to eliminate non performing players using customized method of their performance analysis in earlier matches, assembling a decent playing eleven for any match using revolutionary methods and deciding batting order in an efficient manner.
AB - IPL is the most celebrated T20 cricket festival in the world in which 8 teams give their best to reach the top team in the tournament. In such a contest there are various players from different nationalities playing for different teams. As we know that only a certain amount of players can play one match, so there is a problem for team management to choose the best combination of players for the match. In this paper, we are calculating the Most Valuable Player (MVP) by using a novel approach, decision tree is used to classify the players into various classes. Further, bipartite cover is used for selection of bowlers, variance analysis is used to find the similarity among players. Finally, genetic algorithm is used to select the best playing eleven. After selecting the best players, we are predicting individual strike rates with total team scores. This paper is going to give them a solution to eliminate non performing players using customized method of their performance analysis in earlier matches, assembling a decent playing eleven for any match using revolutionary methods and deciding batting order in an efficient manner.
UR - https://www.scopus.com/pages/publications/84945893575
UR - https://www.scopus.com/inward/citedby.url?scp=84945893575&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-23036-8_16
DO - 10.1007/978-3-319-23036-8_16
M3 - Conference contribution
AN - SCOPUS:84945893575
SN - 9783319230351
VL - 384
T3 - Advances in Intelligent Systems and Computing
SP - 173
EP - 190
BT - Intelligent Systems Technologies and Applications
A2 - Srivastava, Praveen Ranjan
A2 - Berretti, Stefano
A2 - Thampi, Sabu M.
PB - Springer Verlag
Y2 - 10 August 2015 through 13 August 2015
ER -