Abstract:
"
Cricket is a sport where teams of less than a dozen players compete against each other
in the form of a match. Players in each team can be categorized based on their role in
the field. Despite eleven players being on the field, an additional four players are added
to the squad so that players can be swapped out in case of injuries or less than stellar
form. These fifteen players in the squad are selected from a pool of players. The process
involved in manual, involving selectors, coaching staff and the Captain. Due to the
process being manual, several factors can affect the selection process such as personal
biases and political influences which turns the process into subjective judgement
instead of an objective judgement. This can result in better teams being snubbed of their
opportunities in succeeding due to less than stellar players being selected. This process
requires the elimination of personal judgement and a shift into a more objective process.
Thus, the author proposes a solution for T20 Squad Selection by using Machine
Learning Models to recommend squads from pools of players. Previous two years of
performance, previous year performance in Premiere Leagues such as IPL, PSL, BPL,
LPL, BBL and CPL, Performance in Domestic circuits and Under 19 performance are
considered for each player to ensure that youngsters and well-experienced players
aren’t disadvantaged in these processes."
