CAMP: A Context-Aware Cricket Players Performance Metric
Muhammad Sohaib Ayub Naimat Ullah Sarwan Ali Imdad Ullah Khan Mian Muhammad Awais Muhammad Asad Khan Safiullah Faizullah
Cricket is the second most popular sport after soccer in terms of viewership.
However, the assessment of individual player performance, a fundamental task in
team sports, is currently primarily based on aggregate performance statistics,
including average runs and wickets taken. We propose Context-Aware Metric of
player Performance, CAMP, to quantify individual players' contributions toward
a cricket match outcome. CAMP employs data mining methods and enables effective
data-driven decision-making for selection and drafting, coaching and training,
team line-ups, and strategy development. CAMP incorporates the exact context of
performance, such as opponents' strengths and specific circumstances of games,
such as pressure situations. We empirically evaluate CAMP on data of
limited-over cricket matches between 2001 and 2019. In every match, a committee
of experts declares one player as the best player, called Man of the M}atch
(MoM). The top two rated players by CAMP match with MoM in 83\% of the 961
games. Thus, the CAMP rating of the best player closely matches that of the
domain experts. By this measure, CAMP significantly outperforms the current
best-known players' contribution measure based on the Duckworth-Lewis-Stern
(DLS) method.