Data-Driven Probabilistic S for Batsman Performance Prediction in a Cricket Match

Batsmen are the backbone of any cricket team and their selection is very critical to team’s success. A good batsman not only scores run but also provides stability innings. The most important factor in selecting a ability score runs. It generally accepted notion that future performance can be predicted by observing analyzing past record. This hypothesis based on fact player’s batting average considered indicator performance. We proposed data-driven probabilistic system for prediction game cricket. captures dependencies between runs scored consecutive balls. evaluated using dataset extracted from Cricinfo website. Hidden Markov model (HMM). HMM used generate foresee players’ upcoming performances. first-order chain assumes probability scoring next ball dependent how many he current ball. use approach learn parameters data. matrix made predicts what batter do results show accurately predict