Out to chase, Chris Gayle (51 from 28), Mayank Agarwal (43 from 40) and a late cameo of 27 from 16 from Nicholas Pooran leads them to a five-wicket victory. In the Eliminator clash between CSK and PBKS, a 66-ball 113 from Faf du Plessis and a 34-ball 46 from Ambati Rayudu pushes CSK to 198 in their 20 overs. Although Prithvi Shaw and Marcus Stoinis hit quick-fire cameos: 41 from 42 and 45 from 30 respectively, RCB manages to restrict DC seven short of the target to proceed to the final. What happened in the Playoffs? Qualifier 1: DC vs RCBĪs per the simulator’s result, RCB defeats DC in the first Qualifier after posting 188/6 on the back of Virat Kohli’s 33-ball 66 and Devdutt Padikkal’s 42-ball 63. How did the things stand at the end of the league phase? As per his simulation, the standings are: He mentioned that the rotation of bowlers in the simulation is “such that a player with three overs and an economy of 9 is picked over a player with one over and an economy of just 3” and there are no Super Overs, which means a tied will remain a tie. Jain also mentioned the shortcomings and limitations of his analysis as there were no no-balls or byes. He explains that the model of simulation is not based on machine learning, but it uses statistics to “make the decisions for the batsman” and “uses a randomizer to determine the outcome.” Jain explained in the post that he used ball-by-ball data of the last 5 years of the IPL, created a unique identification for every player and stored that data of each ball they played, the pattern of runs scored such as singles, doubles, fours or sixes etc., against the type of bowlers those runs were scored, their mode of dismissals, and even the similarity for the bowlers. I mainly wanted to share this because there are some really interesting scenarios in the scorecards or some epic batting collapses, also I think RCB fans will like this one,” he wrote on Redditt, informing about his rather interesting initiative.
“I made a Python program to simulate an entire season of the IPL (excluding the playoffs) using past data, predictive analysis, and randomization techniques.