When it comes to IPL, Analytics is the next big thing in cricket

This year’s IPL auctions have been a treat for the Cricket-frenzy.

After all, it is only in the recent years that Indian Cricket lovers have been given the inside-view of what happens behind the scenes in team selections, player training, and match preparation. Big data, artificial intelligence, and analytics have become the deal-breakers in league cricket across the world. IPL is a brilliant example of how data consumption in Indian cricket has come of age.

 

Choice of Players and Team Formation

At the outset, let us start with the following quote by Satish Menon, CEO of Kings XI Punjab, published in a recent Times Now article.

“I think we spent a lot of time working at analytics. We were completely ready for the auctions as a result of the groundwork. If we missed out on one or two players, we made up by matching it accordingly. While initially, we were hoping to get at least 50 percent of players who were on our list, we ended up with 60-70% of the players we wanted. Whether it was Andrew Tye, or R Ashwin, Yuvraj Singh or even Chris Gayle, we are happy with the players we have in our squad. Gayle was not on the list of the core players we wanted, but we bought him towards the end.”

In fact, not just Kings XI Punjab. Many IPL teams have cracked down on data at a granular level to augment their team selection strategy. So what kind of data are we talking about?

The comprehensive player analysis is one of the biggest challenges faced by any team administration. FORMCEPT has used dataset for CricSheet data to analyze player performance by calculating the MVPI or the Most Valuable Player Index, which is a weighted composite score of the following attributes of a player:

Batting Metrics

1. Hard Hitting Ability = (4*Fours + 6*Sixes) / Balls Played by Batsman

2. Finisher = Not Out innings / Total Innings played
3. Fast Scoring Ability = Total Runs / Balls Played by Batsman
4. Consistency = Total Runs/Number of Times Out
5. Running Between Wickets = (Total Runs – (4*Fours + 6*Sixes))/(Total Balls Played – Boundary Balls)

 

Bowling Metrics

1. Economy = Runs Scored / (Number of balls bowled by bowler/6)

2. Wicket Taking Ability = Number of balls bowled / Wickets Taken
3. Consistency = Runs Conceded / Wickets Taken
4. Crucial Wicket Taking Ability = Number of times Four or Five Wickets Taken / Number of Innings Played
5. Short Performance Index = (Wickets Taken – 4* Number of Times Four Wickets Taken – 5* Number of Times Five Wickets Taken) / (Innings Played – Number of Times Four Wickets or Five Wickets Taken)

 

To know more about MVPI analysis based on actual examples of Chris Gayle and Amit Mishra, read FORMCEPT’s blog here.

Check out the Data Analytics course to know more about it – Click here

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