Enhancing Bowling Strategy with Data Insights

Enhancing Bowling Strategy with Data Insights

Synopsis

Instead of relying only on instinct, I now combine that data with AI tools like ChatGPT to plan my bowling, writes Sumit Mitra
ETtech
By Sumit Mitra

I play in local corporate leagues and bowl spin, and like most players, there are always a few batsmen who are tough to get out. Recently, I started using data from an app called CrickHero, where I can access a player’s match history and performance profile. Instead of relying only on instinct, I now combine that data with AI tools like ChatGPT to plan my bowling.

I take the player’s CrickHero profile link and feed it into AI tools along with context like pitch conditions and ground size. The AI analyses scoring patterns, preferred shots and weaknesses, and gives me a customised plan on how to bowl to that specific player. It suggests lines, lengths and field placements based on real data.
In one match, it suggested bowling outside off stump with a packed off-side field. I tried it, and the batsman mistimed a shot and got out. AI adds a layer of precision that helps me stay one step ahead.

Prompts Used:

Analyse this player’s CrickHero profile and suggest weaknesses against spin

Given a slow pitch, what line and length should I bowl to this batsman

What field setting will restrict his scoring areas

How can I force a mistake against this player in a T20 match

(The author is India CEO, Tesco.)

Disclaimer: This column is for general information and does not constitute advice; readers act on it at their own risk.

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