Bidding smarter at a cricket auction
A decision support tool for cricket player auctions that combines machine learning valuations with game theory, giving a franchise real-time guidance on when to bid and when to walk away.
- Sector
- Sports
- Scope
- Valuation model and live bidding support
- My role
- Builder
The problem
A player auction is a fast, high-stakes market. A franchise has a fixed purse, a squad to complete and rivals bidding against it, often with seconds to decide.
The approach
Value every player
Use machine learning on performance data to estimate each player's value to the team, adjusted for role and conditions.Model the rivals
Apply game theory to estimate how other teams will bid given their purse and squad gaps.Advise live
Update recommendations after every sale so the room knows the walk-away price at each moment.
Who it serves
Team management
A clear ceiling price for every target.Analysts
A model they can update as the auction unfolds.
The outcome
A working tool that treats a squad like a portfolio and the auction like a market.