A Year of Modelling Cricket Player Props - 2024 Review
"A year of cheering on the unders, or so I thought..."
Introduction
The end of the Men’s Big Bash in Jan 2025 bought to a close a year (13 months) of gambling on cricket player props, and to be more precise a year of modelling these markets with the aim of finding positive value (+EV) bets.
The markets in question are/were:
· Player Match Runs
· Player Match 6’s
· Player Match 4’s
· Player Match Wickets
· Player Performance Points
All bets generated were in T20 franchise matches across the major leagues. The year-round schedule, large player/ground datasets, wide bookmaker coverage and long-term future in this format made it an obvious place to target.
Overview
Below is a basic breakdown of results via T20 tournament showing the number of games priced (covered), overall profit/loss and a return on investment (ROI). Note here this includes every bet that has been calculated as + expected value (+EV) no matter how small or big an edge.
Staking System/ Min +EV
The graph below shows the profit and loss throughout the year. The blue line is a flat staking system for every bet with a greater than 10% calculated edge (+EV). The red line shows the results with the “Tyche staking” system, this is a basic staking system as explained below:
< 7.5% Edge = No Bet
7.5-10% - 0.5 Unit Bet
10-15% - 1 Unit
>15% - 1.5 Units
The edge/+EV is a simple subtraction of the % represented from the bookmakers odds from the percentage of the calculated model odds.
With an overlap of bets both sets of data are naturally correlated. The Tyche Staking system returned 11.45 units more profit, but at a lower ROI due to the increased number of bets. Below is the above graph in table form for a more detailed comparison.
Market Analysis
The below table is a comparison of the two staking strategies across the the five player markets that are modelled. As expected the >10% staking plan returns a greater ROI across all the markets apart from interestingly player performance points.
The table below was a major surprise. While most profitable punters believe there's more value in betting on Unders—due to bookmakers adjusting odds to account for the average punter's preference for action—the data shows otherwise. Contrary to my belief that Unders were the main profit source, the >10% EV strategy actually yielded higher profits and a significantly better return from betting Overs.
Statistical Analysis - P-Value
The P-value is a statistical measure that estimates the likelihood that a betting record’s results are due to chance, or alternatively, the probability that they reflect actual skill.
For high levels of confidence, we should only really be interested in betting history analysis when the P-Value is less than 0.05. Note the P-Value calculation estimates probability based from a level stakes betting record, so the above number is the result of the >10% EV betting record.
With a P-value of 0.006, there is strong statistical evidence that the results are not due to chance. This corresponds to roughly a 1 in 161 likelihood that such a performance would occur randomly, or alternatively a a 99.40% chance that the results are determined by skill.
Summary
In summary, the Tyche Model had a strong first year, delivering 54 units profit at just under 10% ROI using the >10% EV strategy, supported by a robust P-value. The main area for improvement is increasing game coverage—something that can likely be addressed through automation.
If you're interested in using the model for cricket betting, I run a premium group where selections are posted for every tournament match. Feel free to reach out here or on Twitter.
The system is still evolving, so any questions, feedback or suggestions are always welcome. Thank you very reading (especially considering you will have made it all the way down here).
Charlie.