Data before opinion.
Statistical research notes on T20 cricket: methodology, league analysis, and findings from EdgeXI's machine learning models. No punditry. No predictions posted here.
Why sportsbooks limit accounts: what systematic bettors need to know
Bookmakers are risk businesses. They limit accounts that consistently beat their prices. Here is how professional syndicates manage that reality, and what recreational bettors can learn from it.
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IPL 2026 Starts in Five Days. Here Is What to Expect From EdgeXI.
A breakdown of IPL 2025 from the data, what it tells us going into 2026, and how EdgeXI operates during the season.
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Why Strike Rate Isn't Enough: The Case for Runs Per Resource in T20 Analysis
Strike rate is the default T20 batting metric. It is also context-blind. Here is what we use instead.
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The Hot Hand in T20 Cricket: Fallacy or Signal?
Bettors consistently overweight recent form. The data on T20 cricket suggests they should not.
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Understanding our returns: retail sportsbooks vs. exchanges
The ROI figures we publish are calculated on retail sportsbook odds. Here is what that means, why exchange and sharp book returns differ, and how to read our data correctly.
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How EdgeXI's Machine Learning Models Work — and What They Don't Do
Our machine learning models output probability estimates, not predictions. Understanding the difference — and the limits of what any model can do — is central to using EdgeXI's research well.
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Predictive vs. Descriptive: The Statistical Framework Behind Cricket Prediction
Most cricket statistics describe what has already happened. Predictive modelling does something harder — it estimates what will happen next, and the distinction shapes everything about how we build our models.
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AI or Machine Learning? The Distinction Matters in Cricket Prediction
The word 'AI' is used to describe almost everything now. What EdgeXI actually uses is machine learning, and that distinction matters more than it might seem.
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What Nothing Reveals: The Dot Ball as a Predictive Signal
A dot ball scores nothing. But in T20 cricket, the accumulation of dots is one of the cleaner signals available for estimating bowling effectiveness and match-level pressure dynamics.
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Why Cricket Produces Better Prediction Models Than Almost Any Other Sport
The data structure of T20 cricket is unusually well-suited to statistical modelling. Here is why, and what it means for the quality of predictions you can build from it.
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