2024-02-07
Understanding randomness in sports betting
Why you can rarely know whether a single bet was the right decision — even after you see the outcome.
Sports Betting & Prediction Markets
The science of betting markets.
I study the statistics and decision theory of sports betting and prediction markets — as a scientist, not a tout. The public conversation is crowded with picks, affiliate rankings, and models marketed as edge. I work the empty seat: the independent voice that says whether a model, a market, or a claim is actually real, and how you would ever know.
My peer-reviewed work formalizes optimal decision-making under uncertainty in betting markets. The throughline: a billion dollars of real money usually out-forecasts a spreadsheet, the closing line is the only honest benchmark, and a single tournament can never validate a probability. I care about calibration and honesty about variance — not selling winners.
Market vs. model
Closing-line value
Optimal staking
Calibration & wisdom of crowds
Positioning
Independent academic — the referee, not a player. No sportsbook affiliations.
I can speak on
- • Prediction markets vs. Wall Street models
- • Why betting markets are hard to beat
- • Forecasting, calibration, and variance
As featured in · CNN Business · June 2026
“Think you know who’s going to win the World Cup? So does Goldman Sachs.”
On Goldman Sachs’s World Cup prediction model, I told CNN it amounts to a “fun exercise” that sits further from reality than the prediction markets — because “the information going into the model is a tiny sliver of all the information in the possession of the millions of people who have bet into prediction markets.” Markets aren’t perfect either; they overreact to injuries and lean toward unlikely outcomes — and ultimately it’s impossible to know who was right.
The takeaway
The market is the benchmark; a published model is the thing being measured. Where Goldman diverged — Spain near double the market, England roughly half — it was betting against a billion-dollar market with no stated justification.
Signature theses
The recurring ideas I bring to every model, market, and claim.
Market beats model
Aggregated, money-backed forecasts price in information no hand-built model can see. The bar isn’t picking the favorite — it’s beating the closing market price.
Closing-line value is the only benchmark
The closing line is the single number that actually predicts outcomes. Beating it consistently is the real evidence of edge; everything else is narrative.
Single-tournament probabilities are unfalsifiable
A “26% to win the World Cup” number can never be validated — the tournament runs once. Many published forecasts are confident about quantities that are, in principle, uncheckable.
De-vig before you compare
Sportsbook odds sum past 100%; near-zero-vig exchanges already read as probabilities. Comparing the two without removing the vig is the most common way analyses go wrong.
Wisdom of crowds, with caveats
Aggregated independent forecasts converge to a robust estimate — but herding and favorite–longshot bias are real. The market is the best available estimate, not the truth.
Calibration over picks
A good forecaster is judged by calibration and honesty about variance, not by a winning week. You usually cannot know from one outcome whether a decision was right.
Foundational work
The peer-reviewed and open-source backbone behind the commentary.
PLOS ONE · 2023
A statistical theory of optimal decision-making in sports betting
A decision-theoretic framework for when a bet is objectively good or bad, independent of whether it wins — and what that implies for staking and evaluation under uncertainty.
In progress
Ongoing research
A follow-up paper on the profit–bias identity in betting markets, and a quantile-regression model for NFL point spreads with full backtesting. Deep-dives will appear here as they’re ready.
Writing
Accessible essays on the statistics of betting. A newsletter is in the works.
2024-12-02
The economics of teaser bets
Testing the “crossing key numbers” conventional wisdom on NFL teaser legs across multiple seasons.
For journalists
I’m a standing resource for stories on betting models, prediction markets, and forecasting — the independent academic angle, not a tipster’s. Quick to respond, comfortable on deadline, and happy to translate the statistics into plain English.