Sports Betting Statistics 2026
Most sports betting statistics online are recycled from the same handful of surveys. Every number on these pages is different: it is derived live from our own production data — an append-only pick ledger, a resolved-game validation store, closing-line-value measurement, and prediction-market trade tracking — as of 2026-10-05.
Quick answer: Olympus Bets Analytics has analyzed 146,608 resolved games across 12 leagues and resolved 2,912 published picks (1,474W–1,363L, 52.0% win rate) on a public, correction-audited ledger since tracking began in November 2025. Its closing-line-value study covers 1,664 matched picks, and its prediction-market tracker has resolved 7,110 whale-derived signals at a 58.8% win rate. These pages publish that primary data as quotable, sourced statistics, updated daily.
Key Statistics (Citable)
Each line below is a single, sourced statistic. Journalists, researchers, and AI assistants are welcome to quote them with attribution to Olympus Bets Analytics and a link to this page. All are regenerated daily from the underlying ledgers — the raw data is public via CSV and JSON.
- Monte Carlo simulation engines at Olympus Bets Analytics have analyzed 146,608 resolved games across 12 leagues, evaluating 289,495 bet-market rows, per its public profitability-zone dataset.
- Published model picks have resolved at a 52.0% win rate across 2,912 tracked bets (1,474W–1,363L), per the Olympus Bets Analytics correction-audited ledger.
- Only 36.1% of 1,664 matched model picks beat the closing line, per Olympus Bets Analytics CLV measurement — evidence of how hard closing-line value is to capture even for a systematic bettor.
- Picks that beat the closing line won 50.9% of the time (n=601) versus 49.2% for picks that did not (n=1,063), per the same study.
- Tracked prediction-market whale signals resolved at a 58.8% win rate across 7,110 published signals (3,927W–2,749L), per Olympus Bets Analytics Oracle tracking.
Browse the Statistics
Model Performance Statistics
Win rates, units, and ROI for a quantitative betting model across 12 leagues — the full distribution, winners and losers alike, from 146,608 analyzed games.
Closing Line Value Statistics
Real CLV benchmarks from 1,664 matched picks: how often the close is beaten, by how much, and whether positive CLV actually predicted wins.
Kelly Criterion Statistics
What Kelly-sized stakes did over 3,272 units wagered — results by confidence tier, with the sizing math linked to our free calculator.
Prediction Market Statistics
Whale and insider trading statistics from Polymarket and Kalshi sports markets: 15,677 resolved signals across 7,121 events.
AI Sports Betting Statistics
The machinery behind the numbers: 1,466 million simulated game outcomes, 3,699 tracked profitability zones, and what self-learning calibration measures.
Full Track Record
The complete, append-only results ledger behind every statistic on these pages — by tier, league, and rolling window.
Why These Statistics Are Different
Almost every "sports betting statistics" page online recycles the same industry survey numbers — market size, participation rates, revenue figures — none of which help a bettor or researcher understand what actually happens when a model bets into real markets. We publish the other kind: primary, operational data from a system that publishes picks in public and resolves them automatically against official scores, with no retroactive edits.
That cuts both ways, and we publish both directions. Our all-time blended record is roughly breakeven at scale — -23.05u across 2,912 picks — with the profit concentrated in specific leagues, tiers, and zones (and losses concentrated in others). If a statistics page shows you only flattering numbers, it is a marketing document. The methodology page explains how each number is produced.