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edushinka/bookmaker-margin-panel

Bookmaker Margin Panel — daily measured betting margins across 22 leagues and 3 market types A daily panel of measured bookmaker margins (overround/vigorish) across head-to-head, spread and totals markets: one row per day × league × region × market type, aggregated from over 4 million individually recorded odds observations (2.7 million cleaned markets). To our knowledge this is the only openly published bookmaker margin panel. It quantifies the price of sports betting — the… See the full description on the dataset page: https://huggingface.co/datasets/edushinka/bookmaker-margin-panel.

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Dataset Card

Bookmaker Margin Panel — daily measured betting margins across 22 leagues and 3 market types

A daily panel of measured bookmaker margins (overround/vigorish) across head-to-head, spread and totals markets: one row per day × league × region × market type, aggregated from over 4 million individually recorded odds observations (2.7 million cleaned markets).

To our knowledge this is the only openly published bookmaker margin panel. It quantifies the price of sports betting — the amount by which a market's implied probabilities exceed 100% — across operators, sports and time.


Files	Main panel: 3,494 cells (day × league × region × market type × time-to-start) · Props panel: 1,148 cells
Underlying observations	2,002,681 cleaned main markets + 699,733 two-sided player-prop markets
Bookmakers aggregated	52 (not identified individually — see Limitations; exchanges excluded)
Leagues	22 competition keys across 15 sports, including 9 soccer leagues
Market types	head-to-head (2- and 3-way), spread, total
Period	29 June – 2 August 2026, 35 days (collection continues; quarterly updates planned)
Licence	CC BY 4.0

Columns

Column	Meaning
`snap_date`	Observation date (UTC)
`sport`	League/competition key, e.g. `baseball_mlb`, `soccer_epl`
`region`	`au`, `us` or `offshore_intl` — the licensing region of the operators aggregated in the cell
`market_type`	`h2h`, `spread` or `total` (main panel); specific prop market key in the props file
`time_to_start`	Hours from observation to scheduled start, bucketed (under 6h to over 7 days) — main panel
`outcomes`	Number of priced outcomes (2, or 3 for soccer-style h2h with the draw)
`mean_margin_pct`	Mean margin that day: sum of the outcomes' implied probabilities minus 100, in percent
`n_markets`	Number of distinct market observations in the cell (cells with fewer than 10 are excluded)
`n_bookmakers`	Number of distinct operators aggregated in the cell

Method

For every pre-match market observation, all priced outcomes were converted to implied probabilities (1 ÷ decimal odds) and summed; the excess over 100% is the margin. Two-way and three-way markets are kept in separate cells because their margins are not comparable. Excluded: in-play observations, implausible margins (below 0%, or above 20% two-way / 35% three-way — suspended or near-settled prices), and betting exchanges. Full methodology: https://betbetter.world/studies/bookmaker-margins

Headline findings from this panel

—Player props average a 7.93% margin — 66% more than main head-to-head markets (4.77%). To our knowledge this is the first public measurement of prop-market margins (699,733 two-sided prop markets, MLB/NHL/soccer/basketball prop families).
—The market-type price ladder: h2h 4.77% → spreads 4.90% → totals 5.45% → three-way soccer h2h 7.67% → player props 7.93%.
—Margin has a term structure: it peaks 1–3 days before the start (5.23%) and compresses to 4.71% in the final six hours — betting early costs measurably more.
—Australian-licensed bookmakers average 5.25%, US-licensed 4.72%, offshore/international 4.55% — Australians pay roughly 11% more margin than Americans for equivalent bets.
—Individual operators are not identified in these files; operator-level statistics (a 3.16% to 5.78% spread between the cheapest and dearest bookmaker) are published in the accompanying study: https://betbetter.world/studies/bookmaker-margins

Limitations

One month of collection (a longer panel accumulates with each planned update). Individual bookmakers are deliberately not identified in the files: cells aggregate across all operators in a region (n_bookmakers reports how many), so no operator's prices or price patterns are recoverable — the files are irreversible statistics, not a data feed in any form. Head-to-head is the tightest market type bookmakers offer; margins on multis and player props are materially higher, so these figures are a floor for the cost of betting generally. No individual odds, prices or market observations are included — both files are aggregate statistics derived from a licensed feed that does not permit redistribution of the underlying prices.

Licence and citation

CC BY 4.0 — free to use, including commercially, with attribution.

Bet Better (2026). Bookmaker Margin Panel: daily measured betting margins across 22 leagues, three market types and player-prop markets. https://betbetter.world/studies/bookmaker-margins

Maintained by Bet Better, which also publishes a free sports model API and an open AFL dataset.

This dataset contains no odds, no prices and no wagering data — aggregate statistics only. 18+. Most people lose money gambling. If gambling is causing you harm: gamblinghelponline.org.au.