| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: Bookmaker Margin Panel |
| size_categories: |
| - 1K<n<10K |
| task_categories: |
| - tabular-regression |
| - tabular-classification |
| tags: |
| - sports-betting |
| - bookmaker-margin |
| - overround |
| - gambling-economics |
| - panel-data |
| - tabular |
| configs: |
| - config_name: default |
| data_files: |
| - betbetter_margin_panel.csv |
| - betbetter_prop_margin_panel.csv |
| --- |
| |
| # 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](https://betbetter.world), which also publishes a |
| [free sports model API](https://betbetter.world/api/) and an |
| [open AFL dataset](https://doi.org/10.5281/zenodo.21612783). |
| |
| > 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. |
| |