Compare Two Sportsbooks on the Same Soccer 1X2 Market (Fair Probabilities)
Main question: How do you compare two sportsbooks on the same 1X2 (Home/Draw/Away) market so you can see who’s cheaper?
Quick answer
Compare books on the probability layer, not the odds-format layer:
convert Home/Draw/Away to implied probabilities, add them to get the implied sum (overround),
then normalize back to 100% to get fair probabilities. Run the same match at both books.
The book with the lower implied sum (tighter overround) is usually the cheaper execution spot.
Fast path (use the tool)
Use Fair Line Finder (3-Way) to normalize a full 1X2 board in seconds.
To measure how “wide” a board is (cost of the menu), use the
Hold / Overround Calculator.
If you’re dealing with a two-outcome market, use Fair Line Finder (2-Way).
What you need (inputs)
- Home/Draw/Away odds from Book A for the exact match and ruleset.
- Home/Draw/Away odds from Book B for the exact same match and ruleset (recommended).
- One choice: compare on implied sum (cost) and/or fair probabilities (true-price split).
Step-by-step: remove the juice (3-way)
- Convert odds → implied probabilities for Home, Draw, Away.
- Add them to get the implied sum (example: 106.4%).
- Normalize: fair probability = implied probability ÷ implied sum (so totals = 100%).
- (Optional) Convert fair probabilities back to odds for display—but compare books using the probabilities.
What to compare (the only three metrics that matter)
- Implied sum / overround: “How expensive is this board?” (lower is better).
- Shading: “Which leg is padded most?” (often the draw on softer books).
- Consistency: “Which book is cheapest most often for this market type?”
Worked example (1X2) + interpretation
Suppose Book A posts this 1X2 board:
- Home: -145
- Draw: +350
- Away: +230
Posted break-even (implied probabilities):
- Home ≈ 59.18%
- Draw ≈ 22.22%
- Away ≈ 30.30%
Add them: 111.71% total implied.
That’s an expensive menu. (It means the “tax” is baked into the board.)
Fair probabilities (no-vig): normalize by the implied sum:
- Home ≈ 52.98%
- Draw ≈ 19.89%
- Away ≈ 27.13%
What it means: the gap between posted break-even and fair is margin. If Book B has the same match but sums to 104–106%,
Book B is usually the cheaper execution even if one leg looks “prettier” at first glance.
Run this instantly in Fair Line Finder (3-Way), then repeat on a second book.
To measure the board cost directly, use Hold / Overround Calculator.
Proof check: make it apples-to-apples (don’t skip this)
- Same rules: 90 minutes only vs includes extra time can flip the comparison.
- Same moment: compare at the same time—prices move.
- Same market: full-time 1X2 vs “to qualify” is not the same thing.
- Same method: normalize both boards the same way (fair probabilities), then compare.
Decision: shop / size / pass
- Shop: prefer the book with the lower implied sum (tighter overround) for the same match.
- Size smaller: if the board is wide, treat it as higher friction (more margin to overcome).
- Pass: if you’re unsure and the menu is expensive, passing is often the correct +EV behavior.
One-minute cheat sheet
- Odds → implied probabilities
- Add them (implied sum / overround)
- Normalize to 100% (fair probabilities)
- Compare Book A vs Book B on implied sum + fair split
- Shop / size / pass
Related tools (verified)
- Odds Implied Probability (quick break-even check).
- Hold / Overround Calculator (board cost / implied sum).
- Fair Line Finder (3-Way) (no-vig 1X2 probabilities).
- Fair Line Finder (2-Way) (two-outcome markets).
FAQ
What’s the cleanest comparison metric?
Implied sum (overround) plus fair probabilities. They’re comparable across odds formats.
Why do 1X2 comparisons get messy?
Rule differences (90 minutes vs includes extra time), timing differences, and mixing odds formats without converting correctly.
How many samples do I need to learn which book is best?
A handful of matches shows patterns fast; more samples increase confidence.
What should I track?
Book, time, implied sum (overround), fair probability split, and which book was cheapest.
Responsible note: pricing tools reduce margin and improve decision quality, but they don’t guarantee profit.