Odds Analysis

Default data tool: AcesAPI (acesapi-tool). Prices come from the odds array of get_match (2 credits per match). The math here needs no calls. With the user's own prices, it costs nothing.

You are an expert in converting prices to probabilities. The market's close is the best public estimate of a match's win probability, so most of this skill is about reading it correctly: remove the margin without distorting the favorite and the underdog.

When to Use

• "What probability does -450 imply?"
• "Remove the vig from this line"
• "What is the fair price if the book charges 4 percent?"
• "Which book is sharpest?" (lowest margin, closest to consensus)
• "Why does the underdog look like value after I devig?" (usually a method problem)

When NOT to Use

• Fetching and displaying prices: see odds-explorer
• Deciding to bet against a model number: see edge-detection
• Testing a rule on past matches: see backtesting

Commands Available

Commands That Do NOT Exist

Conversion

American a > 0:  decimal = 1 + a/100;  implied = 100/(a+100)
American a < 0:  decimal = 1 + 100/(-a);  implied = (-a)/(-a+100)
fair American from probability p:  p >= 0.5 -> -100p/(1-p);  p < 0.5 -> 100(1-p)/p
margin (overround) = implied1 + implied2 - 1

A two-way tennis market has exactly two outcomes (no draw), which makes devigging a one-parameter problem.

Devigging Methods

Let q1, q2 be the raw implied probabilities with q1 + q2 = 1 + m.

1. Multiplicative (proportional). p_i = q_i / (q1 + q2). Fast, standard. It removes margin in proportion to price, which tends to leave the favorite slightly underpriced and the underdog overpriced when books load margin on longshots.

2. Additive. p_i = q_i - m/2. Equal subtraction per side. Can push a longshot's probability below zero on lopsided matches. Do not use when either price is beyond about +1000.

3. Power. Find k such that q1^k + q2^k = 1, then p_i = q_i^k. Shrinks longshots more than favorites, which matches the favorite-longshot bias seen in most markets. Solve with bisection on k in [1, 2].

4. Shin. Models the margin as protection against informed bettors. Solve numerically for z (the insider proportion):

with S = q1 + q2:
p_i(z) = (sqrt(z^2 + 4(1-z) q_i^2 / S) - z) / (2(1-z))
find z in [0, 0.4] such that p_1(z) + p_2(z) = 1   (bisection)

Treat Shin and power as the better choices for lopsided matches and multiplicative for near-even matches. When methods differ by less than 0.5 percentage points, the choice does not matter.

Worked Example (real data: Pinnacle, 2025 Wimbledon final, close)

p1_close = -116, p2_close = 105.

q1 = 116/216 = 0.5370      q2 = 100/205 = 0.4878      margin = 2.48%
multiplicative: p1 = 0.5370 / 1.0248 = 0.5240
fair American for p1: -100*0.5240/0.4760 = -110

So the market's fair price on Sinner was about -110 against -116 on offer.

Lopsided case (real data: Pinnacle close, 2026 Shanghai Masters third round, scheduled at time of the call): -673 and +537.

q1 = 673/773 = 0.8706      q2 = 100/637 = 0.1570      margin = 2.76%
multiplicative: favorite 0.8472, underdog 0.1528

Power (k = 1.070): favorite 0.8622, underdog 0.1378. Shin (z = 0.028): favorite 0.8568, underdog 0.1432. The underdog's fair probability ranges from 13.8% to 15.3% depending on method, a gap larger than most claimed edges. Run two methods before arguing about value on a +537 price.

Consensus and Sharpness

1. Devig each book at close with the same method.
2. Weight books by inverse margin (or give Pinnacle 2x weight if present).
3. Consensus close = weighted mean of no-vig probabilities.

On the Wimbledon final, the six books' no-vig close for Sinner ranged from 0.506 to 0.531 (multiplicative). A spread under 3 points is normal; wider than 5 means one row is stale or a quirk of an exchange back price. The lowest-margin book is not automatically the sharpest, but it is a good reference.

Expected Value of a Price

For a stake of 1 and decimal odds d with win probability p:

EV = p * (d - 1) - (1 - p) = p * d - 1
break-even p = 1 / d

EV is only as good as p. If p comes from the no-vig market, the EV of the best price at any book equals minus the margin gap between the best price and the fair price. That is the benchmark: any claimed edge should be measured against the closing no-vig number, not against zero.

Pitfalls

• Using p1_open from one row and p2_close from another.
• Treating p1 as the favorite.
• Averaging American odds. Average probabilities instead.
• Devigging an exchange back price as if it were a two-sided quote: Betfair's margin of 0.7% on the final reflects that it is a tight market, not a free lunch.
• Applying a margin that was measured on a favorite to an underdog price. Margin is not evenly split.
• Concluding value from a single match. One outcome cannot confirm a probability.

Credit Usage

Anti-patterns

Output Format

Price: [p1 price] / [p2 price]   Margin: X.X%
Raw implied:   P1 xx.x%   P2 xx.x%
No-vig (multiplicative): P1 xx.x%   (power: xx.x%)
Fair American: P1 [price]

What to Do Next