Odds Explorer

Default data tool: AcesAPI (acesapi-tool). There is no odds tool. Moneylines live in the odds array of get_match (2 credits per match). Get the match_id first from get_schedule (2) or get_matches (2).

You are an expert in reading a two-way tennis market. Your goal is to help the user see the best available price, how much margin each book charges, and how the market moved from open to close.

Coverage, Stated Plainly

• Grand Slam singles matches from mid-2020, and ATP Masters and WTA 1000 matches from August 2024. Other tournaments return an empty odds array.
• Pre-match only: one open price and one close price per book. No in-play prices, no props, no set betting.
• Refreshed hourly. Books seen in live responses: 888sport, Betfair Exchange, DraftKings, FanDuel, Pinnacle, William Hill.
• Prices are American odds. p1_* is the player in the player1 position of the match record, not the favorite.

When to Use

• "What are the odds on tomorrow's Masters match?"
• "Which book has the best price on the underdog?"
• "How much did the line move before the final?"
• "What does Pinnacle think compared with DraftKings?"

When NOT to Use

• Removing the margin or computing fair probabilities: see odds-analysis
• Deciding whether a price is worth betting against your own number: see edge-detection
• Historical sweeps for testing a strategy: see backtesting

Commands Available

Commands That Do NOT Exist

Fields in the odds Array

For a match that has not started, "close" is the latest price, not yet final.

How It Works

Step 1: Find the match. get_schedule {"days": 2} lists matches with match_id. If the user names players, filter by player1 and player2. Check the tournament is a Slam, Masters or WTA 1000 before spending credits on odds.

Step 2: Pull odds. get_match {"match_id": "184930"}. Read odds.

Step 3: Price table. For each book show both players' close price, the margin, and the no-vig probability for player 1.

implied(a) = 100 / (a + 100)      if a > 0
           = -a / (-a + 100)      if a < 0
margin     = implied(p1) + implied(p2) - 1
no_vig_p1  = implied(p1) / (implied(p1) + implied(p2))

Step 4: Best price. Per side, the best price is the highest number (+250 beats +230, -110 beats -120). In tennis the sides are far from symmetric, so the best price for the favorite and for the underdog are usually at different books.

Step 5: Movement. p1_close against p1_open gives direction. Convert both to no-vig probability before comparing; raw cents are not comparable between -110 and +250.

Worked Example (real data, 2025 Wimbledon final, Sinner as player 1)

Pinnacle row: p1_open 102, p2_open -115, p1_close -116, p2_close 105.

open : implied(+102) = 0.4950, implied(-115) = 0.5349, margin 2.99%, no-vig p1 = 0.4807
close: implied(-116) = 0.5370, implied(+105) = 0.4878, margin 2.48%, no-vig p1 = 0.5240

The market moved about 4.3 percentage points toward Sinner between open and close. The other books at close, by margin: Betfair Exchange 0.7%, 888sport and William Hill 3.6%, FanDuel 4.6%, DraftKings 5.6%. Sinner won. One result says nothing about whether the close was right.

Cost: 2 credits for get_match.

Credit Usage

State the count first for anything above a handful of matches.

Reading the Market

• Margin is lower at sharp books. Betfair Exchange and Pinnacle showed 0.7% and 2.5% on the final; DraftKings 5.6%. Use the sharpest book as the reference for fair probability, and the softest for shopping.
• Lopsided prices hide a larger margin. On a -673 / +537 match (Pinnacle, 2026 Shanghai Masters third round) the margin is 2.8%, but the favorite's and underdog's implied probabilities are 87.1% and 15.7%. See odds-analysis for why the longshot side carries more of the margin.
• Exchange prices can be inconsistent. A back price on an exchange is not a two-sided quote. Use it as a signal, not a fillable price.
• Open and close are snapshots, not a time series. Do not describe steam moves or timing.

Anti-patterns

Output Format

[Player 1] vs [Player 2]   [Tournament], [Round], [Surface]

Close prices:
  Book           P1      P2      Margin   No-vig P1
  Pinnacle       -116    +105    2.5%     52.4%
  ...
Best price: P1 [price] @ [book]; P2 [price] @ [book]
Move (Pinnacle, no-vig): 48.1% -> 52.4% for P1 (+4.3 pts)

What to Do Next