Odds API by market / Tennis

Tennis Break Points Won API

The player_break_points_won board is not posted right now. This page keeps the last measured window — 336settled outcomes — and reactivates on its own the first build after books post the market again. The endpoint, the response shape and the free tier work today.

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What Tennis break points won is

Breaks of serve converted by one player. Low-count and high-variance — one loose service game moves it.

How we settle it. Graded against that player's converted break points.

1
books quoting it on the next event
not posted right now; reactivates when books post it
336
outcomes settled in the last 4-day window it was posted

Every number on this page is measured against the live API, never copied from a spec sheet. Last measured 16 August 2026.

Books that last posted Tennis break points won

Measured on the last slate that carried it, 16 August 2026. When books post it again, this list rebuilds from whichever ones actually do.

PrizePicks

Line shopping across all of them is one request — every book arrives in the same bookmakers array, not one call per book. Add ?bookmakers= to narrow it, or use /best-line for the best price per line already ranked.

Recently settled Tennis break points won outcomes

These are real rows out of the API, not an illustration. Each one was a price on a board before the event and carries the actual figure it was graded against afterwards. No other odds API returns that last column — they stop at the price.

336 break points won outcomes settled in the last 4-day window it was posted across 4 books. The 12 most recent:

PlayerBetActualResult
Arthur FilsOver 2.54.0won
Yannick HanfmannOver 0.51.0won
Arthur FilsUnder 2.54.0lost
Yannick HanfmannOver 0.51.0won
Jiri LeheckaOver 2.0void
Jiri LeheckaUnder 2.0void
Arthur FeryOver 2.52.0lost
Arthur FeryOver 2.52.0lost
James DuckworthOver 1.53.0won
Hubert HurkaczOver 1.50.0lost
Hubert HurkaczUnder 1.50.0won
Alex de MinaurOver 2.51.0lost

Over/Under split, last posted window

The Over won 33.3% of 123 decided break points won lines (41 over, 82 under, 2 push). Computed from the settled rows themselves, scoped to Tennis only.

Read off 168 Over legs out of 336 settled outcomes on this market. The rest are Unders and milestone legs (“1+”, “2+”) that some books price here too, and a threshold rung is not an Over.

A few days of one market describes a few days — it is not an edge. Pull the full history through /exports/resolved-props for a sample worth modelling on.

Live response

Captured from the real endpoint on Emiliana Arango @ Iga Swiatek while it was posted, trimmed to one book and three outcomes so the shape stays readable. The full response carries every book and every line, alternates included, in the same call.

{
  "id": "143946",
  "sport_key": "tennis",
  "home_team": "Iga Swiatek",
  "away_team": "Emiliana Arango",
  "commence_time": "2026-08-15T15:00:00Z",
  "live": false,
  "last_update": "2026-08-15T14:47:03.319694Z",
  "bookmakers": [
    {
      "key": "prizepicks",
      "title": "PrizePicks",
      "last_update": "2026-08-15T14:47:03.319694Z",
      "link": null,
      "book_event_id": null,
      "markets": [
        {
          "key": "player_break_points_won",
          "last_update": "2026-08-15T14:47:03.319694Z",
          "period": null,
          "outcomes": [
            {
              "name": "Over",
              "description": "Emiliana Arango",
              "price": 100,
              "point": 1.5,
              "book_updated_at": null,
              "book_version": null,
              "payout_multiplier": null,
              "dfs_odds_type": "standard",
              "last_change_at": "2026-08-15T12:26:40.686257Z",
              "line_gap": null,
              "book_outcome_id": null
            },
            {
              "name": "Over",
              "description": "Iga Swiatek",
              "price": 100,
              "point": 5.5,
              "book_updated_at": null,
              "book_version": null,
              "payout_multiplier": null,
              "dfs_odds_type": "standard",
              "last_change_at": "2026-08-15T12:26:40.686257Z",
              "line_gap": null,
              "book_outcome_id": null
            },
            {
              "name": "Under",
              "description": "Emiliana Arango",
              "price": 100,
              "point": 1.5,
              "book_updated_at": null,
              "book_version": null,
              "payout_multiplier": null,
              "dfs_odds_type": "standard",
              "last_change_at": "2026-08-15T12:26:40.686257Z",
              "line_gap": null,
              "book_outcome_id": null
            }
          ]
        }
      ]
    }
  ]
}

The response shape is the-odds-api compatible — events, bookmakers, markets, outcomes — so migrating is usually a base URL change.

Try it

1. List Tennis events to get an event id:

curl "https://api.prop-line.com/v1/sports/tennis/events?apiKey=YOUR_API_KEY"

2. Pull break points won for one game across every book — swap in a live event id from step 1 once books post it again:

curl "https://api.prop-line.com/v1/sports/tennis/events/143946/odds?apiKey=YOUR_API_KEY&markets=player_break_points_won"

3. After the game, get the graded outcomes with the actual stat:

curl "https://api.prop-line.com/v1/sports/tennis/events/143946/results?apiKey=YOUR_API_KEY"

Steps 1 and 2 run on the free tier. Step 3 — prop resolution — starts on Hobby at $9/mo. See pricing.

Get your free Tennis odds API key

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