Odds API by market / Tennis

Tennis Total Games API

Live total_games odds across every book that posts it, in one REST call — and, unlike any other odds API, every one of those outcomes settled against the official result once play ends.

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What Tennis total games is

Over/Under on games in the match. Some books post this at match level and others per player under the same name; both are carried and settled on their own terms.

How we settle it. The match-level version is graded from both players' game counts. The per-player version is graded from the named player's only.

books quoting it on the next event

2/12

of the next Tennis events carry it right now

2,614

outcomes settled in the last 4 days

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

Books posting Tennis total games

Measured live, not listed from a spec. Coverage moves — a book that has not put its board up yet will not appear until it does, which is exactly what this list is for.

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 total games 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.

2,614 total games outcomes settled in the last 4 days across 4 books. The 12 most recent:

Game	Book	Bet	Price	Actual	Result
Jessica Bouzas Maneiro @ Katerina Siniakova	dabble	Over 20.5	100	—	void
Jessica Bouzas Maneiro @ Katerina Siniakova	dabble	Under 20.5	100	—	void
Jessica Bouzas Maneiro @ Katerina Siniakova	sleeper	Over 21.5	-123	26.0	won
Jessica Bouzas Maneiro @ Katerina Siniakova	sleeper	Under 21.5	-133	26.0	lost
Zizou Bergs @ Daniel Merida Aguilar	sleeper	Over 23.5	-128	—	void
Zizou Bergs @ Daniel Merida Aguilar	underdog	Over 22.5	-124	—	void
Zizou Bergs @ Daniel Merida Aguilar	underdog	Under 22.5	100	—	void
Zizou Bergs @ Daniel Merida Aguilar	dabble	Over 23.0	100	—	void
Sebastian Baez @ Learner Tien	underdog	Over 21.5	-115	—	void
Sebastian Baez @ Learner Tien	prizepicks	Over 21.5	100	—	void
Sofia Kenin @ Marta Kostyuk	prizepicks	Over 19.0	100	—	void
Sofia Kenin @ Marta Kostyuk	prizepicks	Under 19.0	100	—	void

Over/Under split, last 4 days

The Over won 51.3% of 863 decided total games lines (443 over, 420 under). Computed from the settled rows themselves, scoped to Tennis only.

Read off 1,307 Over legs out of 2,614 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 Ingrid Neel / Giuliana Olmos @ Shuko Aoyama / En Shuo Liang, 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": "145053",
  "sport_key": "tennis",
  "home_team": "Shuko Aoyama / En Shuo Liang",
  "away_team": "Ingrid Neel / Giuliana Olmos",
  "commence_time": "2026-08-16T15:00:00Z",
  "live": false,
  "last_update": "2026-08-16T16:45:28.592387Z",
  "bookmakers": [
    {
      "key": "prizepicks",
      "title": "PrizePicks",
      "last_update": "2026-08-16T15:04:25.597472Z",
      "link": null,
      "book_event_id": null,
      "markets": [
        {
          "key": "total_games",
          "last_update": "2026-08-16T15:04:25.597472Z",
          "period": null,
          "suspended_at": null,
          "outcomes": [
            {
              "name": "Over",
              "description": "Aoyama S / Liang E-",
              "price": 100,
              "point": 20,
              "book_updated_at": null,
              "book_version": null,
              "payout_multiplier": null,
              "dfs_odds_type": "standard",
              "last_change_at": "2026-08-15T18:30:41.874193Z",
              "line_gap": null,
              "book_outcome_id": null
            },
            {
              "name": "Under",
              "description": "Aoyama S / Liang E-",
              "price": 100,
              "point": 20,
              "book_updated_at": null,
              "book_version": null,
              "payout_multiplier": null,
              "dfs_odds_type": "standard",
              "last_change_at": "2026-08-15T18:30:41.874193Z",
              "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 total games for one game across every book — this exact URL works right now:

curl "https://api.prop-line.com/v1/sports/tennis/events/145053/odds?apiKey=YOUR_API_KEY&markets=total_games"

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

curl "https://api.prop-line.com/v1/sports/tennis/events/145053/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.

Related endpoints

Other Tennis markets

Games Won Player Aces Double Faults Total Points Moneyline Point Spread Total Sets Total Tiebreaks Break Points Won

All markets →Full API documentation →How prop resolution works →Code recipes →

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