Odds API for Positive EV Betting

SportsGameOdds is a sports odds API that ships no-vig consensus fairOdds alongside every sportsbook's posted price, so a positive EV betting tool can compare each book's odds to a true-probability benchmark out of the box. A single event object returns 85+ books (Pinnacle and Circa included) plus fairOdds, fairSpread, and fairOverUnder, with no devig pipeline to build or maintain.

Why use SportsGameOdds to find +EV bets

• No-vig fair odds ship with every market. Each oddID carries fairOdds, fairSpread, and fairOverUnder, the consensus true probability with the vig already removed. Your edge is the fair implied probability minus a book's implied probability, with no devig step to write.
• Every book's price sits side by side in byBookmaker. One object exposes 85+ books: sportsbooks like Pinnacle, Circa, DraftKings, FanDuel, BetMGM, Bet365, and Caesars, plus prediction markets (Kalshi, Polymarket) and DFS (PrizePicks, Underdog). You scan it for the one book pricing a side cheaper than fair.
• Player props, team props, and alt lines are first-class. +EV is easiest to find in less-efficient markets, and SportsGameOdds returns player props, team props, and alternate lines with the exact same fairOdds/byBookmaker shape as the main moneylines.
• Closing-line value is one parameter away. Add includeOpenCloseOdds=true and each book returns its open and close, so you can log CLV and confirm your picks beat the closing number.
• Sub-minute updates and built-in grading. Odds refresh from 10 minutes on the free tier down to sub-minute on Pro, and every odd carries a score result field for per-bet settlement at every tier.

How a +EV bet finder works with our data

In a +EV finder, the comparison loop is trivial. What's hard is the fair-value benchmark behind it. You need an unbiased estimate of each outcome's true probability, which normally means scraping a sharp book, stripping its margin, and blending sources yourself. SportsGameOdds does that aggregation for you and returns the result as fairOdds, a no-vig consensus across the book list (see how consensus odds are calculated). Your tool consumes the benchmark instead of producing it.

Compare each book's price to fairOdds

For any oddID, convert fairOdds to an implied probability, then convert each entry in byBookmaker to its own implied probability. When a book's implied probability is lower than the fair probability, that price pays more than it should. That's a positive-EV bet. Your edge is simply the fair probability minus the book's implied probability, and expected value follows directly from the book's payout. Use bookOdds (the consensus with vig) only when you want the market price; for +EV math you want fairOdds.

Cover props and alt lines, not just mains

Main moneylines on big games are efficient, so the consensus and the sharpest books rarely diverge. The edge lives in player props, team props, and alternate lines, where books disagree more and update unevenly. Because those markets carry the same fairOdds and byBookmaker fields, you can point the same comparison loop at them without a second integration. Widening your finder's surface area is a query change rather than a new parser.

Track closing-line value

Add includeOpenCloseOdds=true and every book returns its opening and closing price for each market. Store the price you flagged a bet at, then compare it to the closing fairOdds to measure CLV, the single best leading indicator that a +EV process is real rather than variance. Historical odds for deeper backtesting are available on Pro and above.

Example request

curl "https://api.sportsgameodds.com/v2/events?leagueID=NBA&oddsAvailable=true&includeOpenCloseOdds=true" \
  -H "x-api-key: YOUR_API_KEY"

{
  "data": [
    {
      "eventID": "abc123",
      "odds": {
        "points-home-game-ml-home": {
          "oddID": "points-home-game-ml-home",
          "fairOdds": "-148",
          "bookOdds": "-155",
          "byBookmaker": {
            "pinnacle":   { "odds": "-150", "available": true },
            "draftkings": { "odds": "-135", "available": true }
          }
        }
      }
    }
  ]
}

Here fairOdds of -148 implies a true win probability near 59.7%, while DraftKings at -135 implies only 57.4%. Because the book's implied probability is lower than fair, the DraftKings price is +EV. You are getting a better number than the no-vig consensus. See the documentation and the handling odds guide for the full field reference, including the score field used to grade each bet after the game.

SportsGameOdds vs building your own devig pipeline

Building this yourself is a reasonable choice if you want total control over which books form your fair value and how the vig is removed, and that flexibility is real. The trade-off is that you take on the scraping, normalization, storage, and upkeep that SportsGameOdds returns ready to use.

Related use cases

• Odds API for Arbitrage Betting: turn the same byBookmaker price grid into cross-book arbitrage scans.
• Odds Comparison & Line Shopping API: surface the best available price across every book for line shopping.
• Odds Data for Sports Betting Models: feed fairOdds and closing-line history into your own predictive models.
• How consensus odds are calculated: the methodology behind the fairOdds benchmark.
• Pricing: object-based plans with a free Amateur tier and no credit card.