Betting Splits

Get public betting splits (handle % and bet %) from DraftKings and Circa Sports.


GET /api/v1/splits

Authentication

Requires API key. Available to all tiers.

What are betting splits?

Handle % is the percentage of total money wagered on each side. Bet % is the percentage of total tickets (bets placed) on each side.

The gap between bet % and handle % reveals sharp money. If 30% of tickets carry 60% of the money, sharp bettors are on that side.

Data Sources

Source	Type	Update Frequency
DraftKings	Recreational book (~35% US market share)	Every 5 minutes
Circa Sports	Sharp-friendly book (attracts professionals)	Every 5 minutes

Comparing DraftKings (recreational) vs Circa (sharp) splits reveals where professional money diverges from the public.

Query Parameters

Parameter	Type	Description
`sport`	string	Filter by sport (comma-separated). Example: `basketball`
`league`	string	Filter by league (comma-separated). Example: `nba,ncaab`
`sportsbook`	string	Filter by splits source. Example: `draftkings,circa`
`event_id`	string	Filter by canonical event ID (comma-separated)
`limit`	integer	Max results (default 100, max 500)
`offset`	integer	Pagination offset (default 0)

Response


{
  "success": true,
  "data": [
    {
      "event_id": "nba_thunder_timberwolves_2026-03-15",
      "sport": "basketball",
      "league": "nba",
      "book": "draftkings",
      "away_team": "Minnesota Timberwolves",
      "home_team": "Oklahoma City Thunder",
      "spread": {
        "away_line": 9.5,
        "home_line": -9.5,
        "handle_pct": { "away": 0.55, "home": 0.45 },
        "bets_pct": { "away": 0.59, "home": 0.41 }
      },
      "total": {
        "line": 225.5,
        "handle_pct": { "over": 0.51, "under": 0.49 },
        "bets_pct": { "over": 0.67, "under": 0.33 }
      },
      "moneyline": {
        "away_odds": 310,
        "home_odds": -395,
        "handle_pct": { "away": 0.51, "home": 0.49 },
        "bets_pct": { "away": 0.22, "home": 0.78 }
      },
      "fetched_at": "2026-03-15T14:30:00Z"
    }
  ],
  "meta": {
    "total": 25,
    "limit": 100,
    "offset": 0,
    "sources": ["draftkings", "circa"],
    "sports": ["basketball", "mma"]
  }
}

Response Fields

Field	Type	Description
`event_id`	string	Canonical event ID — use this to join with `/odds` data
`sport`	string	Atlas-normalized sport name
`league`	string	Atlas-normalized league name
`book`	string	Source sportsbook for the splits data
`away_team`	string	Away team name
`home_team`	string	Home team name
`spread.away_line`	number	Away spread line (e.g., +9.5)
`spread.home_line`	number	Home spread line (e.g., -9.5)
`spread.handle_pct`	object	Money % on each side (`away`, `home`; 0.0-1.0)
`spread.bets_pct`	object	Ticket % on each side (`away`, `home`; 0.0-1.0)
`total.line`	number	Over/under line (e.g., 225.5)
`total.handle_pct`	object	Money % (`over`, `under`; 0.0-1.0)
`total.bets_pct`	object	Ticket % (`over`, `under`; 0.0-1.0)
`moneyline.away_odds`	number	Away moneyline odds (American format)
`moneyline.home_odds`	number	Home moneyline odds (American format)
`moneyline.handle_pct`	object	Money % on each side (`away`, `home`; 0.0-1.0)
`moneyline.bets_pct`	object	Ticket % on each side (`away`, `home`; 0.0-1.0)
`fetched_at`	string	ISO 8601 timestamp when data was last scraped

The event_id field uses the same canonical ID format as the /odds endpoint, so you can join splits with odds data directly. For example, fetch odds for a specific game and compare with its splits:


GET /api/v1/odds?event_id=nba_thunder_timberwolves_2026-03-15
GET /api/v1/splits?event_id=nba_thunder_timberwolves_2026-03-15

Per-Selection Bet % (BetMGM)

In addition to the game-level splits from this endpoint, BetMGM odds items in the /odds response include an inline public_bet_pct field (0.0-1.0) representing ticket percentage per selection. This is available on NBA (100%), MLB (100%), and NHL (~60%) prematch markets.

Examples

All NBA Splits


curl "https://api.sharpapi.io/api/v1/splits?league=nba" \
  -H "X-API-Key: YOUR_API_KEY"

DraftKings Only


curl "https://api.sharpapi.io/api/v1/splits?sportsbook=draftkings&sport=basketball" \
  -H "X-API-Key: YOUR_API_KEY"

Specific Game


curl "https://api.sharpapi.io/api/v1/splits?event_id=nba_thunder_timberwolves_2026-03-15" \
  -H "X-API-Key: YOUR_API_KEY"

Splits History

Track how splits shift over time for a specific event.


GET /api/v1/splits/history?event_id={event_id}

Query Parameters

Parameter	Type	Required	Description
`event_id`	string	Yes	Canonical event ID
`sportsbook`	string	No	Filter by book (comma-separated)
`limit`	integer	No	Max entries (default 100, max 500)

Response

Entries are sorted oldest-first, showing how splits evolved over the game day.


{
  "success": true,
  "data": [
    {
      "book": "draftkings",
      "ts": "2026-03-15T14:30:00Z",
      "timestamp": 1710513000,
      "spread": {
        "handle_pct": { "away": 0.55, "home": 0.45 },
        "bets_pct": { "away": 0.59, "home": 0.41 }
      },
      "total": {
        "handle_pct": { "over": 0.51, "under": 0.49 },
        "bets_pct": { "over": 0.67, "under": 0.33 }
      },
      "moneyline": {
        "handle_pct": { "away": 0.51, "home": 0.49 },
        "bets_pct": { "away": 0.22, "home": 0.78 }
      }
    },
    {
      "book": "draftkings",
      "ts": "2026-03-15T14:35:00Z",
      "timestamp": 1710513300,
      "spread": {
        "handle_pct": { "away": 0.58, "home": 0.42 },
        "bets_pct": { "away": 0.60, "home": 0.40 }
      }
    }
  ],
  "meta": {
    "event_id": "nba_thunder_timberwolves_2026-03-15",
    "total": 2,
    "books": ["draftkings", "circa"],
    "oldest": "2026-03-15T14:30:00Z",
    "newest": "2026-03-15T14:35:00Z"
  }
}

Data is collected every 5 minutes and retained for 48 hours.

Full History


curl "https://api.sharpapi.io/api/v1/splits/history?event_id=nba_thunder_timberwolves_2026-03-15" \
  -H "X-API-Key: YOUR_API_KEY"

Interpreting Splits

Signal	What it means
Bet % high, Handle % low	Public side — lots of small bets
Bet % low, Handle % high	Sharp side — fewer but larger bets
DK and Circa agree	Market consensus — both public and sharp aligned
DK and Circa diverge	Sharp-public split — Circa (sharp) disagrees with DK (public)

Splits data only comes from recreational books (DraftKings) and one sharp-adjacent book (Circa). No sharp book publishes splits. Use splits as one signal alongside line movement and +EV analysis, not in isolation.