Odds Comparison

Compare odds for a specific event across multiple sportsbooks. Results are organized by market and selection, with hold calculations and best/worst book identification for each selection.


GET /api/v1/odds/comparison

Authentication

Requires API key. Available to all tiers.

The sportsbooks included in the comparison depend on your tier’s book access. Free tier compares DraftKings and FanDuel; higher tiers include more books. See Book Access by Tier.

Query Parameters

Parameter	Type	Default	Description
`event`	string	required	Event ID to compare odds for
`market`	string	all	Filter by market type (e.g., `moneyline`, `spread`)
`sportsbook`	string	all	Comma-separated sportsbook IDs to include

The event parameter is required. This endpoint returns a detailed comparison for a single event.

Example Requests

cURL


# Compare all odds for a specific NBA event
curl -X GET "https://api.sharpapi.io/api/v1/odds/comparison?event=33483153" \
  -H "X-API-Key: YOUR_API_KEY"
 
# Compare only moneyline odds
curl -X GET "https://api.sharpapi.io/api/v1/odds/comparison?event=33483153&market=moneyline" \
  -H "X-API-Key: YOUR_API_KEY"

JavaScript


const response = await fetch(
  'https://api.sharpapi.io/api/v1/odds/comparison?event=33483153&market=moneyline',
  { headers: { 'X-API-Key': 'YOUR_API_KEY' } }
);
const { data } = await response.json();
 
data.markets.forEach(market => {
  console.log(`\n${market.market_type} (Hold: ${market.hold.best_available.toFixed(1)}%)`);
  market.selections.forEach(sel => {
    console.log(`  ${sel.selection}: Best ${sel.best_odds} at ${sel.best_book}, Worst ${sel.worst_odds} at ${sel.worst_book}`);
    for (const [book, odds] of Object.entries(sel.books)) {
      console.log(`    ${book}: ${odds.odds_american}`);
    }
  });
});

Python


import requests
 
response = requests.get(
    'https://api.sharpapi.io/api/v1/odds/comparison',
    params={'event': '33483153', 'market': 'moneyline'},
    headers={'X-API-Key': 'YOUR_API_KEY'}
)
result = response.json()
 
event = result['data']
print(f"{event['event_name']}")
 
for market in event['markets']:
    hold = market['hold']['best_available']
    print(f"\n  {market['market_type']} (Hold: {hold:.1f}%)")
 
    for sel in market['selections']:
        print(f"    {sel['selection']}: Best {sel['best_odds']} at {sel['best_book']}")
        for book, odds in sel['books'].items():
            print(f"      {book}: {odds['odds_american']}")

Response

Success (200)


{
  "success": true,
  "data": {
    "event_id": "nba_suns_76ers_2026-01-26",
    "event_name": "PHO Suns @ PHI 76ers",
    "sport": "basketball",
    "league": "nba",
    "start_time": "2026-01-26T19:00:00Z",
    "is_live": false,
    "books_available": ["betmgm", "draftkings", "fanduel", "pinnacle"],
    "markets": [
      {
        "market_type": "moneyline",
        "hold": {
          "best_available": 2.7,
          "by_book": {
            "draftkings": 3.5,
            "fanduel": 3.6,
            "betmgm": 4.7,
            "pinnacle": 3.9
          }
        },
        "selections": [
          {
            "selection": "PHO Suns",
            "selection_type": "away",
            "line": null,
            "books": {
              "fanduel": {
                "odds_american": -145,
                "odds_decimal": 1.690,
                "timestamp": "2026-01-26T02:10:20.000Z"
              },
              "draftkings": {
                "odds_american": -150,
                "odds_decimal": 1.667,
                "timestamp": "2026-01-26T02:10:24.000Z"
              },
              "betmgm": {
                "odds_american": -155,
                "odds_decimal": 1.645,
                "timestamp": "2026-01-26T02:10:18.000Z"
              },
              "pinnacle": {
                "odds_american": -148,
                "odds_decimal": 1.676,
                "timestamp": "2026-01-26T02:10:15.000Z"
              }
            },
            "best_book": "fanduel",
            "best_odds": -145,
            "worst_book": "betmgm",
            "worst_odds": -155,
            "spread": 1.6
          },
          {
            "selection": "PHI 76ers",
            "selection_type": "home",
            "line": null,
            "books": {
              "draftkings": {
                "odds_american": 130,
                "odds_decimal": 2.300,
                "timestamp": "2026-01-26T02:10:24.000Z"
              },
              "fanduel": {
                "odds_american": 125,
                "odds_decimal": 2.250,
                "timestamp": "2026-01-26T02:10:20.000Z"
              },
              "betmgm": {
                "odds_american": 128,
                "odds_decimal": 2.280,
                "timestamp": "2026-01-26T02:10:18.000Z"
              },
              "pinnacle": {
                "odds_american": 126,
                "odds_decimal": 2.260,
                "timestamp": "2026-01-26T02:10:15.000Z"
              }
            },
            "best_book": "draftkings",
            "best_odds": 130,
            "worst_book": "fanduel",
            "worst_odds": 125,
            "spread": 0.9
          }
        ]
      }
    ]
  },
  "meta": {
    "market_filter": null,
    "updated_at": "2026-01-26T02:10:30.000Z"
  }
}

Response Headers


X-RateLimit-Limit: 300
X-RateLimit-Remaining: 297
X-RateLimit-Reset: 1737853200
X-Data-Delay: 0
X-Request-Id: req_comp_456abc

Response Schema

The response data is a single event object (not an array) containing nested markets and selections.

Event Object

Field	Type	Description
`event_id`	string	Event identifier
`event_name`	string	Event display name (e.g., `"Away Team @ Home Team"`)
`sport`	string	Sport slug
`league`	string	League slug
`start_time`	string	ISO 8601 event start time
`is_live`	boolean	Whether the event is currently live
`books_available`	string[]	Sportsbook IDs with odds for this event
`markets`	array	Array of market comparisons

Market Object

Field	Type	Description
`market_type`	string	Market type (e.g., `moneyline`, `spread`, `total`)
`hold`	object	Market hold (overround) calculations
`hold.best_available`	number	Hold percentage using best odds across all books per selection
`hold.by_book`	object	Hold percentage for each individual sportsbook (keyed by book ID)
`selections`	array	Array of selections within this market

Selection Object

Field	Type	Description
`selection`	string	Selection name (e.g., team name, Over/Under)
`selection_type`	string	`home`, `away`, `over`, `under`
`line`	number \| null	Line value (for spreads/totals)
`books`	object	Odds from each sportsbook (keyed by book ID)
`best_book`	string	Sportsbook ID with the best odds
`best_odds`	number	Best American odds value
`worst_book`	string	Sportsbook ID with the worst odds
`worst_odds`	number	Worst American odds value
`spread`	number	Difference in implied probability (%) between best and worst book

Book Odds Object

Each entry in the books object:

Field	Type	Description
`odds_american`	number	American odds
`odds_decimal`	number	Decimal odds
`timestamp`	string	When this book’s odds were last updated

Understanding Hold

The hold field on each market shows the bookmaker’s built-in margin:

best_available: The hold (%) if you shop for the best odds on each selection. This is the “true” market efficiency from a bettor’s perspective.
by_book: The hold (%) at each individual sportsbook. Higher hold = more margin taken by the book.

Hold (%)	Interpretation
< 2	Very efficient market (sharp books)
2-5	Normal market
5-8	High margin (typical for props)
> 8	Very high margin

Understanding the `spread` Field

The spread on each selection represents the difference in implied probability between the best and worst sportsbook for that selection. A higher spread indicates more variance across books.

Spread	Interpretation
< 1%	Books are tightly aligned
1-3%	Normal variance, moderate shopping value
> 3%	Significant discrepancy, strong shopping value

Use Cases

Line Shopping

Find the best price before placing a bet by comparing all books:


curl "https://api.sharpapi.io/api/v1/odds/comparison?event=33483153&market=spread" \
  -H "X-API-Key: YOUR_API_KEY"

Identifying Stale Lines

Look for books that haven’t updated recently by checking each book’s timestamp. A book with stale odds may be slow to adjust, creating temporary value.

Market Efficiency

Compare hold.best_available vs individual book holds. A large gap means line shopping is particularly valuable for this market.

Odds Snapshot - Get raw odds from individual sportsbooks
Best Odds - Get just the best odds with consensus and hold
Odds Delta - Get only odds that changed since a given timestamp
Batch Odds - Fetch comparison data for multiple events at once