+EV Opportunities

Find positive expected value betting opportunities across all sportsbooks.


GET /api/v1/opportunities/ev

This endpoint replaces the former /positive-ev and /value-bets endpoints. All scoring fields (confidence_score, kelly_percent, fair_probability) are now included in every response.

Multi-book results: When multiple sportsbooks are +EV on the same selection, the API returns a separate opportunity for each book. For example, if DraftKings is +105, FanDuel is +103, and BetMGM is +101 on the same moneyline, you’ll see three entries — each with its own sportsbook, odds_american, ev_percentage, kelly_percent, and confidence_score. Results are sorted by EV% descending by default, so the best-odds book appears first. Use the sportsbook filter to narrow to specific books.

Live game state: EV rows do not carry scores, period, or clock. Live game state is served exclusively by the Game State endpoint and the gamestate stream channel. Join rows to game state by event_id.

Authentication

Requires API key. Pro tier or higher required. Your account must have the ev feature enabled.

Query Parameters

Parameter	Type	Default	Description
`sport`	string	all	Filter by sport(s), comma-separated (e.g. `basketball`, `football`, `ice_hockey`)
`league`	string	all	Filter by league(s), comma-separated (e.g. `nba`, `nfl`, `nhl`)
`sportsbook`	string	tier-allowed	Filter by sportsbook(s), comma-separated. Tier limits enforced.
`market`	string	all	Filter by market type(s), comma-separated. Supports category aliases (`main`, `spread`, `total`, `props`) or exact types (`point_spread`, `player_points`).
`event`	string	all	Filter by game/event ID(s), comma-separated
`min_ev`	number	0	Minimum EV percentage threshold
`max_ev`	number	—	Maximum EV percentage threshold
`live`	boolean	—	`true` = live only, `false` = prematch only, omit = both
`min_odds`	number	—	Minimum American odds (e.g., `-200`)
`max_odds`	number	—	Maximum American odds (e.g., `+500`)
`min_market_width`	number	—	Minimum market width (vig indicator). Lower width = sharper market.
`max_market_width`	number	—	Maximum market width
`max_hold`	number	5.0	Maximum book hold (vig) percentage. Drops opportunities where the market hold exceeds this threshold.
`min_kelly`	number	—	Minimum Kelly percentage (e.g. `2` = 2% bankroll allocation)
`max_kelly`	number	—	Maximum Kelly percentage
`min_confidence`	number	—	Minimum confidence score (0–100)
`max_confidence`	number	—	Maximum confidence score (0–100)
`max_odds_age`	number	—	Maximum odds age in seconds. Filters out stale opportunities where the underlying odds are older than this threshold.
`is_player_prop`	boolean	—	`true` = player props only, `false` = game-level markets only
`is_alternate_line`	boolean	—	`true` = alternate lines only, `false` = main line only
`arb_available`	boolean	—	`true` = only opportunities that also have an arbitrage cross-reference
`player_name`	string	—	Filter to a specific player (alias: `player`). Case-insensitive exact match on the canonical name (e.g. `Aaron Judge`).
`stat_category`	string	—	Filter to a player-prop stat category (e.g. `points`, `rebounds`, `passing_yards`)
`selection`	string	—	Filter to a specific selection name (case-insensitive exact match)
`devig_book`	string	—	Override the sharp anchor book used for devigging. Defaults to Pinnacle.
`date_range`	string	—	Filter by event date: `today`, `tomorrow`, or `week`. Dates are evaluated in US Eastern Time (ET).
`sort`	string	`-ev`	Sort field. Options: `ev`, `confidence`/`confidence_score`, `kelly`/`kelly_percent`, `time`/`start_time`, `book_count`/`books`. Prefix with `-` for descending.
`limit`	integer	50	Results per page (max 200)
`offset`	integer	0	Pagination offset (max 5000)

Filtering Multiple Values

Use comma-separated values for multi-select filters:


?sportsbook=draftkings,fanduel&league=nba,nfl

Example Requests

cURL


# Basic EV opportunities for NBA
curl -X GET "https://api.sharpapi.io/api/v1/opportunities/ev?league=nba&min_ev=2" \
  -H "X-API-Key: YOUR_API_KEY"

JavaScript


const response = await fetch(
  'https://api.sharpapi.io/api/v1/opportunities/ev?league=nba&min_ev=2',
  { headers: { 'X-API-Key': 'YOUR_API_KEY' } }
);
const { data, meta } = await response.json();
console.log(`Found ${meta.count} +EV opportunities`);
console.log(`Average EV: ${meta.summary.avg_ev}%`);

Python


import requests
 
response = requests.get(
    'https://api.sharpapi.io/api/v1/opportunities/ev',
    params={
        'league': 'nba',
        'min_ev': 2,
    },
    headers={'X-API-Key': 'YOUR_API_KEY'}
)
data = response.json()
for opp in data['data']:
    print(f"{opp['selection']} @ {opp['sportsbook']}: {opp['ev_percentage']}% EV")

Response

Success (200)


{
  "success": true,
  "data": [
    {
      "id": "ev_dk_nba_33483153_ml_PHO",
      "game_id": "evt_nba_phi_pho_20260208",
      "ev_percentage": 4.2,
      "odds_american": -105,
      "odds_decimal": 1.952,
      "no_vig_odds": -118,
      "fair_probability": 0.541,
      "market_width": 3.2,
      "devig_method": "power",
      "sharp_book": "pinnacle",
      "selection": "PHO Suns",
      "market": "moneyline",
      "line": null,
      "sportsbook": "draftkings",
      "game": "PHI 76ers vs PHO Suns",
      "sport": "basketball",
      "league": "nba",
      "home_team": "PHI 76ers",
      "away_team": "PHO Suns",
      "start_time": "2026-02-08T19:00:00Z",
      "is_live": false,
      "confidence_score": 87,
      "kelly_percent": 2.1,
      "book_count": 5,
      "arb_available": false,
      "arb_profit": null,
      "is_player_prop": false,
      "player_name": null,
      "stat_category": null,
      "possibly_stale": false,
      "oldest_odds_age_seconds": null,
      "warnings": [],
      "detected_at": "2026-02-08T14:22:10.456Z"
    },
    {
      "id": "ev_fd_nba_33483153_ml_PHO",
      "game_id": "evt_nba_phi_pho_20260208",
      "ev_percentage": 2.8,
      "odds_american": -108,
      "odds_decimal": 1.926,
      "no_vig_odds": -118,
      "fair_probability": 0.541,
      "market_width": 3.2,
      "devig_method": "power",
      "sharp_book": "pinnacle",
      "selection": "PHO Suns",
      "market": "moneyline",
      "line": null,
      "sportsbook": "fanduel",
      "game": "PHI 76ers vs PHO Suns",
      "sport": "basketball",
      "league": "nba",
      "home_team": "PHI 76ers",
      "away_team": "PHO Suns",
      "start_time": "2026-02-08T19:00:00Z",
      "is_live": false,
      "confidence_score": 82,
      "kelly_percent": 1.5,
      "book_count": 5,
      "arb_available": false,
      "arb_profit": null,
      "is_player_prop": false,
      "player_name": null,
      "stat_category": null,
      "possibly_stale": false,
      "oldest_odds_age_seconds": null,
      "warnings": [],
      "detected_at": "2026-02-08T14:22:10.456Z"
    }
  ],
  "pagination": {
    "limit": 50,
    "offset": 0,
    "has_more": false,
    "next_offset": null
  },
  "meta": {
    "source": "redis",
    "last_update": "2026-02-08T14:22:10.456Z",
    "summary": {
      "count": 24,
      "avg_ev": 3.8,
      "max_ev": 7.1,
      "by_sportsbook": {
        "draftkings": 9,
        "fanduel": 8,
        "betmgm": 7
      },
      "by_sport": {
        "basketball": 12
      },
      "by_market": {
        "moneyline": 5,
        "point_spread": 4,
        "player_points": 3
      }
    },
    "filters": {
      "sport": null,
      "league": ["nba"],
      "sportsbook": null,
      "market": null,
      "min_ev": 2.0,
      "max_ev": null,
      "live": null,
      "sort": "-ev",
      "include": null
    }
  }
}

Response Headers


X-RateLimit-Limit: 300
X-RateLimit-Remaining: 298
X-RateLimit-Reset: 1707401000
X-Data-Delay: 0
X-Request-Id: req_abc123def456

Error Responses

401 Unauthorized


{
  "error": {
    "code": "unauthorized",
    "message": "Invalid or missing API key",
    "docs": "https://docs.sharpapi.io/en/authentication"
  }
}

403 Feature Required


{
  "error": {
    "code": "feature_required",
    "message": "The 'ev' feature is required. Upgrade to Pro or higher.",
    "docs": "https://docs.sharpapi.io/en/pricing"
  }
}

429 Rate Limited


{
  "error": {
    "code": "rate_limited",
    "message": "Rate limit exceeded",
    "docs": "https://docs.sharpapi.io/en/api-reference/overview"
  }
}

Response Fields

Core Fields

Field	Type	Description
`id`	string	Unique opportunity identifier (hash)
`game_id`	string\|null	Associated game/event identifier
`external_event_id`	string\|null	Sportsbook’s native event ID
`selection_id`	string\|null	Sportsbook’s native outcome/selection ID (for deep linking to the bet slip)
`ev_percentage`	number	Expected value as a percentage (e.g., `4.2` = 4.2% EV). Deprecated alias: `ev_percent`.
`odds_american`	number	Current American odds at the sportsbook
`odds_decimal`	number	Decimal odds (e.g., `1.952`)
`no_vig_odds`	number\|null	Fair (no-vig) American odds derived from the sharp line
`fair_probability`	number\|null	No-vig (devigged) fair probability (0.0 to 1.0)
`market_width`	number\|null	Width of the market (vig indicator)
`devig_method`	string	De-vig method used (e.g., `power`)
`sharp_book`	string	Sharp book used as reference (e.g., `pinnacle`). Deprecated alias: `devig_book`.
`selection`	string	The selection (team name, Over/Under, player, etc.)
`market`	string	Market type (`moneyline`, `point_spread`, `total_points`, etc.)
`line`	number\|null	Spread/total line (e.g., `-3.5`, `220.5`)
`sportsbook`	string	Sportsbook offering these odds. Multiple entries may exist for the same selection if several books are +EV.
`game`	string	Human-readable game name
`sport`	string	Sport identifier (lowercase)
`league`	string	League identifier
`home_team`	string\|null	Home team name
`away_team`	string\|null	Away team name
`start_time`	string\|null	ISO 8601 event start time
`is_live`	boolean	Whether the event is currently live
`confidence_score`	number	Multi-factor confidence score (0-100)
`kelly_percent`	number\|null	Full-Kelly optimal bet percentage of bankroll (0–100, e.g. `2.1` = 2.1% of bankroll). Most practitioners apply a fractional Kelly multiplier (¼ or ½) before sizing — see Kelly Criterion below.
`book_count`	number	Number of sportsbooks offering this market
`arb_available`	boolean	Whether an arbitrage exists on this market
`arb_profit`	number\|null	Arbitrage profit percentage if available
`is_player_prop`	boolean	Whether this is a player prop market
`player_name`	string\|null	Player name (if player prop)
`stat_category`	string\|null	Stat type (if player prop, e.g., `points`, `rebounds`)
`possibly_stale`	boolean	`true` if underlying odds may have moved since detection
`oldest_odds_age_seconds`	number\|null	Age of the stalest odds used in the EV calculation (seconds)
`warnings`	string[]	Data quality warnings (e.g., `POTENTIALLY_STALE_ODDS`, `LIVE_STALE_ODDS`)
`detected_at`	string	ISO 8601 timestamp when the +EV was first detected

Meta Summary Fields

Field	Type	Description
`summary.count`	number	Total opportunities matching filters
`summary.avg_ev`	number	Average EV across all results
`summary.max_ev`	number	Highest EV found
`summary.by_sportsbook`	object	Opportunity count per sportsbook
`summary.by_sport`	object	Opportunity count per sport
`summary.by_market`	object	Opportunity count per market type

Understanding Expected Value

Expected Value (EV) measures the average profit or loss per bet over time. A positive EV (+EV) bet means you have a mathematical edge over the sportsbook.


EV% = (fair_probability x decimal_odds - 1) x 100

Where:

fair_probability = No-vig probability derived from the sharp book (Pinnacle)
decimal_odds = The decimal odds offered by the soft book

How SharpAPI Calculates EV

SharpAPI uses Pinnacle (a sharp book with efficient odds) as the source of truth for fair probability.

Step 1: Get the sharp book odds


Pinnacle: Team A -115 / Team B +105

Step 2: Remove the vig to find fair probability (Power method)


// Implied probabilities (with vig)
probA = 1 / 1.87 = 0.535  // -115 in decimal = 1.87
probB = 1 / 2.05 = 0.488  // +105 in decimal = 2.05
total = 1.023              // 2.3% vig
 
// Power devig: solve for k where probA^k + probB^k = 1
// k ≈ 1.036 for this market
fairProbA = 0.535^1.036 = 0.522 (52.2%)
fairProbB = 0.488^1.036 = 0.478 (47.8%)

Step 3: Compare to a soft book


DraftKings: Team A -105 (decimal 1.952)
Fair probability: 52.3%

EV% = (0.523 x 1.952 - 1) x 100
EV% = +2.1%

A +2.1% EV means you expect to profit $2.10 for every $100 wagered on this bet over time.

Why This Works

Book Type	Characteristics
Sharp (Pinnacle)	Low vig, efficient odds, accurate probabilities
Soft (DraftKings, FanDuel, BetMGM)	Higher vig, slower to adjust, exploitable

When soft books are slow to update their odds after a market move, their implied probability deviates from reality, creating a +EV opportunity.

EV Thresholds

EV %	Quality	Suggested Action
< 0%	Negative EV	Avoid
0 - 2%	Marginal	Only viable at high volume
2 - 5%	Good	Standard profitable threshold
5%+	Excellent	High confidence opportunities

We recommend setting min_ev=2 for most use cases. Marginal EV (below 2%) can be eroded by line movement before you place the bet.

Kelly Criterion

The kelly_percent field is the optimal percentage of your bankroll (0–100) to wager according to the full Kelly criterion. A value of 2.1 means full Kelly recommends 2.1% of bankroll; a value of 34.4 means 34.4%.


Kelly% = (fair_prob × decimal_odds - 1) / (decimal_odds - 1) × 100

This is full Kelly, computed from the model’s fair probability with no quality-of-signal adjustment. Full Kelly is mathematically optimal only when the true probability is known exactly. In practice, sharp anchors carry uncertainty (single sharp reference, late-arriving live odds, low cross-validation), and full Kelly can produce dangerously large stake suggestions. See confidence_score, cross_ref_count, and warnings (e.g. SINGLE_SHARP_REF, LIVE_STALE_ODDS) before sizing.

Use a fractional Kelly multiplier: most practitioners apply ¼ or ½ Kelly (kelly_percent × 0.25 or × 0.5). Cap any single bet at 1–2% of bankroll regardless of what kelly_percent reports, especially when warnings is non-empty or confidence_score < 80.

Kelly Sizing Guide

`kelly_percent`	Risk Level	Recommendation
< 1	Low	Small edge, consider skipping
1 – 3	Moderate	Standard bet size — quarter Kelly = 0.25–0.75% of bankroll
3 – 5	Aggressive	Strong edge — quarter Kelly = 0.75–1.25% of bankroll
5+	Very aggressive	Excellent edge or sharp-signal artifact; cap at 1–2% of bankroll regardless

Variance Warning: +EV does not guarantee profit on every bet. Over 100 bets at 5% EV, actual results can range widely. The edge only materializes over hundreds or thousands of bets. Never bet more than you can afford to lose.

Best Practices

Set a minimum EV threshold - Use min_ev=2 or higher to focus on meaningful edges
Use Kelly sizing - kelly_percent is a percentage (e.g. 2.1 = 2.1% of bankroll). Apply a fractional Kelly multiplier (¼ or ½) before sizing
Filter by confidence - Use confidence_score to prioritize high-confidence opportunities
Monitor market_width - Narrow markets (low width) indicate more efficient pricing and more reliable EV calculations
Act quickly - +EV opportunities are fleeting; lines move fast
Track your results - Log every bet and compare actual ROI to expected EV over time
Use fractional Kelly - Most professionals use quarter or half Kelly to reduce variance

Arbitrage Opportunities - Guaranteed profit across books
Low Hold Opportunities - Tightest lines across books
Middles - Line discrepancy opportunities
Best Odds - Find the best price across all books
EV Calculation Concepts - Deep dive into the math