+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, 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. 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.

AuthenticationPermalink for this section

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

Query ParametersPermalink for this section

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. The engine only surfaces opportunities above ~0.1% EV, so `min_ev=0` and omitting the parameter are equivalent.
`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 ValuesPermalink for this section

Use comma-separated values for multi-select filters:


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

Example RequestsPermalink for this section

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, pagination } = await response.json();
console.log(`Found ${pagination.total} +EV opportunities`);

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")

ResponsePermalink for this section

Success (200)Permalink for this section

Real response for GET /api/v1/opportunities/ev?limit=2 (live tennis, captured 2026-07-02):


{
  "data": [
    {
      "arb_available": false,
      "arb_profit": 0,
      "away_team": "Jiri Lehecka",
      "book_count": 8,
      "confidence": 85,
      "cross_ref_count": 1,
      "cross_ref_dispersion": null,
      "deep_link": "https://api.sharpapi.io/api/v1/deeplink/213493110750883",
      "detected_at": "2026-07-02T18:10:09.102807044Z",
      "devig_method": "POWER",
      "display_selection": "Over 27.5",
      "est_correction_s": 0,
      "ev_percentage": 14.85,
      "event_id": "tennis_men_alex_molcan_jiri_lehecka_2026-07-02",
      "event_name": "Jiri Lehecka @ Alex Molcan",
      "external_event_id": "34344853",
      "fair_probability": 0.2393,
      "home_team": "Alex Molcan",
      "id": "fbdcf59049c3d385",
      "is_alternate_line": false,
      "is_live": true,
      "is_player_prop": false,
      "kelly_percent": 3.91,
      "league": "atp",
      "line": 27.5,
      "market_id": "tennis_men_alex_molcan_jiri_lehecka_2026-07-02:total_games:27.5",
      "market_type": "total_games",
      "market_width": 4.781228895356837,
      "no_vig_odds": 318,
      "odds_american": 380,
      "odds_decimal": 4.8,
      "odds_probability": 0.2083,
      "oldest_odds_age_seconds": 1.7,
      "partner_fair_probability": 0.7607,
      "player_id": null,
      "player_name": null,
      "possibly_stale": false,
      "selection": "Over",
      "selection_id": "0QA348202437#2200852961_13L44337Q11374667207Q20",
      "sharp_book": "pinnacle",
      "single_sharp_period": false,
      "sport": "tennis",
      "sportsbook": "draftkings",
      "sportsbooks": [
        "draftkings"
      ],
      "start_time": "2026-07-02T15:40:00Z",
      "stat_category": null,
      "warnings": [
        "SINGLE_SHARP_REF"
      ]
    },
    {
      "arb_available": true,
      "arb_profit": 3.45,
      "away_team": "Jakub Mensik",
      "book_count": 4,
      "confidence": 80,
      "cross_ref_count": 1,
      "cross_ref_dispersion": null,
      "deep_link": "https://api.sharpapi.io/api/v1/deeplink/226072303819692",
      "detected_at": "2026-07-02T18:10:00.944122076Z",
      "devig_method": "POWER",
      "display_selection": "Under 44.5",
      "est_correction_s": 29,
      "ev_percentage": 14.38,
      "event_id": "tennis_men_grigor_dimitrov_jakub_mensik_2026-07-02",
      "event_name": "Jakub Mensik @ Grigor Dimitrov",
      "external_event_id": "1028209623",
      "fair_probability": 0.4485,
      "home_team": "Grigor Dimitrov",
      "id": "2385ab8c057dcd49",
      "is_alternate_line": false,
      "is_live": true,
      "is_player_prop": false,
      "kelly_percent": 9.27,
      "league": "atp",
      "line": 44.5,
      "market_id": "tennis_men_grigor_dimitrov_jakub_mensik_2026-07-02:total_games:44.5",
      "market_type": "total_games",
      "market_width": 4.8401734395482565,
      "no_vig_odds": 123,
      "odds_american": 155,
      "odds_decimal": 2.55,
      "odds_probability": 0.3922,
      "oldest_odds_age_seconds": 3.2,
      "partner_fair_probability": 0.5515,
      "player_id": null,
      "player_name": null,
      "possibly_stale": false,
      "selection": "Under",
      "selection_id": "4244429455",
      "sharp_book": "pinnacle",
      "single_sharp_period": false,
      "sport": "tennis",
      "sportsbook": "ballybet",
      "sportsbooks": [
        "ballybet"
      ],
      "start_time": "2026-07-02T15:55:00Z",
      "stat_category": null,
      "warnings": [
        "SINGLE_SHARP_REF"
      ]
    }
  ],
  "pagination": {
    "count": 2,
    "has_more": true,
    "limit": 2,
    "next_cursor": "eyJ2IjoxNC4zOCwiaSI6IiJ9",
    "next_offset": 2,
    "offset": 0,
    "total": 351
  },
  "updated_at": "2026-07-02T18:10:19.758741204Z"
}

Response HeadersPermalink for this section


X-RateLimit-Limit: 300
X-RateLimit-Remaining: 298
X-RateLimit-Reset: 1707401000
X-Data-Delay: 0
X-Request-Id: 1783016224442558-9486

Error ResponsesPermalink for this section

401 Unauthorized

No key supplied returns missing_api_key; a bad key returns invalid_api_key.


{
  "error": {
    "code": "missing_api_key",
    "message": "API key required. Pass via X-API-Key header, api_key query parameter, or Bearer token.",
    "docs": "https://sharpapi.io/docs/authentication"
  }
}

403 Tier Restricted


{
  "error": {
    "code": "tier_restricted",
    "message": "This endpoint requires Pro tier or higher",
    "docs": "https://sharpapi.io/pricing",
    "tier": "hobby",
    "required_tier": "pro"
  }
}

429 Rate Limited

retry_after is a Unix-millisecond timestamp of the next window (not a duration); the Retry-After header carries the equivalent seconds value.


{
  "error": {
    "code": "rate_limited",
    "message": "Rate limit exceeded for pro tier (300/min)",
    "retry_after": 1737853260000,
    "tier": "pro",
    "limit": 300,
    "docs": "https://sharpapi.io/pricing"
  }
}

Response FieldsPermalink for this section

Core FieldsPermalink for this section

Field	Type	Description
`id`	string	Unique opportunity identifier (hash)
`event_id`	string\|null	Associated 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)
`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)
`partner_fair_probability`	number\|null	The complementary side’s fair probability from the same devig call — on 2-way markets `fair_probability + partner_fair_probability = 1.0`. `null` on n-way markets or when the partner side couldn’t be resolved.
`market_width`	number\|null	Width of the market (vig indicator)
`devig_method`	string	De-vig method used, uppercase (e.g. `POWER`)
`sharp_book`	string	Sharp book used as the devig reference (e.g., `pinnacle`; `circa` is also used). Override via the `devig_book` query param.
`cross_ref_count`	number	Number of sharp reference books that priced this market. `1` = single sharp ref (see the `SINGLE_SHARP_REF` warning).
`cross_ref_dispersion`	number\|null	Spread (max − min) of devigged fair probabilities across the sharp reference books, in percentage points. `null` when fewer than 2 sharp refs priced the market.
`selection`	string	The selection (team name, Over/Under, player, etc.)
`display_selection`	string	Human-readable selection including the line (e.g. `"Over 27.5"`, `"PHI 76ers -3.5"`)
`market_type`	string	Market type (`moneyline`, `point_spread`, `total_points`, etc.)
`market_id`	string\|null	Canonical market identifier for this row’s market group (joins sibling selections of the same market)
`market_segment`	string\|undefined	Contest slice (`full_game`, `1st_half`, `1st_5_innings`, `set_1`, …). Omitted when the adapter didn’t derive a segment.
`team_side`	string\|undefined	Raw side per the adapter (`home` \| `away` \| `draw` \| `over` \| `under`). Omitted when not stamped.
`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.
`event_name`	string	Human-readable event name (e.g. “Away @ Home”)
`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
`is_alternate_line`	boolean	`true` when this opportunity’s `line` differs from the market’s canonical main line. Markets with no line (moneyline, outright) always emit `false`.
`confidence`	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)
`player_id`	string\|null	Canonical cross-book player ID (e.g. `baseball_mlb_corbin_carroll`), resolved by atlas_players. `null` until resolved — group player props on `player_id` and fall back to `player_name`.
`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)
`est_correction_s`	number\|null	Estimated seconds until the bet-side book corrects toward the sharp move (P50 follow-lag for this sportsbook+sport). `null` when no sample is available.
`warnings`	string[]	Data quality warnings (e.g., `POTENTIALLY_STALE_ODDS`, `LIVE_STALE_ODDS`, `SINGLE_SHARP_REF`, `SINGLE_SHARP_PERIOD`)
`single_sharp_period`	boolean	`true` when only one sharp book priced the line and the market is a period/derivative sub-slice (innings, halves, quarters, sets). Filterable flag for phantom-suspect period EV; mirrors the `SINGLE_SHARP_PERIOD` warning.
`quality_tier`	string\|undefined	Grader-certified quality label — `A` (bet-this), `B` (edge), or `C` (informational). Present on every opportunity; omitted on suspended rows (`is_suspended`). Output-only — there is no `quality_tier` query filter. See Quality Tier below for the criteria.
`is_suspended`	boolean\|undefined	`true` (omitted otherwise) when the sharp reference is currently suspended live: the bet is still offerable but the edge is unknown, so `ev_percentage`, `fair_probability`, `no_vig_odds`, `kelly_percent`, and `market_width` are `null`ed rather than shown stale. `suspended_since` (Unix epoch seconds) accompanies it.
`detected_at`	string	ISO 8601 timestamp when the +EV was first detected
`odds_probability`	number	Implied probability of `odds_american` (vig-included)
`sportsbooks`	string[]	All sportsbooks currently offering this +EV selection
`deep_link`	string\|undefined	Resolver URL to the sportsbook bet slip (pass `state=` for state subdomains)
`home`	object\|undefined	Reserved — not currently emitted on this endpoint. Nested home-team reference: `{id, numerical_id, name, abbreviation, logo, city, mascot, conference, division}`. See Entity reference IDs.
`away`	object\|undefined	Reserved — not currently emitted on this endpoint. Nested away-team reference (same shape as `home`).
`sport_ref`	object\|undefined	Reserved — not currently emitted on this endpoint. Nested sport reference: `{id, numerical_id, name}`.
`league_ref`	object\|undefined	Reserved — not currently emitted on this endpoint. Nested league reference: `{id, numerical_id, label}`.
`market_ref`	object\|undefined	Reserved — not currently emitted on this endpoint. Nested market reference: `{id, numerical_id, label}`.
`sportsbook_ref`	object\|undefined	Reserved — not currently emitted on this endpoint. Nested sportsbook reference: `{id, numerical_id, label}`.

Nested reference blocks (reserved)Permalink for this section

The response schema reserves six nested reference objects (home, away, sport_ref, league_ref, market_ref, sportsbook_ref) mirroring the blocks on /odds. As of 2026-07-02 the EV engine does not stamp them, so live /opportunities/ev rows never include these blocks — today they appear only on /odds rows for atlas-mapped books. Treat every block (and every inner field) as optional and never require them; when the EV pipeline is wired to emit them, they will appear additively without changing any existing flat field. See Entity reference IDs for the shape and the dense-from-1 / frozen / never-reused guarantees.

Understanding Expected ValuePermalink for this section

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 EVPermalink for this section

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 WorksPermalink for this section

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 ThresholdsPermalink for this section

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.

Quality TierPermalink for this section

Every opportunity carries a quality_tier — a grader-certified A / B / C label that supersedes the rough EV Thresholds heuristic above with evidence from SharpAPI’s historical grading ledger. It answers “how much should I trust this edge?”, not just “how big is the stated EV?”

Tier	Meaning	Criteria
A	Bet this	`ev_percentage` ≥ 4 (≥ 6 for player props), Pinnacle-anchored (`sharp_book: "pinnacle"`), prematch (`is_live: false`), and the `(book, sport, market)` segment is not flagged by our nightly reliability model. Historically the only class with consistently positive graded ROI.
B	Edge	`ev_percentage` ≥ 2 (≥ 4 for props) and the segment is not exclusion-flagged. Includes live, non-Pinnacle-anchored, and watch-flagged rows that clear the band — historically around break-even.
C	Informational	Everything else, plus any exclusion-flagged segment regardless of EV. Disclosed as market intelligence, not a recommended bet.

quality_tier is output-only — there is no quality_tier query parameter. Filter client-side. min_ev / live / sportsbook are only partial proxies: min_ev alone does not reproduce a tier, because the sharp anchor, prematch/live state, and segment reliability also gate it.

A high ev_percentage does not guarantee tier A. Two prematch, Pinnacle-anchored baseball totals from the same book illustrate why:

Selection	`ev_percentage`	`quality_tier`	Why
1st 5 Innings Total Runs — Over 5	7.35	A	Segment unflagged
Total Runs — Over 9	7.94	B	Higher EV, but the full-game `total_runs` segment is watch-flagged for historically weak results

The higher-EV row is B, not A, because our reliability model has seen that segment underperform — exactly the “big EV number that’s actually the artifact” the tiering is designed to demote. See EV Calculation → Quality Tiers for the grading rationale behind the bands.

A tier is not a profit guarantee. Even tier A carries variance (see Kelly Criterion and the Variance Warning below). Suspended rows (is_suspended: true) carry no tier — their edge is unknown, so no quality claim is made.

Kelly CriterionPermalink for this section

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, 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 < 80.

Kelly Sizing GuidePermalink for this section

`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 PracticesPermalink for this section

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 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