MCP Server

Lumify Sports Intelligence

ai.lumify/sports-intelligence
Data & Analytics Public & reachable MCP 2025-11-25

What this MCP does

Provides sports schedules, scores, odds, statistical splits, and explainable betting-confidence information across multiple sports.

batch_get_events
Get multiple events by id in one call — for agents that already have a list of ids and want full detail for each without one call per event. Max 25 ids. Returns full detail for every id that exists plus a not_found list for any that don't (never billed). Use get_event for a single id, or list_events / query_events to discover ids first.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_ids'], 'properties': {'bookmaker': {'type': 'string', 'description': 'Bookmaker for inlined odds and intelligence market prices. Defaults to pinnacle. Valid: pinnacle, fanduel, draftkings, betmgm, caesars, bet365, circa, westgate, wynn, south_point, stations, hardrock, betonline, betr, betrivers, lowvig, bovada, all.'}, 'event_ids': {'type': 'array', 'items': {'type': 'integer'}, 'maxItems': 25, 'description': 'Event ids to fetch (max 25); duplicates are billed once.'}, 'include_odds': {'type': 'boolean', 'default': False, 'description': 'Inline current odds scoped by bookmaker (default: pinnacle). Does not add credits — each found event stays 1 credit.'}, 'include_intelligence': {'type': 'boolean', 'default': False, 'description': 'Inline bet intelligence on each event. Does not add credits.'}}}
Output schema
{'type': 'object', 'properties': {'total': {'type': 'integer'}, 'events': {'type': 'array', 'items': {'type': 'object'}, 'description': 'Full event detail (same shape as get_event) for every found id.'}, 'not_found': {'type': 'array', 'items': {'type': 'integer'}, 'description': "Requested event_ids that don't exist. Never billed."}}}
estimate_cost
Estimate the credit cost of one or more planned tool calls before making them — no credits are spent. Costs are data-dependent (e.g. odds/intelligence/splits not yet ingested for an event are free, and batch_get_events ids that don't exist cost nothing), so this returns a [min_credits, max_credits] range per call rather than a single number. Pass the exact tool name and arguments you're considering, e.g. {"tool": "get_event", "arguments": {"event_id": 123, "include_odds": true}}.
Read only Idempotent
Input schema
{'type': 'object', 'required': ['calls'], 'properties': {'calls': {'type': 'array', 'items': {'type': 'object', 'required': ['tool'], 'properties': {'tool': {'type': 'string', 'description': 'Tool name to estimate, e.g. get_event, batch_get_events, get_odds.'}, 'arguments': {'type': 'object', 'description': "Same arguments you'd pass to that tool."}}}, 'maxItems': 50, 'minItems': 1}}}
Output schema
{'type': 'object', 'properties': {'estimates': {'type': 'array', 'items': {'type': 'object', 'properties': {'note': {'type': ['string', 'null']}, 'tool': {'type': 'string'}, 'max_credits': {'type': 'integer'}, 'min_credits': {'type': 'integer'}}}}, 'total_max_credits': {'type': 'integer'}, 'total_min_credits': {'type': 'integer'}}}
get_event
Get a single event with participants and venue. Optionally inline current odds and/or bet intelligence (same 1 credit as the event call). Raises a not-found error if event_id doesn't exist. Use list_events / query_events to discover ids first, or batch_get_events to fetch several ids in one call.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}, 'bookmaker': {'type': 'string', 'description': 'Bookmaker for inlined odds and intelligence market prices. Defaults to pinnacle. Valid: pinnacle, fanduel, draftkings, betmgm, caesars, bet365, circa, westgate, wynn, south_point, stations, hardrock, betonline, betr, betrivers, lowvig, bovada, all.'}, 'include_odds': {'type': 'boolean', 'default': False, 'description': 'Inline current odds scoped by bookmaker (default: pinnacle). Does not add credits — the event call stays 1 credit.'}, 'include_intelligence': {'type': 'boolean', 'default': False, 'description': 'Inline bet intelligence. Does not add credits.'}}}
Output schema
{'type': 'object', 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'sport': {'type': 'string'}, 'venue': {'type': ['object', 'null']}, 'league': {'type': 'string'}, 'status': {'type': 'string'}, 'starts_at': {'type': 'string'}, 'updated_at': {'type': ['string', 'null']}, 'participants': {'type': 'array', 'items': {'type': 'object', 'properties': {'role': {'type': 'string'}, 'team': {'type': ['object', 'null']}, 'score': {'type': ['string', 'null']}, 'player': {'type': ['object', 'null']}, 'is_winner': {'type': ['boolean', 'null']}, 'participant_id': {'type': 'integer'}}}}, 'inprogress_since': {'type': ['string', 'null'], 'description': 'ISO-8601 UTC when status first became inprogress (first live tick). Null until then; stays set after final.'}}}
get_injuries
Beta. Get late-breaking player injury and availability status for an event (out / doubtful / questionable / probable / day_to_day / ir / suspended / available), with previous_status, body_part, note, source_url, and severity (info / material / critical). Beta coverage: NFL and MLB (more sports rolling out). NFL monitoring starts ~4.5 days before kickoff (Wednesday/Thursday practice reports); MLB stays on a 48-hour window. Returns available:false with no charge until the injury monitor has written a first structured report. Checks run on cadence, on a significant main-market odds move, and at a guaranteed pre-kickoff checkpoint. Subscribe to webhook event_type=injury for material/critical changes. No in-game feed. Use exclude_status to drop noisy long-standing designations (e.g. ir) from the response — does not affect available or credit cost.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}, 'exclude_status': {'type': 'string', 'description': 'Comma-separated statuses to drop, e.g. "ir" to hide injured-reserve/long-term-IL rows (long-standing roster designations, not late-breaking news). Valid values: out, doubtful, questionable, probable, day_to_day, ir, suspended, available.'}}}
Output schema
{'type': 'object', 'properties': {'event_id': {'type': 'integer'}, 'injuries': {'type': 'array', 'items': {'type': 'object'}, 'description': "Per-player rows: player, player_id, team, team_id, status, previous_status, body_part, note, source_url, severity, last_changed_at. team/team_id prefer the player's current roster team when that team is a participant in this event."}, 'available': {'type': 'boolean'}, 'confirmed_at': {'type': ['string', 'null']}, 'next_check_at': {'type': ['string', 'null']}, 'last_checked_at': {'type': ['string', 'null']}}}
get_intelligence
Get predictive bet intelligence for an event: vig-stripped probability, fair_price, Price overlay, main-line ev (Beta), and forecasts[] — forecasted wagers from the model (same objects as list_forecasts): player props plus high-confidence main-line picks on tennis, NFL, NCAAF, MLB, and soccer. bets[] is live for MLB, tennis, soccer (MLS + big-five), NFL, and NCAAF. forecasts[] covers MLB, NFL, NCAAF, NBA, NCAAB, NHL, tennis, and soccer and can populate when available is false. Fair-price + line-shopping on bets[] today (edge/tier null; has_recommend false). bookmaker is ignored. Match-level tokens (OVER, UNDER, ML_DRAW) have null player/team attribution. Free only when available is false and forecasts is empty. Field catalog: https://lumify.ai/docs/reference#event-intelligence
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}, 'bookmaker': {'type': 'string', 'description': 'Ignored. Intelligence always reports the book the assessment was priced against. Valid: pinnacle, fanduel, draftkings, betmgm, caesars, bet365, circa, westgate, wynn, south_point, stations, hardrock, betonline, betr, betrivers, lowvig, bovada.'}}}
Output schema
{'type': 'object', 'properties': {'bets': {'type': 'array', 'items': {'type': 'object', 'properties': {'ev': {'type': ['object', 'null'], 'description': 'Beta. Customer-facing EV estimate: {beta: true, book, price, ev_pct, kelly_fraction, quote_age_seconds, n_books}. Re-packages the same fair price gap for direct display. Moneyline only. n=1 Pinnacle is a valid fair (soccer/tennis). Null when the gap is ≤0, above 25% (stale-line), or only suppressed books remain (MLB ML × DK/FD proven null; BetMGM/Bet365/BetOnline unscreened).'}, 'best': {'type': ['object', 'null'], 'description': 'Highest price-gap book across edges_by_book: {book, price, edge, quote_age_seconds}. Tier C informational line-shopping.'}, 'edge': {'type': ['number', 'null'], 'description': 'Expected profit per 1 unit staked at market.price. Null while no model-backed edge is published (Stage 1). Present on customer surface for recommend gating.'}, 'fair': {'type': ['object', 'null'], 'description': 'Sharp-consensus fair: {probability, books, n_books, is_consensus}. MLB/NFL: Pinnacle+Circa; MLS/tennis: Pinnacle. Price-gap reference for edges_by_book/best.'}, 'tier': {'type': ['string', 'null'], 'description': "Confidence tier: 'very_high', 'strong', 'moderate', or 'avoid'. Null whenever edge is null. Present on MLB customer surface and all other shapes."}, 'phase': {'type': ['string', 'null'], 'description': 'Internal — omitted from customer payloads (MLB/soccer/tennis).'}, 'market': {'type': ['object', 'null'], 'description': 'Market quote: {price: American odds, line: handicap/total line or null for moneyline, book: bookmaker slug when known (always set for probability-model sports)}.'}, 'blend_w': {'type': ['number', 'null'], 'description': 'Internal — omitted from customer payloads (MLB/soccer/tennis).'}, 'drivers': {'type': 'array', 'items': {'type': 'object'}, 'description': 'Internal — omitted from customer payloads (MLB/soccer/tennis).'}, 'p_model': {'type': ['number', 'null'], 'description': 'Internal — omitted from customer payloads (MLB/soccer/tennis).'}, 'signals': {'type': ['object', 'null'], 'description': 'Not published.'}, 'team_id': {'type': ['integer', 'null'], 'description': 'Set when this bet is about a team. Null for match-level tokens (OVER, UNDER, ML_DRAW) — a draw is not a bet on either team, so summing exposure by team_id never double-counts it.'}, 'bet_type': {'type': 'string', 'description': 'Canonical bet token, e.g. ML_HOME/ML_AWAY/ML_DRAW (soccer), ML_P1/ML_P2 (head-to-head sports), SPREAD_HOME/SPREAD_AWAY, OVER, UNDER.'}, 'coverage': {'type': ['number', 'null'], 'description': 'Not published.'}, 'interval': {'type': ['array', 'null'], 'items': {'type': 'number'}, 'description': '[lo, hi] band around probability — how much evidence backs the number, not a statistical confidence interval.'}, 'p_market': {'type': ['number', 'null'], 'description': 'Internal — omitted from customer payloads (MLB/soccer/tennis). Use probability/fair_price.'}, 'alignment': {'type': ['object', 'null'], 'description': 'Internal — omitted from customer payloads (MLB/soccer/tennis).'}, 'narrative': {'type': ['string', 'null'], 'description': 'Pick-defense rationale for a selected main-line side. Present only when a matching forecasts[] row is selected: true. Null when no pick was made on this token.'}, 'player_id': {'type': ['integer', 'null'], 'description': 'Set when this bet is about an individual player. Null for team bets and match-level tokens.'}, 'rationale': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Not published. Top-level rationale is the event-level context overlay.'}, 'validator': {'type': ['object', 'null'], 'description': 'Not published.'}, 'fair_price': {'type': ['integer', 'null'], 'description': "American-odds fair price implied by probability — the vig-free line. Compare to market.price for the book's margin on this side."}, 'attribution': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Not published.'}, 'computed_at': {'type': ['string', 'null'], 'description': "ISO-8601 UTC time this bet's numbers last materially changed — not when last checked. Rows are only rewritten when price, line, or probability moves beyond a tolerance, so an older value means 'unchanged since', not 'stale'. Differs between bets on one event because markets move independently."}, 'player_name': {'type': ['string', 'null'], 'description': 'Display name of the player or team this bet is about. Null for match-level tokens. Duplicates players[player_role].name.'}, 'player_role': {'type': ['string', 'null'], 'description': "'home'/'away' or 'p1'/'p2'. Null for match-level tokens (OVER, UNDER, ML_DRAW)."}, 'probability': {'type': ['number', 'null'], 'description': 'Published probability for this outcome, 0-1. Outcomes of one market sum to 1. Customer surface for MLB, soccer, tennis, NFL.'}, 'sufficiency': {'type': ['number', 'null'], 'description': 'Internal — omitted from customer payloads (MLB/soccer/tennis).'}, 'edges_by_book': {'type': ['object', 'null'], 'description': 'Price gap versus fair.probability per soft book (fair.probability × decimal_odds − 1). Line-shopping metric: rank soft books by gap.'}, 'model_version': {'type': ['string', 'null'], 'description': 'Internal — omitted from customer payloads (MLB/soccer/tennis).'}, 'confidence_score': {'type': ['number', 'null'], 'description': 'Not published. Use probability.'}}}}, 'sport': {'type': ['string', 'null'], 'description': 'Sport slug for this event.'}, 'league': {'type': ['string', 'null'], 'description': 'League slug for this event, if any.'}, 'matchup': {'type': ['object', 'null'], 'description': 'Not returned. Use get_stats for pitcher/lineup Data.'}, 'players': {'type': 'object', 'description': 'Home/away (or p1/p2) participant identification, keyed by role: {role: {name, player_id, team_id}}.'}, 'event_id': {'type': 'integer', 'description': 'Lumify event ID this intelligence describes.'}, 'available': {'type': 'boolean', 'description': 'False when no predictive bets[] have been computed for this event yet. forecasts[] can still populate on MLB/NFL/NCAAF/NBA/NCAAB/NHL. Free only when available is false and forecasts is empty.'}, 'forecasts': {'type': 'array', 'items': {'type': 'object', 'properties': {'line': {'type': ['number', 'null'], 'description': 'Posted line the model was scored against. Prop and totals main-line rows: Over/Under number. Spreads main-line rows: the spread number. Null on h2h/moneyline rows.'}, 'side': {'type': ['string', 'null'], 'description': "Prop rows: 'over' or 'under' — the more likely side given the player's shrunken rate versus line. Null on main-line rows — read the picked outcome from bet_type instead."}, 'books': {'type': 'object', 'description': 'American price for the picked outcome, keyed by bookmaker slug (e.g. {draftkings: -453}). Posted market price for the side/bet_type the model picked.'}, 'p_hit': {'type': 'number', 'description': "Model probability (0–1) that the picked outcome (side on prop rows, bet_type on main-line rows) hits. Prop rows: built from the player's shrunken counting-stat rate (Poisson vs the posted Over/Under). Optional research may nudge a prop's p_hit by at most ±0.03; the chosen side stays the same."}, 'sport': {'type': ['string', 'null'], 'description': 'Sport slug. Slate only.'}, 'league': {'type': ['string', 'null'], 'description': 'League slug, if any. Slate only.'}, 'market': {'type': 'string', 'description': 'Player-prop rows: prop category (counting stats). MLB: strikeouts_pitcher, hits, rbis, runs, strikeouts_batter, hits_allowed, earned_runs, outs_recorded. NFL/NCAAF: passing/rushing/receiving_yards, receptions, passing_tds, rushing_tds, touchdowns (anytime-TD combo: rushing + receiving + defensive TDs), rush_rec_yards, pass_rush_yards. NBA/NCAAB: points, rebounds, assists, steals, blocks, threes_made. NHL: goals, hockey_assists, shots_on_goal. Main-line rows (bet_type set): the main-line family — h2h, spreads, or totals.'}, 'player': {'type': ['string', 'null'], 'description': 'Player display name from the priced line. Null on main-line rows with no player attribution (bet_type is a match-level token like OVER/UNDER/ML_DRAW).'}, 'drivers': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': 'string', 'description': 'Prop rows: typically player.l10_rate — the recent-form rate that fed Poisson. Main-line rows would use a different namespace once a main-line forecast model ships.'}, 'input': {'type': ['number', 'null'], 'description': 'Measured rate/rating behind this driver, in native units.'}, 'effect': {'type': 'number', 'description': 'Signed shift in p_hit versus a baseline case on the same line. 0.0 on yardage markets.'}, 'direction': {'type': 'string', 'description': 'up / down / neutral from the sign of effect.'}}}, 'description': 'Signed contributions that moved p_hit. Read input as the measured rate/rating behind the pick and effect as how far it lifts the chosen outcome versus a baseline.'}, 'bet_type': {'type': ['string', 'null'], 'description': "Main-line token when this row is a main-line forecast — ML_P1/ML_P2/ML_HOME/ML_AWAY/ML_DRAW, SPREAD_P1/SPREAD_P2/SPREAD_HOME/SPREAD_AWAY, or OVER/UNDER (same vocabulary as get_intelligence bets[].bet_type and list_ev). Null on player-prop rows — that's the discriminator between the two row shapes. Tennis sets ML_P1/ML_P2 (moneyline), SPREAD_P1/SPREAD_P2 (game handicap), and OVER/UNDER (total games)."}, 'event_id': {'type': ['integer', 'null'], 'description': 'Lumify event ID. Present on list_forecasts; omitted on get_intelligence.forecasts (the event is the argument).'}, 'interval': {'type': 'array', 'items': {'type': 'number'}, 'description': '[lo, hi] stated band around p_hit. Wider when sufficiency is low. A stated evidence band, not a statistical confidence interval.'}, 'research': {'type': ['object', 'null'], 'description': 'Optional Deep Research overlay when the background job has written a row for this wager — every wager on the daily board (selected: true), plus other high-probability wagers (p_hit ≥ 0.80) in the catalog: {stance, conviction, note}. stance is validate / neutral / invalidate. note is the wager-level why — on a selected main-line row it is also copied to bets[].narrative. Validate / invalidate rows always carry a note. Validate nudges p_hit up by at most 0.03 and lifts conviction. Invalidate drops the wager from forecasts[] and the daily board — it is not a recommended pick. The chosen side stays. Null means read p_hit from the rate model alone.'}, 'selected': {'type': 'boolean', 'description': 'True when this wager is on the daily board (top conviction). On get_intelligence the array includes selected and the rest of the event catalog.'}, 'away_team': {'type': ['string', 'null'], 'description': 'Away team display name. Slate only.'}, 'home_team': {'type': ['string', 'null'], 'description': 'Home team display name. Slate only.'}, 'player_id': {'type': ['integer', 'null'], 'description': 'Lumify player ID. Bound by exact / Jr-stripped name match. Null on main-line rows with no player attribution.'}, 'conviction': {'type': 'number', 'description': 'Board rank key on 0–1: |p_hit−0.5|×2×sufficiency×research. A high p_hit on a thin sample ranks below a moderate p_hit on a long one. Highest conviction first on the daily slate.'}, 'player_role': {'type': ['string', 'null'], 'description': "'home'/'away' for team sports or 'p1'/'p2' for head-to-head sports, set only alongside a non-null bet_type. Null for player-prop rows and for match-level main-line tokens (OVER, UNDER, ML_DRAW)."}, 'reliability': {'type': 'string', 'description': 'Badge on this sport×market cell: emerging, moderate, high, or informational. v0 ships emerging for every wager.'}, 'sufficiency': {'type': 'number', 'description': "Evidence weight on 0–1: n/(n+12), where n is the recent-form game count (typically L10). A player with 10 games has sufficiency ≈ 0.45. The wager still ships; this field tells you how much of p_hit is earned from this player's own boxes."}, 'commence_time': {'type': ['string', 'null'], 'description': 'ISO-8601 UTC scheduled start. Slate only.'}, 'model_version': {'type': 'string', 'description': 'Scorer version, e.g. forecast-v0.'}}}, 'description': 'Forecasted wagers for this event (same object as list_forecasts) — a model prediction, not a beat-the-market claim. Player-prop rows on team sports; high-confidence main-line picks on tennis, NFL, NCAAF, MLB, and soccer via bet_type (ML_P1/ML_P2/ML_HOME/ML_AWAY/ML_DRAW, SPREAD_*/OVER/UNDER). selected marks the pick — high-confidence main-lines and the top-conviction prop rows on the daily slate. Coin-flip main-lines are not picked. A selected main-line research.note is copied to bets[].narrative. Read p_hit as P(the picked outcome hits). How + field catalog: https://lumify.ai/docs/forecasts'}, 'rationale': {'type': ['array', 'null'], 'items': {'type': 'string'}, 'description': 'Event-level factual pre-game matchup chips (injuries, recent form, lineup/availability news — sport-shaped). Written before kickoff; the request path only reads the stored row.'}, 'odds_source': {'type': ['string', 'null'], 'description': 'Bookmaker bets[].market prices were sourced from. For probability-model sports this is the book the assessment was priced against, not a bookmaker overlay; per-bet market.book is authoritative if they ever differ.'}, 'has_recommend': {'type': ['boolean', 'null'], 'description': 'True when at least one bet meets the recommendation threshold; null when intelligence has not been computed. False while Edge is not published (current MLB/soccer/tennis Stage 1) — a recommendation requires a non-null tier derived from edge.'}, 'match_overview': {'type': ['string', 'null'], 'description': 'Natural-language pre-game matchup preview — form, context, what to watch. Written before kickoff by a Search-backed overlay on every event sport (MLB, NFL, NCAAF, NBA, NCAAB, NHL, soccer, tennis); sport-shaped queries. The request path only reads the stored row. Null when the pre-kickoff job has not run or the fixture was not eligible.'}, 'intelligence_updated_at': {'type': ['string', 'null'], 'description': 'ISO-8601 UTC timestamp of the most recent change anywhere in this payload (max of per-bet computed_at). Use per-bet computed_at to reason about a specific bet.'}}}
get_live_score
Get a lightweight live score snapshot for an event: status, period, clock, per-participant score and period-by-period scores, and last-updated time. Cheaper and faster than get_event when you only need the score, not participants or venue. Capped at 20 calls/min per key (shared with GET /v1/events/{id}/score and list_events include_scores=true). For live updates prefer the SSE stream. Raises a not-found error if event_id doesn't exist.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}}}
Output schema
{'type': 'object', 'properties': {'clock': {'type': ['string', 'null']}, 'period': {'type': ['string', 'null']}, 'scores': {'type': 'array', 'items': {'type': 'object', 'properties': {'name': {'type': 'string'}, 'role': {'type': 'string'}, 'score': {'type': ['string', 'null']}, 'is_winner': {'type': ['boolean', 'null']}, 'abbreviation': {'type': ['string', 'null']}, 'period_scores': {'type': 'array', 'items': {'type': 'object'}}}}}, 'status': {'type': 'string'}, 'event_id': {'type': 'integer'}, 'finished': {'type': 'boolean'}, 'updated_at': {'type': ['string', 'null']}}}
get_odds
Get current betting odds for an event: per-bookmaker lines and last-updated time. Includes in-play quotes while the event is underway; books that have not quoted since kickoff are omitted. bookmaker defaults to pinnacle. Use 'all' or a comma-separated list for multiple books — still 1 credit. Default is main lines (is_main=true); set include_alts for alternate spread/total rungs. Final events include result (won/lost/push/void) graded from the pre-kickoff close. MLB, tennis, and soccer (MLS + big-five) mains also include fair_price and consensus mirrored from published assessments. Returns available:false with no charge if odds aren't posted for this event yet. If bookmaker is omitted and Pinnacle hasn't posted a line yet (common for the first/last games of a preseason slate), falls back to the best-covered other book and adds requested_bookmaker='pinnacle' plus fallback_bookmaker to the response instead of reporting no odds; an explicit bookmaker='pinnacle' never falls back. Use get_odds_history for line movement over time.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}, 'bookmaker': {'type': 'string', 'description': 'Bookmaker slug. Defaults to pinnacle. Valid: pinnacle, fanduel, draftkings, betmgm, caesars, bet365, circa, westgate, wynn, south_point, stations, hardrock, betonline, betr, betrivers, lowvig, bovada, all, or a comma-separated list.'}, 'include_alts': {'type': 'boolean', 'description': 'Include alternate spread/total rungs. Default false (mains only).'}}}
Output schema
{'type': 'object', 'properties': {'event_id': {'type': 'integer'}, 'available': {'type': 'boolean'}, 'bookmakers': {'type': 'array', 'items': {'type': 'object'}, 'description': 'Per-book markets. Outcomes include is_main. In-play omits books that have not quoted since kickoff. Final events add result (won/lost/push/void) and close on the pre-kickoff point.'}, 'last_updated': {'type': ['string', 'null']}, 'fallback_bookmaker': {'type': 'string', 'description': 'The book actually returned when requested_bookmaker is present.'}, 'requested_bookmaker': {'type': 'string', 'description': "Present only when the default (no bookmaker arg) request fell back to a different book because Pinnacle has no line yet — always 'pinnacle' when present."}}}
get_odds_history
Get line-movement history for an event: a list of past odds snapshots (movements), each with its own timestamp, up to limit entries. bookmaker defaults to pinnacle. Use get_odds instead if you only need the current line.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'limit': {'type': 'integer', 'default': 50, 'description': 'Max line-movement entries to return. Default 50.'}, 'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}, 'bookmaker': {'type': 'string', 'description': 'Bookmaker slug. Defaults to pinnacle. Valid: pinnacle, fanduel, draftkings, betmgm, caesars, bet365, circa, westgate, wynn, south_point, stations, hardrock, betonline, betr, betrivers, lowvig, bovada, all, or a comma-separated list.'}}}
Output schema
{'type': 'object', 'properties': {'total': {'type': 'integer'}, 'event_id': {'type': 'integer'}, 'movements': {'type': 'array', 'items': {'type': 'object'}, 'description': 'Odds snapshots over time; each entry carries its own timestamp.'}}}
get_period_odds
Get first-half / first-five / first-set lines and live progress for an NFL, NCAAF, NBA, NCAAB, MLB, soccer, or tennis event. Joins persisted first_half_spreads / first_half_totals mains to this-event period scores (1H = Q1+Q2, NCAAB or soccer native 1H; MLB F5 = innings 1–5; tennis S1 = first-set games) and grades the period, not the full game. GET /odds / get_odds stay on moneyline/spread/total. Returns available:false with no charge if no period mains have been ingested. Other sports return HTTP 400.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}}}
Output schema
{'type': 'object', 'properties': {'clock': {'type': ['string', 'null'], 'description': 'Game clock from the live score snapshot.'}, 'sport': {'type': ['string', 'null'], 'description': 'Sport slug: nfl, ncaaf, nba, ncaab, mlb, soccer, or tennis.'}, 'period': {'type': ['string', 'null'], 'description': 'Current period from the live score snapshot.'}, 'status': {'type': ['string', 'null'], 'description': 'Event status (scheduled, inprogress, delayed, final, …).'}, 'event_id': {'type': 'integer', 'description': 'Lumify event ID.'}, 'available': {'type': 'boolean', 'description': "False when no first-half / first-five / first-set mains have been ingested; period_odds is empty and the call isn't billed."}, 'period_odds': {'type': 'array', 'items': {'type': 'object'}, 'description': 'One row per (scope, market, line). Fields: scope (1H, F5, or S1), market (first_half_spreads / first_half_totals), line (home-perspective for spreads), home_score, away_score, current (totals only), current_margin (spreads only), pct_of_line, settleable, scope_complete, result (totals), home_result / away_result (spreads), books ({book_slug: {home, away} or {over, under}}).'}}}
get_player
Get a single player identity profile: name, sport, country, position/handedness, physical stats, current team, rankings (tennis {singles, points}; null on every other sport), and image_url (Lumify media URL, null until the sport's headshot/enrichment job). Raises a not-found error if player_id doesn't exist. Resolve ids via search_players.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['player_id'], 'properties': {'player_id': {'type': 'integer', 'description': 'Player id, from search_players.'}}}
Output schema
{'type': 'object', 'properties': {'id': {'type': 'integer', 'description': 'Lumify player ID.'}, 'slug': {'type': 'string', 'description': 'URL-safe unique slug.'}, 'sport': {'type': 'string', 'description': 'Sport slug, e.g. mlb, tennis, nfl.'}, 'position': {'type': ['string', 'null'], 'description': 'Roster position abbreviation when the sport has one (e.g. C, P, SS for MLB; QB, WR for NFL). Null for tennis and when not yet ingested.'}, 'rankings': {'type': ['object', 'null'], 'properties': {'points': {'type': ['integer', 'null'], 'description': 'ATP/WTA ranking points. Tennis only.'}, 'singles': {'type': ['integer', 'null'], 'description': 'ATP/WTA singles ranking. Tennis only.'}}, 'description': 'Sport ranking block. Tennis: {singles, points} from ATP/WTA standings. Null for every other sport. Tennis /stats also exposes ranking / ranking_points on the tennis player block.'}, 'birthdate': {'type': ['string', 'null'], 'description': 'YYYY-MM-DD date of birth.'}, 'full_name': {'type': 'string', 'description': 'Display name.'}, 'height_cm': {'type': ['integer', 'null'], 'description': 'Height in centimetres. Null when not ingested.'}, 'image_url': {'type': ['string', 'null'], 'description': "Lumify media URL for the player headshot (https://lumify.ai/media/players/{sport}/{id}.{ext}). Null until the sport's headshot/enrichment job. Never a vendor CDN."}, 'is_active': {'type': 'boolean', 'description': 'False when deactivated or retired.'}, 'last_name': {'type': ['string', 'null']}, 'weight_kg': {'type': ['number', 'null'], 'description': 'Weight in kilograms. Null when not ingested.'}, 'first_name': {'type': ['string', 'null']}, 'handedness': {'type': ['string', 'null'], 'description': 'left | right | switch. Meaning is sport-specific (bats for MLB, shoots for NHL, playing hand for tennis). Null when unknown.'}, 'retired_at': {'type': ['string', 'null'], 'description': 'YYYY-MM-DD retirement date when known.'}, 'country_code': {'type': ['string', 'null'], 'description': 'ISO 3166-1 alpha-3 country code.'}, 'current_team_id': {'type': ['integer', 'null'], 'description': 'Lumify team ID when the player is on a club roster. Null for tennis.'}, 'current_team_name': {'type': ['string', 'null'], 'description': 'Current team display name. Null for tennis.'}}}
get_player_events
List a player's events (schedule/results), paginated by id (after_id). Defaults to ±30 days around today when no date filter is given. Resolve player_id via search_players first.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['player_id'], 'properties': {'to': {'type': 'string', 'description': 'End date YYYY-MM-DD.'}, 'from': {'type': 'string', 'description': 'Start date YYYY-MM-DD.'}, 'limit': {'type': 'integer', 'default': 25, 'maximum': 100, 'minimum': 1, 'description': 'Max events to return per page.'}, 'status': {'enum': ['scheduled', 'inprogress', 'final', 'postponed', 'cancelled', 'suspended', 'delayed', 'walkover'], 'type': 'string', 'description': 'Filter to events in this status.'}, 'after_id': {'type': 'integer', 'description': "Cursor: last event id from the previous page's next_after_id."}, 'player_id': {'type': 'integer', 'description': 'Player id, from search_players.'}}}
Output schema
{'type': 'object', 'properties': {'data': {'type': 'array', 'items': {'type': 'object'}, 'description': "Events in the same shape as list_events' EventSummary."}, 'has_more': {'type': 'boolean'}, 'player_id': {'type': 'integer'}, 'next_after_id': {'type': ['integer', 'null'], 'description': 'Pass as after_id to fetch the next page; null on the last page.'}}}
get_player_props
Get player-prop lines and live progress for an NFL, NCAAF, NBA, NCAAB, NHL, MLB, or soccer event. Joins persisted player-prop mains to this-event player box counts and grades over/under/push (1:1 slugs, combo sums including rush+rec and pass+rush yards, weighted total bases, anytime TD, double-double/triple-double, hockey points). Sport × market catalog: https://lumify.ai/docs/player-props. GET /odds / get_odds stay on moneyline/spread/total. Returns available:false with no charge if no prop mains have been ingested. Other sports return HTTP 400.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}}}
Output schema
{'type': 'object', 'properties': {'clock': {'type': ['string', 'null'], 'description': 'Game clock from the live score snapshot.'}, 'sport': {'type': ['string', 'null'], 'description': 'Sport slug: nfl, ncaaf, nba, ncaab, nhl, or mlb.'}, 'period': {'type': ['string', 'null'], 'description': 'Current period from the live score snapshot.'}, 'status': {'type': ['string', 'null'], 'description': 'Event status (scheduled, inprogress, delayed, final, …).'}, 'event_id': {'type': 'integer', 'description': 'Lumify event ID.'}, 'available': {'type': 'boolean', 'description': "False when no player-prop mains have been ingested; player_props is empty and the call isn't billed."}, 'player_props': {'type': 'array', 'items': {'type': 'object'}, 'description': 'One row per (player, market, line). Fields: player, player_id (null if unmatched), market (prop category), line, current (this-event box count), pct_of_line, settleable, result (in_progress / over / under / push / dnp — box landed and this player has zero rows / no_stat — played but this slug never landed, unmatched, or box not landed yet; null when not settleable), books ({book_slug: {over, under}} American prices).'}}}
get_splits
Get public betting splits (bets% and handle%) for an event: a consensus split plus a per-bookmaker breakdown (bookmakers[].bookmaker uses the same odds slugs as get_odds, e.g. draftkings — not upstream short keys like dk), with a captured_at timestamp. Available for MLB, NBA, NHL, NFL, NCAAF, and NCAAB. Not available for tennis or soccer (upstream 400). Returns available:false with no charge if splits haven't been captured for this event yet or the sport is unsupported.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}}}
Output schema
{'type': 'object', 'properties': {'event_id': {'type': 'integer'}, 'available': {'type': 'boolean'}, 'consensus': {'type': ['object', 'null'], 'description': 'Aggregate bets%/handle% across bookmakers.'}, 'bookmakers': {'type': 'array', 'items': {'type': 'object'}, 'description': 'Per-bookmaker splits. Each item has bookmaker (odds slug), name, moneyline, spread, total.'}, 'captured_at': {'type': ['string', 'null']}}}
get_stats
Get raw, deterministic team/match statistics for a soccer, MLB, tennis, NFL, NCAAF, NBA, NCAAB, or NHL event — no odds (use get_odds) and no scoring (use get_intelligence). Payload is sport-specific: teams.home/away except tennis (players.player_1/player_2). Tennis doubles/qualifying return available:false. Form/record/H2H exclude walkovers and NFL/NCAAF/NBA/NCAAB preseason. Other sports return HTTP 400. Field catalog: https://lumify.ai/docs/reference#event-stats
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}}}
Output schema
{'type': 'object', 'properties': {'match': {'type': ['object', 'null'], 'description': "Tennis only. Match context: surface, competition_id/name, tier, round (ingested labels like 'Round of 16'/'Quarterfinal'/'Final', not 'R16'), court (not currently populated), status, result_type, scoreboard (sets_won + per-set games; tiebreak_score not currently populated)."}, 'teams': {'type': ['object', 'null'], 'description': "Soccer/MLB/NFL/NCAAF/NBA/NCAAB/NHL only (home/away). Each side includes image_url (Lumify media URL, null until ingest; never a vendor CDN). Soccer: recent_form, team_strength, venue, rest_days, sos, lineup, rates_l5, rates_season. MLB: record, recent_form, rest_days, rates_l5/rates_season (incl. OBP/SLG/OPS/RBI/TB), starting_pitcher (post-box only), lineup, player_box (this event's per-player batting/pitching counting stats; final, in-progress, and delayed when rows exist). NFL/NCAAF: record (points_for/against), recent_form (points_scored/allowed), rest_days, rates_l5/rates_season (total/passing/rushing yards, attempts, turnovers, third_down_pct), player_box (one players[] line per athlete with passing/rushing/receiving/defense/kicking counts; final, in-progress, and delayed when rows exist). NBA/NCAAB: record (points_for/against), recent_form (points_scored/allowed), rest_days, rates_l5/rates_season (rebounds/assists/steals/blocks/turnovers/fouls, fg_pct/three_point_pct/free_throw_pct as ratio-of-sums), player_box (points/rebounds/assists/…; final, in-progress, and delayed when rows exist). NHL: record (goals_for/against), recent_form (goals_scored/allowed), rest_days, rates_l5/rates_season (shots_on_goal/hits/penalty_minutes/power_play_goals/giveaways/takeaways/blocked_shots), player_box (skaters[] + goalies[]; assists/hits remapped from assists_nhl/hits_nhl; final, in-progress, and delayed when rows exist). Settleables stay on get_player_props. Absent on tennis responses — use players instead."}, 'players': {'type': ['object', 'null'], 'description': 'Tennis only (player_1/player_2). Each side: player_id, name, country_code, ranking, ranking_points, rest_days, recent_form, surface_form, record (tour_lookback wins/losses), career_rates (Stage-2 serve/return percentages; null until ingest), career_surface (Stage-2 match-surface W/L over windows.career_surface_years; null when empty). History windows exclude walkovers (unplayed) and include retirements.'}, 'profile': {'type': 'string', 'description': "Soccer only. 'world_cup' or 'club'."}, 'windows': {'type': ['object', 'null'], 'description': "Explicit sample depths. Soccer: recent_form (5), rates_l5 (5), rates_season ('season'), head_to_head (10), sos (5). MLB/NFL/NCAAF/NBA/NCAAB/NHL: recent_form (5), rates_l5 (5), rates_season ('season'), head_to_head (10). Tennis: recent_form (10), surface_form (10), head_to_head (10), record_lookback_days (365), career_surface_years (3)."}, 'event_id': {'type': 'integer', 'description': 'Lumify event ID.'}, 'available': {'type': 'boolean', 'description': "False when participants haven't resolved, or tennis draw_type is not exactly 'singles' (doubles/qualifying out of scope); every other field is omitted and the call isn't billed."}, 'draw_type': {'type': ['string', 'null'], 'description': "Tennis only. Always 'singles' when available is true. Values other than 'singles' (including 'doubles' and 'qualifying') return available:false."}, 'league_slug': {'type': ['string', 'null'], 'description': "League/tour slug, e.g. 'mls', 'mlb', 'nfl', 'atp', 'wta'."}, 'head_to_head': {'type': ['object', 'null'], 'description': "Past meetings: {window, meetings, total}. Soccer: {home_goals, away_goals}. MLB: {home_runs, away_runs}. NFL/NCAAF/NBA/NCAAB: {home_points, away_points}. NHL: {home_goals, away_goals}. Tennis: {event_id, starts_at, surface, winner_role, sets_won} relative to this fixture's player_1/player_2 (walkovers excluded)."}, 'neutral_site': {'type': ['boolean', 'null'], 'description': 'Soccer only. Whether this fixture is at a neutral venue. Informational here; factored into home-advantage scoring on get_intelligence.'}, 'league_context': {'type': ['object', 'null'], 'description': "Soccer only. {avg_goals_per_team}: league-wide baseline goals/team/game, used by get_intelligence's attack/defense scoring. Null for fixed-baseline competitions."}}}
get_team
Get a single team profile with its home venue. Raises a not-found error if team_id doesn't exist. Resolve ids via list_teams.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['team_id'], 'properties': {'team_id': {'type': 'integer', 'description': 'Team id, from list_teams.'}}}
Output schema
{'type': 'object', 'properties': {'id': {'type': 'integer'}, 'city': {'type': ['string', 'null']}, 'name': {'type': 'string'}, 'slug': {'type': 'string'}, 'sport': {'type': 'string'}, 'venue': {'type': ['object', 'null']}, 'league': {'type': ['string', 'null']}, 'division': {'type': ['string', 'null']}, 'image_url': {'type': ['string', 'null'], 'description': 'Lumify media URL for the team logo (https://lumify.ai/media/teams/{sport}/{id}.png). Null until ingest. Never a vendor CDN.'}, 'is_active': {'type': 'boolean'}, 'conference': {'type': ['string', 'null']}, 'abbreviation': {'type': ['string', 'null']}}}
get_team_props
Get team-total lines and live progress for an NFL, NCAAF, MLB, or soccer event. Joins persisted Pinnacle team-total mains (each team's full-game points/runs/goals Over/Under) to this-event participant scores and grades over/under/push. GET /odds / get_odds stay on moneyline/spread/total. Returns available:false with no charge if no team-total mains have been ingested. Other sports return HTTP 400.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['event_id'], 'properties': {'event_id': {'type': 'integer', 'description': 'Event id, from list_events, query_events, or search results.'}}}
Output schema
{'type': 'object', 'properties': {'clock': {'type': ['string', 'null'], 'description': 'Game clock from the live score snapshot.'}, 'sport': {'type': ['string', 'null'], 'description': 'Sport slug: nfl, ncaaf, mlb, or soccer.'}, 'period': {'type': ['string', 'null'], 'description': 'Current period from the live score snapshot.'}, 'status': {'type': ['string', 'null'], 'description': 'Event status (scheduled, inprogress, delayed, final, …).'}, 'event_id': {'type': 'integer', 'description': 'Lumify event ID.'}, 'available': {'type': 'boolean', 'description': "False when no team-total mains have been ingested; team_props is empty and the call isn't billed."}, 'team_props': {'type': 'array', 'items': {'type': 'object'}, 'description': 'One row per (team, line). Fields: team, team_id, side (home/away), market (team_total), line, current (this-event team score), pct_of_line, settleable, result (in_progress / over / under / push, or null), books ({book_slug: {over, under}} American prices).'}}}
grade_slip
Grade settleable player-prop legs (over / under / push / in_progress / dnp / no_stat) for nfl, nba, ncaaf, ncaab, nhl, mlb, and soccer — the same sport coverage as get_player_props — plus structured game markets (h2h / spreads / totals) on any sport get_odds already settles. Prefer structured event_id + market_key + side; player_id and line are required on props, line is required on spreads/totals, and both player_id and line are omitted on h2h. team_total requires team_id + line + over/under and is only gradable on nfl/ncaaf/mlb/soccer. draw is only gradable on soccer h2h — off soccer it comes back unmapped. Free-text game phrases (Chiefs -3.5, Over 47.5 vs Bills, Yankees ML, Yankees to win, Yankees over 4.5 runs, Over 52.5 Syracuse vs Pittsburgh, Novak Djokovic ML) grade when the team or player and event resolve uniquely — Over 47.5 alone stays unmapped and is never the first slate game. A tennis moneyline leftover is a player, not a team; vs is the opponent player. Last-name-only tennis stays unmapped. A last-name-only player prop (Bergeron over 1.5 shots on goal last night) grades when a date is present and that surname is unique in scope — a named sport, team, or event narrows it (Johnson nhl last night); with no such clue, uniqueness is across every prop sport the key can see. No date, or a surname shared by more than one player in that scope, stays unmapped unless a date is present and exactly one of those candidates played in the window (optionally vs a named opponent). A colliding team nickname plus a date promotes only the unique in-window club; a football-sized line will not pick a baseball club. anytime goal / anytime assist (soccer_goals/soccer_assists over 0.5) and over a hit / over a homer (hits/home_runs over 1.0) need no explicit number. Free-text player props are graded only when player and event resolve uniquely — never guesses an ambiguous name. A roster-team mention (CIN, Niners) is resolved first; unique team_id scopes the player, and ambiguous/not_found stays on team_resolve. vs/at on a player prop is the opponent and narrows the event, not the player's team. Ambiguous events stay on event_resolve with candidates. Read legs[].result / current / market for the grade; use resolve.player_id to re-issue structured props. Call this tool with an API key to grade from an agent. Capped at 3 concurrent calls per key (shared with POST /v1/grade/slip). The public /grade sheet uses the same engine without a key (20 grades / IP / day). How-to: https://lumify.ai/docs/grade. Not live trading odds. Not wagering advice. Attribution is always Graded by Lumify.
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'legs': {'type': 'array', 'items': {'type': 'object', 'required': ['event_id', 'market_key', 'side'], 'properties': {'line': {'type': 'number', 'description': 'Required on props, spreads, totals, and team_total. Omit on h2h. Signed to the submitted side, not the favorite — side=home with a home -3.5 favorite is line=-3.5.'}, 'side': {'enum': ['home', 'away', 'over', 'under', 'draw'], 'type': 'string', 'description': 'Props and totals: over | under (o | u also accepted). Spreads: home | away, matching the signed line above. Moneyline: home | away, or draw on soccer only.'}, 'team_id': {'type': 'integer', 'description': 'Required on team_total. Forbidden on player-prop, h2h, spreads, and totals.'}, 'event_id': {'type': 'integer'}, 'player_id': {'type': 'integer', 'description': 'Required on player-prop markets. Forbidden on h2h, spreads, totals, and team_total.'}, 'market_key': {'type': 'string', 'description': 'Player-prop slug (e.g. receiving_yards), game market h2h | spreads | totals, or team_total. Aliases accepted: player_reception_yds -> receiving_yards, moneyline/ml -> h2h, spread -> spreads, total/ou -> totals, team totals/tt -> team_total.'}}}, 'maxItems': 8}, 'text': {'type': 'string', 'description': 'Free-text slip (e.g. Chase over 74.5 receiving yards tonight, or Chiefs -3.5 / Over 47.5 vs Bills / Yankees ML / Yankees to win / Yankees over 4.5 runs / Over 52.5 Syracuse vs Pittsburgh / Novak Djokovic ML / Mbappe anytime goal / Judge over a hit / Bergeron over 1.5 shots on goal last night). Date words (today, tonight, yesterday, last night, last Wednesday, this Thursday, or an ISO date) narrow the event. A roster-team span is resolved first; unique team_id scopes a player or binds a game/team-total leg, and ambiguous/not_found stays on team_resolve. vs/at on a player prop is the opponent, not the player\'s team. A tennis moneyline leftover is a player; vs is the opponent player. "anytime goal"/"anytime assist" implies soccer_goals/soccer_assists over 0.5 with no explicit number; "over a hit"/"over a homer" implies hits/home_runs over 1.0. A last-name-only player prop grades when a date is present and the surname is unique in scope (a named sport, team, or event narrows it; otherwise every visible prop sport); no date, or a shared surname in that scope, still refuses. Graded only when team/player and event are unique. A bare Over 47.5 stays unmapped.'}, 'clues': {'type': 'object', 'properties': {'sport': {'type': 'string'}, 'league': {'type': 'string'}, 'team_id': {'type': 'integer'}, 'event_id': {'type': 'integer'}, 'team_text': {'type': 'string'}}, 'description': 'Optional sport / league / event_id / team_id / team_text hints for free-text mode.'}}}
Output schema
{'type': 'object', 'properties': {'legs': {'type': 'array', 'items': {'type': 'object'}}, 'status': {'type': 'string', 'description': 'graded | partial | pending | unmapped'}, 'honesty': {'type': 'object'}, 'slip_id': {'type': ['string', 'null']}, 'summary': {'type': 'object'}, 'branding': {'type': 'object'}}}
list_ev
Beta. List pregame main-line +EV opportunities for a predictive-framework sport (soccer, mlb, tennis, nfl, ncaaf), sorted by ev_pct descending. market=h2h (default, moneyline), spreads, or totals. Tennis totals are not offered (Stage 1 is moneyline + spreads). Same gates as bets[].ev on get_intelligence: sharp-fair price gap, positive and ≤25%, suppressed MLB moneyline null books skipped in favor of the next eligible book. 1 credit. Field catalog: https://lumify.ai/docs/reference#intelligence-ev
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['sport'], 'properties': {'book': {'type': 'string', 'description': 'Restrict opportunities to one sportsbook slug (e.g. fanduel).'}, 'limit': {'type': 'integer', 'description': 'Max opportunities to return (1–200). Default 50.'}, 'sport': {'type': 'string', 'description': 'Sport slug: soccer, mlb, tennis, nfl, or ncaaf.'}, 'league': {'type': 'string', 'description': 'Optional league slug (mls, epl, atp, …). Soccer without a league scans every published soccer league (MLS + big-five).'}, 'market': {'enum': ['h2h', 'spreads', 'totals'], 'type': 'string', 'description': 'Main-line family: h2h (default, moneyline), spreads, or totals. Tennis + totals returns 400.'}, 'min_ev': {'type': 'number', 'description': 'Minimum EV% to include. Default 0. Clamped to 0–25.'}}}
Output schema
{'type': 'object', 'properties': {'beta': {'type': 'boolean', 'description': 'Always true.'}, 'book': {'type': ['string', 'null'], 'description': 'Book filter, or null.'}, 'sport': {'type': 'string', 'description': 'Sport slug this scan was run for.'}, 'total': {'type': 'integer', 'description': 'Count of opportunities on this page.'}, 'league': {'type': ['string', 'null'], 'description': 'League filter, or null for the whole sport.'}, 'market': {'type': 'string', 'description': 'h2h, spreads, or totals — the family scanned.'}, 'max_ev': {'type': 'number', 'description': 'Stale-line cap (25).'}, 'min_ev': {'type': 'number', 'description': 'Minimum EV% applied.'}, 'opportunities': {'type': 'array', 'items': {'type': 'object'}, 'description': 'Positive-EV main-line rows: {event_id, sport, league, commence_time, home_team, away_team, side, team, bet_type, line, fair_probability, ev}.'}}}
list_events
List events (schedules and live scores), paginated by id (after_id). Filter by sport, league, status, date range, season, or team_id (resolve teams via list_teams / get_team). Returns event id, name, sport/league, start time, status, and venue for each; pass include_scores to also inline participants + scores (intended for small result sets — use get_event for one event's full detail, or query_events for free-text/natural-language filters instead of structured params). include_scores shares the 20/min score-poll budget with get_live_score; prefer the SSE stream for live boards.
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'to': {'type': 'string', 'description': 'UTC end date YYYY-MM-DD (inclusive).'}, 'date': {'type': 'string', 'description': 'UTC date YYYY-MM-DD (single day).'}, 'from': {'type': 'string', 'description': 'UTC start date YYYY-MM-DD.'}, 'sort': {'enum': ['time', 'status'], 'type': 'string', 'default': 'time', 'description': 'Sort order. sort=status is incompatible with after_id.'}, 'limit': {'type': 'integer', 'default': 25, 'maximum': 100, 'minimum': 1, 'description': 'Max events to return per page.'}, 'sport': {'type': 'string', 'description': 'Sport slug, e.g. mlb, nfl, tennis, soccer.'}, 'league': {'type': 'string', 'description': 'League slug, e.g. nfl, atp, mls.'}, 'status': {'enum': ['scheduled', 'inprogress', 'final', 'postponed', 'cancelled', 'suspended', 'delayed', 'walkover'], 'type': 'string', 'description': 'Filter to events in this status.'}, 'team_id': {'type': 'integer', 'description': 'Filter to events where this team participates. Resolve ids via list_teams.'}, 'after_id': {'type': 'integer', 'description': "Cursor: return events with id > after_id (from the previous page's next_after_id)."}, 'season_id': {'type': 'integer', 'description': 'Filter by season ID (from list_seasons).'}, 'has_recommend': {'type': 'boolean', 'description': 'When true, only events with at least one recommended bet.'}, 'include_scores': {'type': 'boolean', 'default': False, 'description': 'Inline participants + scores in each event (intended for small result sets). Shares the 20/min score-poll budget with get_live_score.'}}}
Output schema
{'type': 'object', '$defs': {'EventSummary': {'type': 'object', 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'clock': {'type': ['string', 'null']}, 'sport': {'type': 'string'}, 'venue': {'type': ['object', 'null']}, 'league': {'type': 'string'}, 'period': {'type': ['string', 'null']}, 'status': {'type': 'string'}, 'season_id': {'type': ['integer', 'null']}, 'starts_at': {'type': 'string', 'description': 'ISO-8601 UTC start time.'}, 'inprogress_since': {'type': ['string', 'null'], 'description': 'ISO-8601 UTC when status first became inprogress (first live tick). Null until then; stays set after final.'}}}}, 'properties': {'total': {'type': 'integer'}, 'events': {'type': 'array', 'items': {'$ref': '#/$defs/EventSummary'}}, 'next_after_id': {'type': ['integer', 'null'], 'description': 'Pass as after_id to fetch the next page; null on the last page.'}}}
list_forecasts
Daily board of forecasted wagers from Lumify's model — a prediction, not a beat-the-market claim (no OOS/independence gate; see list_ev for the gated main-line +EV claim). Player props (rate model) on MLB, NCAAF, NFL, NBA, NCAAB, NHL. High-confidence main-line picks on tennis, NFL, NCAAF, MLB, and soccer: one side per moneyline / spread / total when the uncertainty band does not include a coin flip. Tennis moneyline is ranking Bradley-Terry; tennis spreads/totals are a Normal-approx games model. Other sports use the published assessment probability. Each wager has p_hit, conviction, and posted books prices. Use list_ev to scan main lines by sharp-fair price gap; use this tool to scan high-probability forecasts. reliability is emerging on v0. 1 credit; empty slate is still 200. How + field catalog: https://lumify.ai/docs/forecasts Worked wager: https://lumify.ai/docs/understanding-odds#forecasts
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['sport'], 'properties': {'date': {'type': 'string', 'description': 'UTC slate date YYYY-MM-DD. Defaults to today UTC.'}, 'limit': {'type': 'integer', 'description': 'Max wagers (1–100). Default 25.'}, 'sport': {'type': 'string', 'description': 'Sport slug: mlb, ncaaf, nfl, nba, ncaab, nhl, tennis, or soccer.'}, 'market': {'enum': ['h2h', 'spreads', 'totals'], 'type': 'string', 'description': 'Main-line family filter (h2h, spreads, or totals). Main-line sports publish a high-confidence side of each family when the lean clears the coin-flip gate. Ignored on prop-only sports (nba, ncaab, nhl).'}}}
Output schema
{'type': 'object', 'properties': {'date': {'type': 'string', 'description': 'UTC slate date (YYYY-MM-DD).'}, 'sport': {'type': 'string', 'description': 'Sport slug this slate was scored for.'}, 'total': {'type': 'integer', 'description': 'Count of wagers on this page.'}, 'wagers': {'type': 'array', 'items': {'type': 'object', 'properties': {'line': {'type': ['number', 'null'], 'description': 'Posted line the model was scored against. Prop and totals main-line rows: Over/Under number. Spreads main-line rows: the spread number. Null on h2h/moneyline rows.'}, 'side': {'type': ['string', 'null'], 'description': "Prop rows: 'over' or 'under' — the more likely side given the player's shrunken rate versus line. Null on main-line rows — read the picked outcome from bet_type instead."}, 'books': {'type': 'object', 'description': 'American price for the picked outcome, keyed by bookmaker slug (e.g. {draftkings: -453}). Posted market price for the side/bet_type the model picked.'}, 'p_hit': {'type': 'number', 'description': "Model probability (0–1) that the picked outcome (side on prop rows, bet_type on main-line rows) hits. Prop rows: built from the player's shrunken counting-stat rate (Poisson vs the posted Over/Under). Optional research may nudge a prop's p_hit by at most ±0.03; the chosen side stays the same."}, 'sport': {'type': ['string', 'null'], 'description': 'Sport slug. Slate only.'}, 'league': {'type': ['string', 'null'], 'description': 'League slug, if any. Slate only.'}, 'market': {'type': 'string', 'description': 'Player-prop rows: prop category (counting stats). MLB: strikeouts_pitcher, hits, rbis, runs, strikeouts_batter, hits_allowed, earned_runs, outs_recorded. NFL/NCAAF: passing/rushing/receiving_yards, receptions, passing_tds, rushing_tds, touchdowns (anytime-TD combo: rushing + receiving + defensive TDs), rush_rec_yards, pass_rush_yards. NBA/NCAAB: points, rebounds, assists, steals, blocks, threes_made. NHL: goals, hockey_assists, shots_on_goal. Main-line rows (bet_type set): the main-line family — h2h, spreads, or totals.'}, 'player': {'type': ['string', 'null'], 'description': 'Player display name from the priced line. Null on main-line rows with no player attribution (bet_type is a match-level token like OVER/UNDER/ML_DRAW).'}, 'drivers': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': 'string', 'description': 'Prop rows: typically player.l10_rate — the recent-form rate that fed Poisson. Main-line rows would use a different namespace once a main-line forecast model ships.'}, 'input': {'type': ['number', 'null'], 'description': 'Measured rate/rating behind this driver, in native units.'}, 'effect': {'type': 'number', 'description': 'Signed shift in p_hit versus a baseline case on the same line. 0.0 on yardage markets.'}, 'direction': {'type': 'string', 'description': 'up / down / neutral from the sign of effect.'}}}, 'description': 'Signed contributions that moved p_hit. Read input as the measured rate/rating behind the pick and effect as how far it lifts the chosen outcome versus a baseline.'}, 'bet_type': {'type': ['string', 'null'], 'description': "Main-line token when this row is a main-line forecast — ML_P1/ML_P2/ML_HOME/ML_AWAY/ML_DRAW, SPREAD_P1/SPREAD_P2/SPREAD_HOME/SPREAD_AWAY, or OVER/UNDER (same vocabulary as get_intelligence bets[].bet_type and list_ev). Null on player-prop rows — that's the discriminator between the two row shapes. Tennis sets ML_P1/ML_P2 (moneyline), SPREAD_P1/SPREAD_P2 (game handicap), and OVER/UNDER (total games)."}, 'event_id': {'type': ['integer', 'null'], 'description': 'Lumify event ID. Present on list_forecasts; omitted on get_intelligence.forecasts (the event is the argument).'}, 'interval': {'type': 'array', 'items': {'type': 'number'}, 'description': '[lo, hi] stated band around p_hit. Wider when sufficiency is low. A stated evidence band, not a statistical confidence interval.'}, 'research': {'type': ['object', 'null'], 'description': 'Optional Deep Research overlay when the background job has written a row for this wager — every wager on the daily board (selected: true), plus other high-probability wagers (p_hit ≥ 0.80) in the catalog: {stance, conviction, note}. stance is validate / neutral / invalidate. note is the wager-level why — on a selected main-line row it is also copied to bets[].narrative. Validate / invalidate rows always carry a note. Validate nudges p_hit up by at most 0.03 and lifts conviction. Invalidate drops the wager from forecasts[] and the daily board — it is not a recommended pick. The chosen side stays. Null means read p_hit from the rate model alone.'}, 'selected': {'type': 'boolean', 'description': 'True when this wager is on the daily board (top conviction). On get_intelligence the array includes selected and the rest of the event catalog.'}, 'away_team': {'type': ['string', 'null'], 'description': 'Away team display name. Slate only.'}, 'home_team': {'type': ['string', 'null'], 'description': 'Home team display name. Slate only.'}, 'player_id': {'type': ['integer', 'null'], 'description': 'Lumify player ID. Bound by exact / Jr-stripped name match. Null on main-line rows with no player attribution.'}, 'conviction': {'type': 'number', 'description': 'Board rank key on 0–1: |p_hit−0.5|×2×sufficiency×research. A high p_hit on a thin sample ranks below a moderate p_hit on a long one. Highest conviction first on the daily slate.'}, 'player_role': {'type': ['string', 'null'], 'description': "'home'/'away' for team sports or 'p1'/'p2' for head-to-head sports, set only alongside a non-null bet_type. Null for player-prop rows and for match-level main-line tokens (OVER, UNDER, ML_DRAW)."}, 'reliability': {'type': 'string', 'description': 'Badge on this sport×market cell: emerging, moderate, high, or informational. v0 ships emerging for every wager.'}, 'sufficiency': {'type': 'number', 'description': "Evidence weight on 0–1: n/(n+12), where n is the recent-form game count (typically L10). A player with 10 games has sufficiency ≈ 0.45. The wager still ships; this field tells you how much of p_hit is earned from this player's own boxes."}, 'commence_time': {'type': ['string', 'null'], 'description': 'ISO-8601 UTC scheduled start. Slate only.'}, 'model_version': {'type': 'string', 'description': 'Scorer version, e.g. forecast-v0.'}}}, 'description': 'Selected forecasted wagers, highest conviction first. Read p_hit as P(the picked outcome — side on prop rows, bet_type on main-line rows — hits); conviction is the board rank. How + field catalog: https://lumify.ai/docs/forecasts'}, 'reliability': {'type': 'string', 'description': 'Default badge on this slate. v0 ships emerging; each wager repeats the same field.'}, 'model_version': {'type': 'string', 'description': 'Scorer version (forecast-v0).'}}}
list_seasons
List seasons per sport/league. By default returns only currently active seasons; pass current_only=false to include historical seasons. Optionally filter by sport. Returns each season's id, year, phase, start/end dates, and whether it is_current. Use list_sports for just each sport's current season.
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'sport': {'type': 'string', 'description': 'Filter by sport slug, e.g. nhl, nba, soccer.'}, 'current_only': {'type': 'boolean', 'default': True, 'description': 'Return only currently active seasons (default true). Pass false for historical seasons.'}}}
Output schema
{'type': 'object', 'properties': {'total': {'type': 'integer'}, 'seasons': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': 'integer'}, 'name': {'type': ['string', 'null']}, 'year': {'type': ['integer', 'null']}, 'phase': {'type': ['string', 'null']}, 'sport': {'type': 'object'}, 'league': {'type': 'object'}, 'end_date': {'type': ['string', 'null']}, 'is_current': {'type': 'boolean'}, 'start_date': {'type': ['string', 'null']}}}}}}
list_sports
List supported sports with their leagues and current season. Returns each sport's id, slug, name, team-sport flag, and its leagues (each with its current_season). Use list_seasons with current_only=false for historical seasons.
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'active_only': {'type': 'boolean', 'default': True, 'description': 'When true (default), omit sports with no active coverage.'}}}
Output schema
{'type': 'object', 'properties': {'total': {'type': 'integer'}, 'sports': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'slug': {'type': 'string'}, 'leagues': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'slug': {'type': 'string'}, 'current_season': {'type': ['object', 'null']}}}}, 'is_team_sport': {'type': 'boolean'}}}}}}
list_teams
List teams, paginated by id (after_id). Filter by sport, league, conference, division, country, active status, or name (q, partial match). Returns each team's id, slug, name, city, conference/division, venue, and image_url (Lumify media URL, null until ingest). Use get_team for full detail on one id once resolved here.
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'q': {'type': 'string', 'description': 'Team name search (partial match).'}, 'limit': {'type': 'integer', 'default': 25, 'maximum': 100, 'minimum': 1, 'description': 'Max teams to return per page.'}, 'sport': {'type': 'string', 'description': 'Sport slug, e.g. nfl, nba, soccer.'}, 'active': {'type': 'boolean', 'description': 'Filter by active status.'}, 'league': {'type': 'string', 'description': 'League slug, e.g. nfl, mls.'}, 'country': {'type': 'string', 'description': 'ISO country code, e.g. USA.'}, 'after_id': {'type': 'integer', 'description': "Cursor: last team id from the previous page's next_after_id."}, 'division': {'type': 'string', 'description': 'Division name, e.g. AFC East.'}, 'conference': {'type': 'string', 'description': 'Conference name, e.g. AFC, Eastern.'}}}
Output schema
{'type': 'object', '$defs': {'Team': {'type': 'object', 'properties': {'id': {'type': 'integer'}, 'city': {'type': ['string', 'null']}, 'name': {'type': 'string'}, 'slug': {'type': 'string'}, 'sport': {'type': 'string'}, 'state': {'type': ['string', 'null']}, 'venue': {'type': ['object', 'null']}, 'league': {'type': ['string', 'null']}, 'division': {'type': ['string', 'null']}, 'image_url': {'type': ['string', 'null'], 'description': 'Lumify media URL for the team logo (https://lumify.ai/media/teams/{sport}/{id}.png). Null until ingest. Never a vendor CDN.'}, 'is_active': {'type': 'boolean'}, 'conference': {'type': ['string', 'null']}, 'short_name': {'type': ['string', 'null']}, 'abbreviation': {'type': ['string', 'null']}, 'country_code': {'type': ['string', 'null']}}}}, 'properties': {'data': {'type': 'array', 'items': {'$ref': '#/$defs/Team'}}, 'has_more': {'type': 'boolean'}, 'next_after_id': {'type': ['integer', 'null'], 'description': 'Pass as after_id to fetch the next page; null on the last page.'}}}
query_events
Search events with a natural-language query instead of structured filters — e.g. 'live nfl games today' or 'college basketball this week'. Rule-based (not an LLM): recognizes sport (nfl/nba/mlb/nhl/tennis/soccer/ncaaf/ncaab + aliases like hockey, american football, college basketball), status (live/final/upcoming/…), dates (today/tomorrow, this week, next N days, YYYY-MM-DD ranges). Bare 'football' is ambiguous and left unrecognized. Response includes interpreted filters, equivalent REST call, and unrecognized_terms. Prefer list_events when you already know the structured filters you want.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['query'], 'properties': {'limit': {'type': 'integer', 'description': 'Overrides any limit parsed from the query text. Max 100.'}, 'query': {'type': 'string', 'description': "Free text, e.g. 'live nfl games today'."}}}
Output schema
{'type': 'object', 'properties': {'query': {'type': 'string', 'description': 'The original natural-language query text.'}, 'total': {'type': 'integer'}, 'events': {'type': 'array', 'items': {'type': 'object'}}, 'interpreted': {'type': 'object', 'description': 'The list_events-equivalent filters parsed from the query text (sport, status, date, from, to, limit).'}, 'next_after_id': {'type': ['integer', 'null']}, 'equivalent_request': {'type': 'string', 'description': 'The literal GET /v1/events request this query was translated to.'}, 'unrecognized_terms': {'type': 'array', 'items': {'type': 'string'}, 'description': "Query words that didn't map to a known filter."}}}
resolve_event
Resolve event identity from an event_id, or a player_id/team_id clue plus an optional date window, to a Lumify event_id. Falls back to a player's roster team schedule for team sports (only individual sports like tennis track per-player game participation directly). Combine team_id + opponent_team_id for a specific matchup. Returns ambiguous instead of guessing when the window has more than one candidate — never auto-pick candidates[0].
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'clues': {'type': 'object', 'properties': {'team_id': {'type': 'integer'}, 'end_date': {'type': 'string', 'description': 'UTC YYYY-MM-DD. Requires start_date.'}, 'event_id': {'type': 'integer'}, 'player_id': {'type': 'integer'}, 'start_date': {'type': 'string', 'description': 'UTC YYYY-MM-DD. Requires end_date.'}, 'opponent_team_id': {'type': 'integer', 'description': 'Requires team_id or player_id.'}}, 'description': 'event_id (ground truth), or player_id/team_id plus a date window.'}, 'options': {'type': 'object', 'properties': {'max_candidates': {'type': 'integer', 'default': 5, 'maximum': 25, 'minimum': 1}, 'min_confidence': {'type': 'number', 'default': 0.85, 'maximum': 1, 'minimum': 0}}}}}
Output schema
{'type': 'object', 'properties': {'sport': {'type': ['string', 'null']}, 'league': {'type': ['string', 'null']}, 'method': {'type': ['string', 'null']}, 'status': {'type': 'string', 'description': 'resolved | ambiguous | not_found | error'}, 'message': {'type': ['string', 'null']}, 'event_id': {'type': ['integer', 'null']}, 'away_team': {'type': ['string', 'null']}, 'home_team': {'type': ['string', 'null']}, 'starts_at': {'type': ['string', 'null']}, 'candidates': {'type': 'array', 'items': {'type': 'object'}}, 'clues_used': {'type': 'array', 'items': {'type': 'string'}}, 'confidence': {'type': ['number', 'null']}, 'event_status': {'type': ['string', 'null']}, 'match_reasons': {'type': 'array', 'items': {'type': 'string'}}, 'participant_conflict': {'type': 'boolean'}}}
resolve_player
Resolve messy sports player names to a Lumify player_id using sport, team, or event clues. Prefer this before grade_slip when the name is a fragment, initial, or nickname. Returns ambiguous instead of guessing — never auto-pick candidates[0]. A sport-scoped key binds the in-scope side of a collision and returns not_found when every hit is out of scope. Does not grade props.
Read only Open world Idempotent
Input schema
{'type': 'object', 'required': ['query'], 'properties': {'clues': {'type': 'object', 'properties': {'sport': {'type': 'string', 'description': 'Sport slug, e.g. nfl.'}, 'vendor': {'type': 'string'}, 'team_id': {'type': 'integer'}, 'event_id': {'type': 'integer'}, 'position': {'type': 'string'}, 'team_text': {'type': 'string', 'description': 'Team abbreviation, slug, or name.'}, 'vendor_player_key': {'type': 'string'}}, 'description': 'Optional sport, team, event, or position clues.'}, 'query': {'type': 'string', 'description': 'Messy player name or fragment, e.g. J. Chase.'}, 'options': {'type': 'object', 'properties': {'mode': {'enum': ['strict', 'permissive', 'ingest'], 'type': 'string', 'default': 'strict'}, 'max_candidates': {'type': 'integer', 'default': 5, 'maximum': 25, 'minimum': 1}, 'min_confidence': {'type': 'number', 'default': 0.85, 'maximum': 1, 'minimum': 0}}}}}
Output schema
{'type': 'object', 'properties': {'sport': {'type': ['string', 'null']}, 'status': {'type': 'string', 'description': 'resolved | ambiguous | not_found | error'}, 'message': {'type': ['string', 'null']}, 'team_id': {'type': ['integer', 'null']}, 'player_id': {'type': ['integer', 'null']}, 'candidates': {'type': 'array', 'items': {'type': 'object'}}, 'clues_used': {'type': 'array', 'items': {'type': 'string'}}, 'confidence': {'type': ['number', 'null']}, 'display_name': {'type': ['string', 'null']}, 'match_reasons': {'type': 'array', 'items': {'type': 'string'}}}}
resolve_team
Resolve messy team names, abbreviations, metros, or aliases to a Lumify team_id using sport, league, event, or player clues. Prefer this before list_teams when the string is a nickname or city token. Returns ambiguous instead of guessing — never auto-pick candidates[0]. City-only metros sit below the auto-resolve floor.
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'clues': {'type': 'object', 'properties': {'sport': {'type': 'string', 'description': 'Sport slug, e.g. nfl.'}, 'league': {'type': 'string', 'description': 'League slug, e.g. mls.'}, 'team_id': {'type': 'integer'}, 'event_id': {'type': 'integer'}, 'player_id': {'type': 'integer'}}, 'description': 'Optional sport, league, event, player, or team-id clues.'}, 'query': {'type': 'string', 'description': 'Team string, e.g. Niners, CIN, NY Giants.'}, 'options': {'type': 'object', 'properties': {'max_candidates': {'type': 'integer', 'default': 5, 'maximum': 25, 'minimum': 1}, 'min_confidence': {'type': 'number', 'default': 0.85, 'maximum': 1, 'minimum': 0}}}}}
Output schema
{'type': 'object', 'properties': {'sport': {'type': ['string', 'null']}, 'league': {'type': ['string', 'null']}, 'method': {'type': ['string', 'null']}, 'status': {'type': 'string', 'description': 'resolved | ambiguous | not_found | error'}, 'message': {'type': ['string', 'null']}, 'team_id': {'type': ['integer', 'null']}, 'candidates': {'type': 'array', 'items': {'type': 'object'}}, 'clues_used': {'type': 'array', 'items': {'type': 'string'}}, 'confidence': {'type': ['number', 'null']}, 'abbreviation': {'type': ['string', 'null']}, 'display_name': {'type': ['string', 'null']}, 'match_reasons': {'type': 'array', 'items': {'type': 'string'}}, 'sport_conflict': {'type': 'boolean'}}}
search_players
Search players by name, sport, country, ranking, or active status, paginated by id (after_id). Returns the same identity object on every sport (null means unknown, not wrong sport). Tennis standings nest under rankings.{singles, points}; rankings is null on every other sport. Use get_player for full detail on one id, or get_player_events for a player's schedule/results.
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'q': {'type': 'string', 'description': 'Name search (partial match).'}, 'limit': {'type': 'integer', 'default': 25, 'maximum': 100, 'minimum': 1, 'description': 'Max players to return per page.'}, 'sport': {'type': 'string', 'description': 'Sport slug, e.g. tennis, nba.'}, 'active': {'type': 'boolean', 'description': 'Filter by active status.'}, 'ranked': {'type': 'boolean', 'description': 'If true, only tennis players with an ATP/WTA singles ranking (rankings.singles).'}, 'country': {'type': 'string', 'description': 'ISO 3166-1 alpha-3 country code, e.g. USA.'}, 'after_id': {'type': 'integer', 'description': "Cursor: last player id from the previous page's next_after_id."}}}
Output schema
{'type': 'object', '$defs': {'Player': {'type': 'object', 'properties': {'id': {'type': 'integer', 'description': 'Lumify player ID.'}, 'slug': {'type': 'string', 'description': 'URL-safe unique slug.'}, 'sport': {'type': 'string', 'description': 'Sport slug, e.g. mlb, tennis, nfl.'}, 'position': {'type': ['string', 'null'], 'description': 'Roster position abbreviation when the sport has one (e.g. C, P, SS for MLB; QB, WR for NFL). Null for tennis and when not yet ingested.'}, 'rankings': {'type': ['object', 'null'], 'properties': {'points': {'type': ['integer', 'null'], 'description': 'ATP/WTA ranking points. Tennis only.'}, 'singles': {'type': ['integer', 'null'], 'description': 'ATP/WTA singles ranking. Tennis only.'}}, 'description': 'Sport ranking block. Tennis: {singles, points} from ATP/WTA standings. Null for every other sport. Tennis /stats also exposes ranking / ranking_points on the tennis player block.'}, 'birthdate': {'type': ['string', 'null'], 'description': 'YYYY-MM-DD date of birth.'}, 'full_name': {'type': 'string', 'description': 'Display name.'}, 'height_cm': {'type': ['integer', 'null'], 'description': 'Height in centimetres. Null when not ingested.'}, 'image_url': {'type': ['string', 'null'], 'description': "Lumify media URL for the player headshot (https://lumify.ai/media/players/{sport}/{id}.{ext}). Null until the sport's headshot/enrichment job. Never a vendor CDN."}, 'is_active': {'type': 'boolean', 'description': 'False when deactivated or retired.'}, 'last_name': {'type': ['string', 'null']}, 'weight_kg': {'type': ['number', 'null'], 'description': 'Weight in kilograms. Null when not ingested.'}, 'first_name': {'type': ['string', 'null']}, 'handedness': {'type': ['string', 'null'], 'description': 'left | right | switch. Meaning is sport-specific (bats for MLB, shoots for NHL, playing hand for tennis). Null when unknown.'}, 'retired_at': {'type': ['string', 'null'], 'description': 'YYYY-MM-DD retirement date when known.'}, 'country_code': {'type': ['string', 'null'], 'description': 'ISO 3166-1 alpha-3 country code.'}, 'current_team_id': {'type': ['integer', 'null'], 'description': 'Lumify team ID when the player is on a club roster. Null for tennis.'}, 'current_team_name': {'type': ['string', 'null'], 'description': 'Current team display name. Null for tennis.'}}}}, 'properties': {'data': {'type': 'array', 'items': {'$ref': '#/$defs/Player'}}, 'has_more': {'type': 'boolean'}, 'next_after_id': {'type': ['integer', 'null'], 'description': 'Pass as after_id to fetch the next page; null on the last page.'}}}
Changed
grade_slip
Sept. 21, 2026, 2:58 a.m.
Changed
list_forecasts
Sept. 21, 2026, 2:58 a.m.
Changed
get_intelligence
Sept. 21, 2026, 2:58 a.m.
Changed
get_player_props
Sept. 21, 2026, 2:58 a.m.
Changed
grade_slip
Sept. 19, 2026, 2:49 a.m.
Changed
list_forecasts
Sept. 19, 2026, 2:49 a.m.
Changed
get_intelligence
Sept. 19, 2026, 2:49 a.m.
Changed
get_stats
Sept. 19, 2026, 2:49 a.m.
Changed
grade_slip
Sept. 17, 2026, 12:56 p.m.
Added
grade_slip
Sept. 17, 2026, 7:57 a.m.
Added
resolve_event
Sept. 17, 2026, 7:57 a.m.
Added
resolve_team
Sept. 17, 2026, 7:57 a.m.
Added
resolve_player
Sept. 17, 2026, 7:57 a.m.
Added
estimate_cost
Sept. 17, 2026, 7:57 a.m.
Added
list_seasons
Sept. 17, 2026, 7:57 a.m.
Added
get_player_events
Sept. 17, 2026, 7:57 a.m.
Added
get_player
Sept. 17, 2026, 7:57 a.m.
Added
get_team
Sept. 17, 2026, 7:57 a.m.
Added
search_players
Sept. 17, 2026, 7:57 a.m.
Added
list_teams
Sept. 17, 2026, 7:57 a.m.
Added
list_forecasts
Sept. 17, 2026, 7:57 a.m.
Added
list_ev
Sept. 17, 2026, 7:57 a.m.
Added
get_intelligence
Sept. 17, 2026, 7:57 a.m.
Added
get_injuries
Sept. 17, 2026, 7:57 a.m.
Added
get_splits
Sept. 17, 2026, 7:57 a.m.
Added
get_period_odds
Sept. 17, 2026, 7:57 a.m.
Added
get_team_props
Sept. 17, 2026, 7:57 a.m.
Added
get_player_props
Sept. 17, 2026, 7:57 a.m.
Added
get_stats
Sept. 17, 2026, 7:57 a.m.
Added
get_odds_history
Sept. 17, 2026, 7:57 a.m.