--- name: markets description: | Markets orchestration — connects ESPN live schedules with Kalshi and Polymarket prediction markets. Unified dashboards, odds comparison, entity search, and bet evaluation across platforms. Use when: user wants to see prediction market odds alongside ESPN game schedules, compare odds across platforms, search for a team/player on Kalshi or Polymarket, check for arbitrage between ESPN odds and prediction markets, or evaluate a specific game's market value. Don't use when: user wants raw prediction market data without ESPN context — use polymarket or kalshi directly. For pure odds math (conversion, de-vigging, Kelly) — use betting. For live scores without market data — use the sport-specific skill. license: MIT metadata: author: machina-sports version: "0.2.0" --- # Markets Orchestration Bridges ESPN live schedules (NBA, NFL, MLB, NHL, WNBA, CFB, CBB) with Kalshi and Polymarket prediction markets. Before writing queries, consult `references/api-reference.md` for supported sport codes, command parameters, and price normalization formats. ## Quick Start ```bash sports-skills markets get_todays_markets --sport=nba sports-skills markets search_entity --query="Lakers" --sport=nba sports-skills markets compare_odds --sport=nba --event_id=401234567 sports-skills markets get_sport_markets --sport=nfl sports-skills markets get_sport_schedule --sport=nba sports-skills markets normalize_price --price=0.65 --source=polymarket sports-skills markets evaluate_market --sport=nba --event_id=401234567 ``` Python SDK: ```python from sports_skills import markets markets.get_todays_markets(sport="nba") markets.search_entity(query="Lakers", sport="nba") markets.compare_odds(sport="nba", event_id="401234567") markets.get_sport_markets(sport="nfl") markets.get_sport_schedule(sport="nba", date="2025-02-26") markets.normalize_price(price=0.65, source="polymarket") markets.evaluate_market(sport="nba", event_id="401234567") ``` ## CRITICAL: Before Any Query CRITICAL: Before calling any orchestration command, verify: - A `sport` code is provided for sport-aware commands (`get_todays_markets`, `compare_odds`, `get_sport_markets`, `evaluate_market`). - Price sources are identified correctly before normalization: `espn` = American odds, `polymarket` = 0-1 probability, `kalshi` = 0-100 integer. ## Important Notes - **Sport context is passed through.** `--sport=nba` maps automatically to the correct Polymarket sport code and Kalshi series ticker. - **Both platforms use sport-aware search.** Polymarket uses `sport` → series_id; Kalshi uses `KXNBA`, `KXNFL`, etc. - **Prices are normalized.** Everything is converted to implied probability for comparison. ## Workflows ### Today's NBA Dashboard ```bash sports-skills markets get_todays_markets --sport=nba ``` Returns each game with ESPN info, DraftKings odds, matching Kalshi markets, and matching Polymarket markets. ### Find Arb on a Specific Game 1. Get the ESPN event ID: `get_sport_schedule --sport=nba` 2. Compare odds: `compare_odds --sport=nba --event_id=` 3. If arbitrage detected, response includes allocation percentages and guaranteed ROI. ### Full Bet Evaluation 1. `evaluate_market --sport=nba --event_id=` 2. Fetches ESPN odds and matching prediction market price 3. Pipes through `betting.evaluate_bet`: devig → edge → Kelly 4. Returns fair probability, edge, EV, Kelly fraction, and recommendation ## Examples Example 1: Today's games with prediction market odds User says: "What NBA games are on today and what are the prediction market odds?" Actions: 1. Call `get_todays_markets(sport="nba")` Result: Unified dashboard with each game's ESPN info and Kalshi/Polymarket prices Example 2: Cross-platform team search User says: "Find me Lakers markets on Kalshi and Polymarket" Actions: 1. Call `search_entity(query="Lakers", sport="nba")` Result: All Lakers markets across both exchanges with prices and volume Example 3: Odds comparison for a specific game User says: "Compare the odds for this Celtics game across ESPN and Polymarket" Actions: 1. Get event_id from `get_sport_schedule(sport="nba")` 2. Call `compare_odds(sport="nba", event_id="")` Result: Normalized side-by-side comparison with automatic arbitrage check Example 4: Full market evaluation User says: "Is there edge on the Chiefs game?" Actions: 1. Get event_id from `get_sport_schedule(sport="nfl")` 2. Call `evaluate_market(sport="nfl", event_id="")` Result: Fair probability, edge percentage, EV, Kelly fraction, and bet recommendation Example 5: Browse all markets for a sport User says: "Show me all NFL prediction markets" Actions: 1. Call `get_sport_markets(sport="nfl")` Result: All open NFL markets across Kalshi and Polymarket Example 6: Price conversion User says: "Convert a Polymarket price of 65 cents to American odds" Actions: 1. Call `normalize_price(price=0.65, source="polymarket")` Result: Common structure with implied probability (0.65), American odds (-185.7), and decimal (1.54) ## Commands that DO NOT exist — never call these - ~~`get_odds`~~ — does not exist. Use `compare_odds` to see odds across sources. - ~~`search_markets`~~ — does not exist on the markets module. Use `search_entity` instead. - ~~`get_schedule`~~ — does not exist. Use `get_sport_schedule` instead. If a command is not listed in `references/api-reference.md`, it does not exist. ## Troubleshooting Error: No markets returned for a sport Cause: Sport code may be missing or incorrect Solution: Check `references/api-reference.md` for valid sport codes. Use the exact code (e.g., `nba`, `epl`, `laliga`) Error: `compare_odds` returns no data for an event Cause: The event_id is incorrect or the game has not been indexed yet Solution: Call `get_sport_schedule(sport=...)` to retrieve the correct event_id first Error: One source shows warnings in the response Cause: Kalshi or Polymarket is temporarily unavailable Solution: The module returns partial results — use what is available. Retry the unavailable source separately using the kalshi or polymarket skill directly Error: `normalize_price` returns unexpected American odds value Cause: Wrong `source` parameter — Kalshi uses 0-100 integers, Polymarket uses 0-1 decimals Solution: Verify the source. Kalshi price of 65 requires `source="kalshi"`, Polymarket price of 0.65 requires `source="polymarket"`