Sports Markets — Trading Context

When to load

When analyzing PM contracts about: sports outcomes, player props, game results, championship futures.

Instructions

Inject silently. Use to inform analysis.

PM Sports vs Sportsbooks

Kalshi and Polymarket offer sports contracts but they are NOT sportsbooks:

• No vig/juice transparency — sportsbooks show -110 lines; PM shows YES/NO prices
• Binary contracts — YES/NO at a price, not spreads/totals (though some PM markets approximate these)
• Thin liquidity — PM sports markets have MUCH less volume than DraftKings/FanDuel
• Wider spreads — 5-15c spreads on PM vs 2-4c equivalent at sportsbooks

Key implication: If the same event is available at a sportsbook with tighter lines, PM sports contracts are likely mispriced relative to the sharp market. The sportsbook line is ground truth.

Cross-Referencing with Sharp Lines

Sharp sportsbooks (Pinnacle, Circa, Bookmaker) set efficient lines based on ~$1B+ handle. PM markets with $50K volume are NOT going to be more efficient.

Process:

1. Find the sharp line for the same event
2. Convert to implied probability: fair prob = 1 / decimal odds (remove vig)
3. Compare to PM price
4. If PM price diverges >5c from de-vigged sharp line → potential trade

Injury Reports

• NFL: official injury reports (Wednesday-Friday practice participation + game-day designations)
• NBA: injury reports ~5:30 PM ET (1 hour before most games)
• MLB: less structured, beat reporter intel matters more
• Soccer: manager press conferences 1-2 days before match

PM signal: Injury news moves PM prices SLOWER than sportsbook lines because PM has less automated/professional participation. If a key player is ruled out and the sportsbook line moves 3 points but PM hasn't adjusted → arbitrage.

Sport-Specific Notes

NFL: Most efficient PM sports market (highest volume). Regular season games have the most data for modeling. Playoff/Super Bowl contracts attract casual money → more mispricing.

NBA: Player prop contracts on PM are often mispriced because PM participants don't track minutes/rest/back-to-backs. Check injury report + recent minutes trends.

MLB: Highly variable single-game outcomes. Starting pitcher is the single biggest variable. PM MLB contracts have very thin liquidity.

Soccer: International tournaments and Champions League have PM volume. League matches are very thin. Home/away advantage is significant and sometimes underpriced.

Championship/Futures Contracts

Long-dated "Will X win championship?" contracts:

• High vig baked in (both YES and NO are overpriced relative to fair probability)
• Illiquid — hard to exit before resolution
• The market systematically overprices "popular" teams and underprices unpopular ones (public bias)
• Sharp approach: fade popular teams in futures markets

Trading Rules

1. ALWAYS cross-reference PM sports prices with sharp sportsbook lines. The sportsbook is more efficient.
2. Injury reports are the single biggest alpha source for sports PM — PM reacts slower than sportsbooks.
3. PM sports spreads are wide (5-15c). Only trade when your edge exceeds the spread cost.
4. Championship futures on PM are overpriced for popular teams. Fade public bias.
5. Volume matters — very thin PM sports markets can be manipulated by single large orders.
6. Sports contracts have hard deadlines (game time). No extension risk, but also no time for the market to correct.

SimpleFunctions integration

For live data on this theme through SimpleFunctions:

# CLI (npm install -g @spfunctions/cli)
sf query "sports" --json --limit 5
sf investigate "sports" --json --limit 5

# HTTP API (free, no auth required for these endpoints)
curl "https://simplefunctions.dev/api/public/scan?q=sports"
curl "https://simplefunctions.dev/api/agent/world"

Reference: <https://docs.simplefunctions.dev>