Betting

Betting Analysis

Before writing queries, consult references/api-reference.md for odds formats, command parameters, and key concepts.

Quick Start

sports-skills betting convert_odds --odds=-150 --from_format=american
sports-skills betting devig --odds=-150,+130 --format=american
sports-skills betting find_edge --fair_prob=0.58 --market_prob=0.52
sports-skills betting evaluate_bet --book_odds=-150,+130 --market_prob=0.52
sports-skills betting find_arbitrage --market_probs=0.48,0.49
sports-skills betting parlay_analysis --legs=0.58,0.62,0.55 --parlay_odds=600
sports-skills betting line_movement --open_odds=-140 --close_odds=-160

Python SDK:

from sports_skills import betting

betting.convert_odds(odds=-150, from_format="american")
betting.devig(odds="-150,+130", format="american")
betting.find_edge(fair_prob=0.58, market_prob=0.52)
betting.find_arbitrage(market_probs="0.48,0.49")
betting.parlay_analysis(legs="0.58,0.62,0.55", parlay_odds=600)
betting.line_movement(open_odds=-140, close_odds=-160)

CRITICAL: Before Any Analysis

CRITICAL: Before calling any analysis command, verify:

• Odds format is correctly identified (american, decimal, or probability).
• ESPN odds are de-vigged with devig before computing edge vs prediction market prices.
• This module computes — it does not fetch. Obtain odds from sport-specific skills or polymarket/kalshi first.

Workflows

Compare ESPN vs Polymarket/Kalshi

1. Get ESPN moneyline odds (e.g., from nba get_scoreboard): Home: -150, Away: +130 2. Get Polymarket/Kalshi price for the same outcome (e.g., home at 0.52) 3. De-vig: devig --odds=-150,+130 --format=american → Fair: Home 57.9%, Away 42.1% 4. Compare: find_edge --fair_prob=0.579 --market_prob=0.52 → Edge: 5.9%, EV: 11.3% 5. Or all in one step: evaluate_bet --book_odds=-150,+130 --market_prob=0.52

Arbitrage Detection

1. Get best price per outcome from different sources (Polymarket home at 0.48, Kalshi away at 0.49) 2. find_arbitrage --market_probs=0.48,0.49 --labels=home,away 3. Total implied 0.97 (< 1.0) → arbitrage found, guaranteed ROI: 3.09%

Parlay Evaluation

1. De-vig each leg: Leg 1 → 0.58, Leg 2 → 0.55, Leg 3 → 0.50 2. parlay_analysis --legs=0.58,0.55,0.50 --parlay_odds=600 3. Returns combined fair probability, edge, and Kelly fraction

Line Movement Analysis

1. Get ESPN open and close lines: Open -140, Close -160 2. line_movement --open_odds=-140 --close_odds=-160 3. Returns probability shift, direction, and classification (sharp_action, steam_move, etc.)

Examples

Example 1: Edge check using ESPN and Polymarket prices User says: "Is there edge on the Lakers game? ESPN has them at -150 and Polymarket has them at 52 cents" Actions: 1. Call devig(odds="-150,+130", format="american") → fair home probability ~58% 2. Call find_edge(fair_prob=0.58, market_prob=0.52) → edge ~6%, positive EV 3. Call kelly_criterion(fair_prob=0.58, market_prob=0.52) → optimal bet fraction Result: Present edge percentage, EV per dollar, and recommended bet size as % of bankroll

Example 2: Arbitrage opportunity detection User says: "Can I arb this? Polymarket has home at 48 cents and Kalshi has away at 49 cents" Actions: 1. Call find_arbitrage(market_probs="0.48,0.49", labels="home,away") 2. Check arbitrage_found in result Result: If arbitrage: present allocation percentages and guaranteed ROI. If not: present overround and explain no guaranteed profit

Example 3: Parlay evaluation User says: "Is this 3-leg parlay at +600 worth it?" Actions: 1. De-vig each leg to get fair probabilities (e.g., 0.58, 0.62, 0.55) 2. Call parlay_analysis(legs="0.58,0.62,0.55", parlay_odds=600) Result: Present combined fair probability, edge, EV, +EV or -EV verdict, and Kelly fraction

Example 4: Line movement interpretation User says: "The line moved from -140 to -160, what does that mean?" Actions: 1. Call line_movement(open_odds=-140, close_odds=-160) Result: Present probability shift, direction, magnitude, and classification (sharp action, steam move, etc.)

Example 5: De-vig a standard spread User says: "What are the true odds for this spread? Both sides are -110" Actions: 1. Call devig(odds="-110,-110", format="american") Result: Present each side as 50% fair probability, vig is ~4.5%

Example 6: Odds format conversion User says: "Convert -200 to implied probability" Actions: 1. Call convert_odds(odds=-200, from_format="american") Result: Present 66.7% implied probability and 1.50 decimal odds

Commands that DO NOT exist — never call these

• ~~get_odds~~ — does not exist. This module analyzes odds; it does not fetch them. Use nba-data/nfl-data/etc. for ESPN odds, or polymarket/kalshi for prediction market prices.
• ~~calculate_ev~~ — does not exist. Use find_edge or evaluate_bet instead.
• ~~compare_markets~~ — does not exist. Use the markets skill for cross-platform comparison.

If a command is not listed in references/api-reference.md, it does not exist.

Troubleshooting

Error: ValueError: unknown format when calling convert_odds Cause: The from_format parameter is not one of american, decimal, or probability Solution: Use exactly american, decimal, or probability as the format string

Error: find_edge returns negative EV when a positive edge is expected Cause: Fair probability and market probability may be reversed, or de-vigging was skipped Solution: Run devig on sportsbook odds first, then pass the de-vigged fair_prob to find_edge

Error: find_arbitrage shows no arbitrage even when prices seem low Cause: Prices may sum to more than 1.0 when all outcomes are correctly included Solution: Verify you are using the correct probabilities for all outcomes; check total_implied in the result

Error: Kelly fraction is very high (greater than 0.5) Cause: Edge estimate is very large — often from a miscalculated fair probability Solution: Use half-Kelly or quarter-Kelly for conservative sizing. Re-verify fair probability via devig

Betting Analysis — API Reference

Odds Formats

Conversion rules:

• American negative: prob = -odds / (-odds + 100). Example: -150 → 150/250 = 0.600
• American positive: prob = 100 / (odds + 100). Example: +130 → 100/230 = 0.435
• Decimal: prob = 1 / odds. Example: 1.67 → 0.599
• Kalshi prices (0-100 integer): divide by 100 to get probability format

Commands

Key Concepts

• Vig/Juice: The sportsbook's margin. A -110/-110 line implies 52.4% + 52.4% = 104.8% total (4.8% overround). De-vigging removes this to get fair probabilities.
• Edge: The difference between your estimated true probability and the market price. Positive edge = profitable in expectation.
• Kelly Criterion: Optimal bet sizing. f* = (fair_prob - market_prob) / (1 - market_prob). For conservative sizing, use half-Kelly (×0.5) or quarter-Kelly (×0.25).
• Expected Value (EV): Average return per dollar bet. EV = fair_prob / market_prob - 1.
• Arbitrage: When prices across sources don't sum to 100%, you can bet all outcomes and guarantee profit regardless of the result.
• Parlay: Multi-leg bet where all legs must win. Combined probability = product of individual leg probabilities. Higher risk, higher reward.
• Line Movement: How odds change between open and close. Large moves toward one side suggest sharp/professional money. Reverse line movement (ML and spread moving opposite directions) suggests a public vs sharp split.