/betting

name: betting
description: |
  Betting analysis — odds conversion, de-vigging, edge detection, Kelly criterion, arbitrage detection, parlay analysis, and line movement. Pure computation, no API calls. Works with odds from any source: ESPN (American odds), Polymarket (decimal probabilities), Kalshi (integer probabilities).

  Use when: user asks about bet sizing, expected value, edge analysis, Kelly criterion, arbitrage, parlays, line movement, odds conversion, or comparing odds across sources. Also use when you have odds from ESPN and a prediction market price and want to evaluate whether a bet has positive expected value.
  Don't use when: user asks for live odds or market data — use polymarket, kalshi, or the sport-specific skill to fetch odds first, then use this skill to analyze them.
license: MIT
metadata:
  author: machina-sports
  version: "0.2.0"

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 `fr