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