🎁 Get the FREE AI Skills Starter Guide β€” Subscribe β†’
BytesAgainBytesAgain
BytesAgain β€Ί Skills β€Ί Kalshi Odds Scanner Pro
πŸ¦€ ClawHub

Kalshi Odds Scanner Pro

by @themsquared

Real-time scanner comparing Kalshi odds to 6 sportsbooks, auto-buys 8%+ edge plays with Kelly sizing on NBA, NCAAB, NHL, and MLB markets.

Versionv1.0.0
Downloads543
#legal
TERMINAL
clawhub install kalshi-odds-scanner-pro

πŸ“– About This Skill

Kalshi Odds Scanner Pro

Compare Kalshi prediction market prices vs 6 major sportsbooks in real-time. Fires automatically on 8%+ edge. Kelly-sized execution. The exact scanner used to deploy capital daily on Kalshi sports markets.

> πŸ’° Used to generate consistent returns on Kalshi sports markets. $79 value.

What It Does

  • Fetches live odds from The Odds API (6+ sportsbooks: DraftKings, FanDuel, BetMGM, Caesars, etc.)
  • Compares sportsbook-implied probabilities vs Kalshi ask prices
  • Fires on 8%+ edge (YES side) or 5%+ edge (NO side heavy favorites)
  • Kelly criterion position sizing (25% fractional Kelly, capped at $60)
  • NCAAB heavy-favorite NO-side insight: ~74% historical win rate when fav > 80%
  • Deduplicates β€” ONE side per game only

    • Setup

    1. Copy odds_scanner.py to your polymarket/trading directory 2. Get a free API key at the-odds-api.com 3. Set your Kalshi API credentials: - KALSHI_KEY_ID β€” your Kalshi API key ID - ~/.config/kalshi/private_key.pem β€” your Kalshi private key

    Edit constants at the top of the script: 

    ODDS_API_KEY = "your_key_here"
KALSHI_KEY_ID = "your_kalshi_key_id"

    Usage

    # Scan YES plays (default NBA)
python3 odds_scanner.py
    Scan NO plays (heavy favorites, 74% win rate)
    
python3 odds_scanner.py --side no
    Scan both YES and NO
    
python3 odds_scanner.py --side both
    Scan NCAAB (college basketball)
    
python3 odds_scanner.py --sport ncaab --side both
    Execute found plays on Kalshi
    
python3 odds_scanner.py --buy --sport nba --side both
    Set custom edge threshold
    
python3 odds_scanner.py --min-edge 0.10

    Supported Sports

    | Key | League | |-----|--------| | nba | NBA Basketball | | ncaab | NCAA Basketball | | nhl | NHL Hockey | | mlb | MLB Baseball |

    Edge Logic

    YES side: sportsbook_prob - kalshi_yes_ask > 8%

  • Example: Sportsbooks say Lakers win 72%, Kalshi YES at 62% β†’ +10% edge β†’ BUY

    • NO side: (1 - sportsbook_prob) - kalshi_no_ask > 5%

  • Example: Sportsbooks say team wins 85%, Kalshi NO at 8% β†’ true NO worth 15% β†’ +7% edge β†’ BUY NO

    • Kelly Sizing

    f = (b*p - q) / b  Γ— 0.25 (quarter Kelly)
  • MIN_BET = $10, MAX_BET = $60
  • RESERVE = $50 kept aside always

    • Integration

    Works with ensemble.py and momentum.py in the same directory for multi-model consensus gating.

    Requirements

  • Python 3.9+
  • cryptography library: pip install cryptography
  • The Odds API key (free tier: 500 requests/month)
  • Kalshi account with API access

    • πŸ’‘ Examples

    # Scan YES plays (default NBA)
python3 odds_scanner.py
    Scan NO plays (heavy favorites, 74% win rate)
    
python3 odds_scanner.py --side no
    Scan both YES and NO
    
python3 odds_scanner.py --side both
    Scan NCAAB (college basketball)
    
python3 odds_scanner.py --sport ncaab --side both
    Execute found plays on Kalshi
    
python3 odds_scanner.py --buy --sport nba --side both
    Set custom edge threshold
    
python3 odds_scanner.py --min-edge 0.10

    βš™οΈ Configuration

    1. Copy odds_scanner.py to your polymarket/trading directory 2. Get a free API key at the-odds-api.com 3. Set your Kalshi API credentials: - KALSHI_KEY_ID β€” your Kalshi API key ID - ~/.config/kalshi/private_key.pem β€” your Kalshi private key

    Edit constants at the top of the script: 

    ODDS_API_KEY = "your_key_here"
KALSHI_KEY_ID = "your_kalshi_key_id"