Real-time scanner comparing Kalshi odds to 6 sportsbooks, auto-buys 8%+ edge plays with Kelly sizing on NBA, NCAAB, NHL, and MLB markets.
# 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. > ๐ฐ **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 โ 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](https://the-odds-api.com) 3. Set your Kalshi API credentials: - `KALSHI_KEY_ID` โ your Kalshi API key ID - `~/.config/kalshi/private_key.pem` โ your Kalshi private key Edit constants at the top of the script: ```python ODDS_API_KEY = "your_key_here" KALSHI_KEY_ID = "your_kalshi_key_id" ``` ## Usage ```bash # 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% โ +10% edge โ BUY **NO side:** `(1 - sportsbook_prob) - kalshi_no_ask > 5%` - Example: Sportsbooks say team wins 85%, Kalshi NO at 8% โ true NO worth 15% โ +7% edge โ BUY NO ## Kelly Sizing ``` f = (b*p - q) / b ร 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
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