Scans thousands of Kalshi markets, cross-references 12 sportsbooks and free data APIs, prices fair value with a normal-CDF model, and executes Kelly-sized limit orders — every bet cleared through 13 risk gates and logged with fill-accurate accounting for closing-line-value tracking.
| Category | Coverage | Data sources |
|---|---|---|
| 🏟️ Sports betting | NFL, NBA, MLB, NHL, NCAAB/NCAAF, UFC, soccer/MLS, F1, NASCAR, PGA, IPL, esports — 27 filters across 18 sports | The Odds API (12 sportsbooks), ESPN, NHL/MLB Stats, NWS |
| 🏆 Championship futures | Super Bowl, NBA Finals, Stanley Cup, World Series, PGA Tour — priced with N-way de-vig | Sportsbook outright odds |
| 📈 Prediction markets | Crypto (BTC, ETH, XRP, SOL, DOGE), S&P 500 + VIX, weather (13 cities), politics | CoinGecko, Yahoo Finance, NWS |
Fair value is a sport-specific normal-CDF model over a weighted-median consensus of 12 sportsbooks (sharp books like Pinnacle/Circa weighted 3×, recreational 0.7×), then adjusted by team-stats win%, sharp-money line movement, weather, pitcher matchups, rest/back-to-back fatigue, and book-disagreement signals. Sports Guide → breaks down each signal and the de-vig math.
Important
Every scan defaults to preview mode. No money is risked until you pass --execute. Each scan row shows a Gate column (R18) that previews whether it will pass the static risk gates — ok if all clear, or a short label (score, conf, no-fav, pred-off, live-off, etc.) for the failing gate.
Every order must clear gates 1-7 (including 3.5, 4.5, 4.6, 4.7). Gates 8-9 cap sizing instead of rejecting.
| # | Gate | Action |
|---|---|---|
| 1 | Daily loss limit | Reject at -$250 |
| 2 | Position count | Reject at 50 open |
| 3 | Edge threshold | Reject below floor (3% global; 4% MLB/NBA/NCAAB) |
| 3.5 | Market price floor | Reject bets priced below MIN_MARKET_PRICE (default $0.06 — lottery-ticket filter) |
| 4 | Composite score | Reject below 6.0/10 |
| 4.5 | Min confidence | Reject below MIN_CONFIDENCE (default medium) |
| 4.6 | NO-side favorite | Reject NO bets <25¢ unless edge ≥25% AND confidence=high |
| 4.7 | Prediction-market safety | Reject crypto/weather/spx/mentions/companies/politics unless ALLOW_PREDICTION_BETS=true (R25) |
| 5 | Duplicate check | Reject same market |
| 6 | Per-event cap | Reject at 2/game |
| 7 | Series dedup | Reject same matchup bet within window (MLB/NHL 72h, others 48h; per-sport via SERIES_DEDUP_HOURS_<SPORT>) |
| 8 | Bet size cap | Cap at $100 |
| 9 | Bet ratio cap | Cap at 3x batch median |
All limits configurable via .env. Every gate traces to a documented calibration finding — the per-rule history (why the price floor, the NO-side guard, the per-sport edge floors, one-way confidence bumps, and the prediction-market block exist) lives in Architecture → Risk Management.
Bet size scales with edge, divided by batch count to control total exposure. Edge is soft-capped above 15% before sizing (trusted_edge()) to damp Kelly on likely-overstated signals — raw edge remains in gates and reports.
bet = max(unit, (kelly_frac / batch) * trusted_edge(edge) * bankroll)
Result is capped by max bet ($100), the bet-ratio cap, and available bankroll. Architecture → Position Sizing has the full edge→contracts worked example and every KELLY_* knob.
# 0. Clone repo and enter project
git clone https://github.com/michaelschecht/Edge-Radar.git
cd Edge-Radar
# 1. Create + activate virtual environment
python -m venv .venv
# macOS/Linux (bash/zsh):
source .venv/bin/activate
# Windows PowerShell:
# .venv\Scripts\Activate.ps1
# 2. Install dependencies and create env file
python -m pip install --upgrade pip
pip install -r requirements.txt
cp .env.example .env
# 3. Verify environment (API keys, dependencies)
python scripts/doctor.py
# 4. Preview opportunities (no money risked)
python scripts/scan.py sports --filter nba
# 5. Execute with risk controls
python scripts/scan.py sports --filter nba --execute --unit-size 1 --max-bets 5
# 6. Settle bets and view P&L
python scripts/kalshi/kalshi_settler.py report --detail --saveTip
All scanners share the same flags: --execute, --unit-size, --max-bets, --pick, --ticker, --save, --date, --exclude-open. Use --date tomorrow --exclude-open to avoid double-betting.
| Guide | What it covers |
|---|---|
| Setup Guide | First-time install, API keys + RSA private key generation, .env wiring, safe rollout plan (dry-run → low-stakes → normal), automation, ongoing monitoring, troubleshooting |
Expand any section for copy-paste CLI examples by workflow.
Sports Betting
python scripts/scan.py sports --filter nhl
python scripts/scan.py sports --filter mlb --execute --unit-size 1 --max-bets 10
python scripts/scan.py sports --filter mlb --date tomorrow --exclude-open
python scripts/scan.py sports --filter nba --saveChampionship Futures
python scripts/scan.py futures --filter nba-futures
python scripts/scan.py futures --filter mlb-futures --execute --unit-size 2 --max-bets 5
python scripts/scan.py futures --filter nba-futures --savePrediction Markets
python scripts/scan.py prediction --filter crypto
python scripts/scan.py prediction --filter weather
python scripts/scan.py prediction --filter crypto --execute --unit-size 1 --max-bets 5Portfolio & Settlement
python scripts/kalshi/kalshi_executor.py status --save
python scripts/kalshi/risk_check.py --report positions --save
python scripts/kalshi/kalshi_settler.py settle
python scripts/kalshi/kalshi_settler.py report --detail --saveBacktesting
python scripts/backtest/backtester.py
python scripts/backtest/backtester.py --simulate --save
python scripts/backtest/backtester.py --sport mlb --confidence high --min-edge 0.10Analyzes settled trades for win rate, ROI, profit factor, Sharpe ratio, equity curves, max drawdown, and calibration — broken down by sport, category, confidence level, and edge bucket. The --simulate flag runs what-if scenarios across edge thresholds, confidence tiers, and categories; --save exports reports.
Edge-Radar ships with two slash commands for Claude Code:
| Skill | Definition | Description |
|---|---|---|
/edge-radar |
skills/edge-radar/SKILL.md |
Unified command center — scan, bet, status, settle, risk, detail, backtest across Kalshi sports, futures, and prediction markets. |
/edge-radar-analysis |
skills/edge-radar-analysis/SKILL.md |
Post-hoc performance report — trade ledger + slices by sport, category, side, edge bucket, confidence, price, calibration, longshots, streaks, daily P&L. |
The skill source of truth lives in
skills/. Claude Code loads them from.claude/skills/, which on Windows are directory junctions toskills/(git-ignored, sincecore.symlinks=false). After a fresh clone, recreate the junctions once:pwsh -File scripts/setup/link_skills.ps1.
Prefer copy-paste recipes over slash commands? The Prompt Library has 35 ready-to-use natural-language prompts — daily scans, execution sessions, live/prop betting, futures, portfolio routines, and backtesting — grouped by workflow.
/edge-radar status # Balance, positions, P&L
/edge-radar scan nba # Preview NBA opportunities
/edge-radar bet mlb --unit-size 1 # Scan + execute on confirm
/edge-radar settle # Settle + P&L report
/edge-radar-analysis 30 --save # 30-day performance report to reports/Performance/
Routes natural language to the correct scanner, enforces all risk gates, always previews before executing. All CLI flags work inline.
Note
Requires Claude Code CLI, Desktop, or IDE extension.
Gemini CLI / OpenAI Codex — add the skill content to your GEMINI.md or AGENTS.md for equivalent functionality.
Pre-built scripts scan all sports, rank by composite score, and execute with Kelly sizing. See the Automation Guide.
# Install all scheduled tasks at once
python scripts/schedulers/automation/install_windows_task.py install all| Task | Schedule | Description |
|---|---|---|
daily-summary |
4:50 AM PT | Morning P&L digest — yesterday settled + open exposure + today pending + 7d context. Emailed at 5:00 AM PT (U2, 2026-04-30) |
scan |
8:00 AM ET | Preview scan — saves report, no bets |
execute |
8:00 AM ET | Scan + execute — places live orders |
settle |
11:00 PM ET | Settle bets, update P&L |
next-day |
9:00 PM ET | Scan + execute tomorrow's games |
calibration |
2:00 AM, 1st of month | 30-day calibration report — Brier, calibration curve, prescriptive recommendations |
Reports save to reports/Sports/schedulers/ with full execution details.
Want the complete pipeline — emails, midday/late runs, weekly calibration/backtest/analysis — beyond the installer's core tasks? See the owner's live task-schedule — the full ~20-task roster the repo owner actually runs (documented as a recommended starting point), with copy-paste .bat/.sh templates and schtasks registration.
| Guide | Description |
|---|---|
| Documentation Index | Central index and map linking all guides, references, and specifications |
| Setup Guide | Install, API keys, .env, safe rollout, automation, and monitoring — the single end-to-end operator guide |
| Automation Guide | Windows Task Scheduler for daily betting — one-command installer for the core tasks |
| Task Schedule (owner's live setup) | The full ~20-task automation pipeline the repo owner runs — recommended template, with .bat/.sh templates and schtasks setup |
| Scripts Reference | Every script, flag, and example |
| Kalshi Coverage & Guides | Coverage matrix — which sports/markets are configured and what bet types |
| Sports Guide | Edge detection model, consensus de-vig, daily workflow |
| Futures Guide | NFL, NBA, NHL, MLB, golf championships |
| Prediction Markets | Crypto, weather, S&P 500, politics |
| Architecture | Pipeline, edge models, risk gates, data flow, and project structure |
| MLB Filtering | 10 filter categories for MLB picks |
| Roadmap | All enhancements — completed & pending |
| Changelog | Full project history |
All external data is free. Only Kalshi requires a funded account.
| API | Purpose |
|---|---|
| Kalshi | Market data + order execution (API key + RSA signing) |
| The Odds API | 12 US sportsbook odds (500 free req/mo) |
| ESPN | NBA, NFL, NCAAB, NCAAF standings + line movement |
| NHL Stats API | Standings, goal differential, last 10 record |
| MLB Stats API | Standings, run differential, pitcher stats |
| NWS | Hourly forecasts for 61 NFL/MLB outdoor venues |
| CoinGecko | Crypto prices + 24h volatility |
| Yahoo Finance | S&P 500 + VIX implied volatility |
Setup • Architecture • Scripts • Changelog
Built with Python, scipy, and too many API calls — Back to top