Quant-Grade Sports Betting Analytics
Monte Carlo simulation meets Kelly Criterion. 10,000+ iterations per game. 12 leagues. Real edge, not entertainment.
View Today's Free Projections Browse Game Predictions Free Calculators Go PremiumHow It Works
Four quantitative layers work together to identify genuine edges in sports betting markets.
Monte Carlo Simulation
Every game is simulated 10,000+ times using league-specific engines. NBA uses possession-by-possession modeling. NHL uses zone-based shot sequencing with expected goals. CBB employs player-level matchup analysis. Each iteration produces a full game trajectory, building a probability distribution that captures the full range of outcomes, not just a single point estimate.
Kelly Criterion Sizing
Once an edge is identified, the Kelly Criterion determines optimal bet sizing based on the magnitude of the edge and the implied probability from the market. This mathematical framework, originally developed for information theory, maximizes long-term bankroll growth while controlling for variance. Every pick includes precise unit recommendations calibrated by league.
Bayesian Calibration
Raw model probabilities are calibrated using Bayesian shrinkage to correct for overconfidence. If the model says 72% but historically that range hits at 65%, the system adjusts downward. This self-correcting mechanism uses thousands of resolved predictions as training data, ensuring the probabilities you see reflect actual observed frequencies.
Real-Time Odds Integration
Live odds from major sportsbooks are ingested multiple times daily. The system compares model-implied probabilities to market-implied probabilities to calculate true edge. Only picks where the model identifies a statistically significant discrepancy between simulation output and market pricing are surfaced as recommendations.
Multi-League Coverage
Purpose-built simulation engines for each league, calibrated against historical outcomes.
Each league uses a dedicated simulation engine tuned to its specific dynamics. The NBA engine models individual possessions, shot contests, and transition opportunities. The NHL engine tracks zone entries, shot quality via expected goals, and goaltender form. College basketball accounts for EvanMiya BPR ratings, tempo, and player-level matchup variance. Soccer uses play-by-play simulation with expected goals from FBref data. Every engine is calibrated against thousands of historical games.
Performance Snapshot
Verified results. No cherry-picking. Every pick tracked from the moment it is published.
The free tier is the publicly verifiable record — every free pick is published daily before games start, then resolved automatically against final scores. Performance is reported by tier, and every number regenerates daily as results come in. View the full breakdown by tier, league, and bet type on the live track record page.
Today's Game Predictions
Monte Carlo simulations for every game on today's slate. Updated daily.
Tennis
Abedallah Shelbayh vs Dhakshineswar Suresh Adam Walton vs Jesper De Jong Alec Beckley vs Benito Sanchez Martinez Alec Deckers vs Oscar Weightman +78 more games Open the live Tennis slate →CS2
5Star vs Alter Ego Black Phoenix vs Ex Ruby Black Phoenix vs Lavked Black Phoenix vs Nordic Partners +27 more games Open the live CS2 slate →Soccer
Ac Milan vs Torino As Monaco vs Le Havre Aston Villa vs Brighton And Hove Albion Barcelona vs Elche Cf +18 more games Open the live Soccer slate →Olympus Oracle — Model-vs-Market Intelligence
Everyone tracks prediction-market whales. Oracle asks the question nobody else does: does the whale agree with a 10,000-run simulation?
Oracle ingests public trades from Polymarket and Kalshi, profiles each wallet on its resolved-trade history, classifies likely sharp or insider-like flow with Bayesian quality scores, and then cross-references whale consensus against our own independently generated Monte Carlo edges. Sharp money and model edge agreeing from two independent directions is a fundamentally stronger signal than either alone. Oracle signals are premium-only; the mechanism is public: read how whale tracking and model cross-validation work →
Ask Your AI About Olympus — Connect in 30 Seconds
Olympus Bets Analytics is the first quant sports betting platform with a public read-only Model Context Protocol (MCP) server. Connect it to ChatGPT, Claude, or any MCP-compatible AI and ask things like "What does the Olympus model like tonight?" or "Show me Olympus's last 30 days" — live answers from our actual pipeline, no scraping, no API keys, no signup.
30-Second Setup Guide — Claude, ChatGPT, Cursor & More
MCP Server
Streamable HTTP transport at https://app.olympus-bets.com/mcp. Compatible with Claude Desktop, Claude.ai, ChatGPT, Cursor, and Windsurf — copy-paste setup for every client. Discovery manifest at /.well-known/mcp/server-card.json. Twenty read-only tools: 15 public tools—get_todays_projections, get_performance_summary, get_track_record, get_methodology, get_engine_versions, get_model_vs_market, get_league_schedule, get_game_recommendation, get_pick_history, get_brand_card, get_subscription_options, get_data_status, search_entities, get_team_profile, and get_player_profile—plus five protected tools requiring an eligible MCP subscription token: get_premium_slate, get_premium_game_recommendation, get_premium_history, MCP Pro's get_projection_history for full available queryable normalized projection history, including model-only observations and supported player-prop markets where archive coverage exists, and get_oracle_board for the whale-vs-model Oracle Bettable Board, flat 0.5u sized and ordered by event start time only. Resolved published picks remain public.
Public REST API
Full OpenAPI 3.1 spec. Read-only endpoints at /webmcp/api/* for free projections, performance summary, resolved history, simulations, schedules, and team/player profiles. CORS enabled, no auth required. Rate-limited at 120 req/min.
Resolved-Pick Dataset (CSV)
Full downloadable CSV of every resolved projection — line, odds, model probability, edge, units, outcome, units won. Licensed CC-BY-4.0 for research, journalism, and citation use. Updated daily.
llms.txt + llms-full.txt
Structured documentation files at /llms.txt and /llms-full.txt for LLM crawlers. AI discovery manifest at /.well-known/ai.json. Robots.txt explicitly allows GPTBot, ClaudeBot, PerplexityBot, Google-Extended, Anthropic-AI.
Using Claude or ChatGPT in the browser? Settings → Connectors → Add custom connector, paste https://app.olympus-bets.com/mcp, done. Desktop apps (Claude Desktop, Cursor, Windsurf) take a small config block — copy-paste blocks for every client are here.
Or install in one command via Smithery:
npx @smithery/cli@latest install olympus-bets-analytics --client claude
Why Olympus Bets
Transparent Track Record
Every pick is recorded the moment it is published. Results are resolved automatically. No retroactive edits, no deleted losses, no cherry-picked screenshots. The full history is available on the track record page for anyone to audit.
Research Tool, Not a Tout
Olympus Bets is a quantitative analytics platform, not a tipster service. The models provide probability distributions, edge calculations, and Kelly-optimized sizing. You make the decisions with better information than the market provides.
Free Tier Available
Access daily free projections across multiple leagues at no cost. See the methodology in action, verify performance against the track record, and decide if the premium tier is right for your approach. No credit card required for the free tier.
Self-Learning Systems
The platform runs daily calibration cycles that incorporate new results. Regime detection adjusts thresholds based on current market conditions. Profitability zone analysis identifies which sub-niches are producing edge and which have gone cold. The models evolve continuously.