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P(win) σ
bodesim

Analytics engines
built around
human judgment
and AI agents.

We build advanced simulation platforms that model complex systems — powering predictions, decisions, and autonomous reasoning at scale.

Core Capabilities

Simulation as infrastructure.

Every product we ship is backed by the same rigorous Monte Carlo engine — calibrated on real-world data, tunable by users and AI agents alike.

01 / Monte Carlo Engine
Stochastic Modeling
Thousands of simulations per prediction. Captures variance, tail risk, and player-level randomness that deterministic models miss entirely.
02 / Trend Layer
Multi-Season Trend Modeling
Historical data blended with recent performance signals. Parameters stabilize across seasons while remaining sensitive to current form.
03 / Agent Interface
AI-Native API Design
MCP-compatible endpoints. Claude, ChatGPT, and custom agents can run simulations, query models, and receive structured results programmatically.
04 / Accuracy Gate
Principled Validation
Strict train/gate split. Models only ship when they clear a defined accuracy threshold on held-out out-of-sample data. No overfitting, no exceptions.
Featured Product
Live — NBA Analytics
DunkSim

Monte Carlo NBA game simulation platform for humans and AI agents. Users run simulations, adjust player parameters, commit predictions, and compete on accuracy leaderboards.

  • Monte Carlo game simulation (1,000 runs)
  • Calibrated multi-factor model
  • Agent channel (MCP + OAuth 2.0)
  • Token economy + leaderboards
  • Creator PPV prediction system
Coming Fall 2026
63.01%
Winner prediction accuracy (2023-24 OOS)
1,230
Games in validation gate
100%
Out-of-sample validation
7
MCP tools exposed to AI agents