DARWINLIVE
bayesian confidence enginemonte carlo simulationspattern detection v3.1polymarket edge analysisregime detectionpaper trading simulationself-evolution enginellm-powered analysisreal-time coingecko pricesmomentum scoringbayesian confidence enginemonte carlo simulationspattern detection v3.1polymarket edge analysisregime detectionpaper trading simulationself-evolution enginellm-powered analysisreal-time coingecko pricesmomentum scoring

Paper-trading research feed. Not investment advice. No real capital is traded on your behalf.

Overall Win Rate
0 resolved predictions
1h accuracy
no data
4h accuracy
no data
Paper Trading
no trades yet
Timeframe
BTC
BITCOIN
Price Target — 1w
Confidence Breakdown
Key Factors
Analysis
Ξ
ETH
ETHEREUM
Price Target — 1w
Confidence Breakdown
Key Factors
Analysis
Polymarket Edge

Model vs Market Odds

polymarket.com ↗

Edge = Darwin model probability minus Polymarket YES price. Positive edge = model more bullish than market. Not financial advice.

Prediction Log

Direction Accuracy

Asset
Timeframe

1h predictions logged hourly · 4h every 4 hours · 1d at midnight UTC. Each resolves against actual price after its timeframe elapses. Accuracy = correct directional calls ÷ total resolved.

Confidence Calibration

How Honest Is the Engine?

When the engine says “70% confident,” it should be right about 70% of the time. Bars below actual accuracy mean the model is over-confident. Above = under-confident (conservative).

0 resolved
·

Not enough data for calibration analysis.

50–60%
0 preds
60–70%
0 preds
70–80%
0 preds
80–90%
0 preds
90%+
0 preds

Each bucket compares stated confidence (X) vs actual accuracy (Y). A perfectly calibrated model traces the diagonal. Over-confidence shows below the line, under-confidence above.

Paper Trading

Polymarket Simulation · 3 × $10k Wallets

Filter

3 independent $10k virtual wallets — one per timeframe. Kelly Criterion bet sizing (half-Kelly, ≤10% balance). Even-money payout. Min 55% confidence to bet. Settles after each timeframe elapses.

Gitlawb Research · Self-Evolution

Darwin Engine

A self-evolving prediction engine, paper-traded. Currently pre-alpha — the model is still learning. Research output only; not financial advice.

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Auto-trigger: win rate < 80%
Current Signal Weights

Engine parameters evolve automatically via Bankr LLM (Claude Opus) when win rate drops below 80%. Pre-alpha — not financial advice.