I Compared 5 Python Trading Strategies Head-to-Head Using Overnight Tournaments

I've been running automated paper trading for a while now, and one thing I kept running into: which strategy is actually performing best right now? Not last month. Not in a backtest from 3 years ago. Right now. The answer I kept giving myself was "I'll check the logs." The logs were a mess. So I built a strategy ranking system into TradeSight — my self-hosted Python trading lab — and it changed how I think about algorithmic trading entirely. The Problem with "Which Strategy Is Better?" Most algo trading systems commit to one strategy. You pick RSI crossover, you backtest it, you deploy it. Done. The problem: market regimes change. What works in a trending market (EMA crossovers crush it) completely falls apart in a choppy sideways market (RSI oscillators do better). No single strategy dominates all conditions. So instead of picking one, I run them all simultaneously and let performance decide. How the Tournament System Works TradeSight runs what I call overnight strategy tournaments .