Research-grade pattern recognition for fantasy football. We study the weekly flow of player performance waves with computational precision.
Wave Inertia Lab is a performance research facility. We study the cyclical nature of athlete output using advanced pattern recognition and statistical analysis.
Like wave physics, player performance isn't random—it oscillates. Our algorithms track these cycles to predict hot and cold stretches before they happen.
Our proprietary algorithms analyze years of performance data to identify wave patterns invisible to traditional analysis.
Identifies cyclical performance patterns using spectral analysis and time-series decomposition across multiple seasons.
Measures performance inertia—how likely players are to continue hot or cold streaks based on historical phase transitions.
Machine learning models trained on wave cycles to forecast upcoming performance phases with measurable confidence intervals.
Live processing of game data to update wave positions and recalibrate predictions as new information becomes available.
Rigorous backtesting against historical data with transparent accuracy metrics and confidence scoring.
Unique performance signatures for each athlete showing cycle length, amplitude, and consistency patterns.
Real players, real data, real predictions. Updated weekly.
RB · San Francisco 49ers
TE · San Francisco 49ers
QB · Kansas City Chiefs
Get access to our performance cycle analysis platform and start making data-driven decisions with confidence.