Championship-Winning Sports Analytics

Pit Rho puts data to work and actively informs decision making both on and off the track.

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What We Do

Pit Rho is a real-time, in-race strategy tool used in the NASCAR Cup Series. Pit Rho ingests competitors' laptime and pitstop data into a series of machine and deep learning models that predict a wide range of race variables, including competitors' behaviors, and recommends optimum race strategy on every lap for any car in the field based on those predicted behaviors. This robust cloud-based application performs more than one million calculations per lap while maintaining near 100% reliability under dynamic conditions and accounting for variations across multiple live data feeds.

Key Features

Exploits asynchronous architecture to ensure real-time information delivery, and rapid release cycles guarantee the latest technical data innovations are included.

Utilizes extra-trees classifier and Bayesian regression machine learning algorithms to create 30,000 decision tree nodes per race car pairs.

Allows the replay, review, and analysis of previous races while creating any combination of race scenarios in Pit Rho's Simulation Tool.

Adaptation of a modern technology stack for seamless integration of race telemetry data and other data intensive pro into Pit Rho.

How It Works

Data Ingestion

Ingest, clean, and store over 100,000 data points on every lap from telemetry, lap time, and pitstop streams.

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Process

Machine and deep learning models that adapt every lap to changing track conditions; the models project cars' future lap times, positions, and outcomes.

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Results

Optimum and predicted strategy and chassis adjustment recommendations for any car on any lap, updated in real-time.

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See Pit Rho in Action

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Implement cutting edge data science