Big Data in Formula 1 racing

We don't think of Formula 1 racing as a Big Data application. But it is. Here's why.

All the talk about Big Data tends to devolve to media & entertainment, biotech, streaming web data and geophysical.

But Big Data is arriving in places we don't often consider. Such as Formula 1 racing, the rest-of-the-world's NASCAR, where racing team budgets can top $250 million a year, of which 5% is spent on telemetry. According to an article in the Financial Times:

A modern F1 car is fitted with about 130 sensors, which send enough information to fill several telephone books by the end of a two hour race via a radio aerial fitted to the car.

But more than races are recorded. Qualifying runs, practice laps, tests. F1 cars don't move under their own power without telemetry.

It isn't just 1 car, either. Most teams field several cars. They correlate the data from the multiple cars in the race with data from testing and simulations, as well as data from previous years at the same track.

Then they are distributing the data to a couple of dozen engineers, who are running the raw numbers through visualization tools and simulations to look for anomalies. When all is said and done I’d expect that each race would require terabytes of data – not a CERN LHC shot, but non-trivial – and there are multiple races.

Here's a print out of data from Monaco last year, from a detailed post on F1 telemetry and data analysis:


Teams even run simulations during races to predict expected lap times, which drivers are expected to meet.

Data as competitive advantage

Telemetry got started in the 1980s, which means that veteran teams have decades of data to build their simulations. Newer teams have much less data - and less detailed models.

Speed matters

The FIA limits the number of test days and wind tunnel time to help limit costs and level the playing field. Thus the telemetry - real time race data - is even more valuable, if you can quickly analyze and act on it.

Two-way telemetry - where engineers would make engine adjustments remotely during a race - was tried in the 90s, but finally banned. But imagine that technology applied to the morning commute during icy or wet conditions.

The Storage Bits take

As quantum mechanics suggests, we live in a statistical universe. More data gives us greater resolution, just as larger populations enable new market niches.

F1 racing telemetry suggests what the future holds for the larger automobile market: massive streams of real-time road and automobile data giving millions of automobiles - and maybe even their drivers - traffic smoothing, energy-optimizing analysis and direction.

F1 innovations not infrequently make their way to broader market. Wealthy crowded countries or cities could mandate vehicle telemetry to monitor and coordinate vehicles and traffic control operations.

Make moving, storing and processing the data cheap enough and it will happen. The only question is when.

Comments welcome, of course. A version of this post appeared in StorageMojo last week.