How data analytics helped Lewis Hamilton win the Formula One drivers' championship

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Data helps Lewis Hamilton know when is best to overtake

Source:  Mercedes-AMG Petronas Motorsport

Data analytics can also help in real time during a Formula One race. The Mercedes-AMG Petronas Motorsport team can model and predict elements of the race, including when and how to attempt to overtake a car in front.

Tibco has created a model that analyses data to come up with a probability for various different overtaking manoeuvres. The algorithm uses a range of data such as race conditions, tyres, track, fuel, the car’s position on the track, the history of previous races at that venue, details of the car and driver that Lewis Hamilton or Valtteri Bottas hope to overtake, and the specific situation they find themselves facing.

Using that modelling, the team can advise the driver when and how to overtake to give the best chance of successfully getting past the other car.

Tibco’s chief analytics officer Michael O’Connell cites an example from the Beijing Grand Prix, where Hamilton was told that if he took a particular corner wider than normal, it would improve his chances of overtaking in the subsequent section of the circuit.

“We looked at the way Lewis makes an overtake, and he’s an aggressive driver,” says O’Connell.

He says that Hamilton approaches corners differently from other drivers, and is able to complete overtakes where other drivers would be less likely to succeed.

“Not everybody can capitalise on a probability of [for example] 0.9 and deliver an overtake, but Lewis can,” says O’Connell.

(Picture above shows Hamilton overtaking a Red Bull rival during the Canadian Grand Prix)

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