Chinese GP 2019 ?>

Chinese GP 2019

Whether the next race marks the 1000th Formula 1 Grand Prix is debatable, but we definitely know that it will be an exciting race to watch! Charles Leclerc lost the win in Bahrain due to a faulty engine component but he – and we – hope that he gets his revenge and takes the win this time. He seems to have the edge over teammate Vettel and if his Ferrari holds strong, rest assured he will do his utmost to get on the top step of the F1 podium for the first time.

After two consecutive one-twos for the Mercedes drivers, the model shows them as favourites. However, I think that Ferrari will be particularly strong but it will still be a very close battle. Red Bull and Verstappen will surely be in the the game. I’m also really looking forward to seeing what Lando Norris can do in his 3rd F1 race after being super impressive in the first two races.

Driver Qualifying Prediction Actual Qualifying Result Race Prediction Actual Race Result
Hamilton 1 2 1 1
Bottas 2 1 2 2
Vettel 3 3 3 3
Verstappen 6 5 5 4
Leclerc 4 4 4 5
Gasly 10 6 6 6
Ricciardo 15 7 8 7
Perez 8 12 11 8
Raikkonen 5 13 7 9
Albon 16 19 18 10
Grosjean 9 10 12 11
Stroll 18 16 15 12
Magnussen 7 9 10 13
Sainz 13 14 14 14
Giovinazzi 12 20 16 15
Russell 20 17 19 16
Kubica 19 18 20 17
Norris 11 15 17 18
Kvyat 17 11 13 R
Hulkenberg 14 8 9 R
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4 thoughts on “Chinese GP 2019

  1. Hi Asterios, how we can introduce in the model the event of the TEAM ORDERS, the could affects the final result of the race but are inexistent in the Qualy and practices. Like today Vettel Lecrec moment.

    1. Hi Ricardo, I think that incorporating team orders in the model is very hard, possibly even impossible.

      There are two main difficulties. First, where can we find all the historical team orders and encode them in a way that allows the model to understand their impact on he final result. Second, even if you have the historical data, how will you use it in the race predictions? You cannot know the team orders of the coming race.

      Any thoughts?

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