Mathematical Predictions for 2021 F1 Season

With the 2021 season due to kick-off shortly, I though now would be a good time to use my mathematical model to predict how teammates will do in 2021. The prediction made is for what percentage of the team’s points each driver will score. To summarise how the model works, it compares every teammate match up in F1 since 1992 to give a score to each driver, I’ve then compared these scores for each 2021 teammate match up.

These predictions assume a similar car level to last year, as car competitiveness affects how close teammates end up. At the end of the year I’ll factor this back in and see how good the predictions were. I’ve also add in my own predictions with a brief explanation when I see a reason that the model might not fully represent reality.

Unfortunately, there are two teams that don’t get a comparison due to the fact that they feature rookies (Haas and Alpha Tauri). Regardless, let’s start at the top.

Mercedes: Hamilton vs Bottas

This partnership continues into its fifth year. Up until now Hamilton has scored between 54% and 62% of the points, so a prediction right in the middle of these two values seems pretty bang on. Bottas is not a bad driver by any means, as very few drivers in F1 history could consistently keep pace with Hamilton over the course of a season. I see no reason to adjust the model’s predictions here.

Red Bull: Verstappen vs Pérez

The model considers Perez to be an upgrade on Albon (who scored just 33% of Red Bull’s points last year), but not like that is likely to upset the general status quo. The model actually considers Verstappen-Perez to be about a close a pairing as Hamilton-Bottas. The larger percentage difference is due to the fact that the Red Bull was a worse car than the Mercedes last year.

McLaren: Ricciardo vs Norris

Ricciardo might not be quite on the level of Hamilton or Verstappen, but the model ranks him above the rest of the upper-midfield (Sainz, Perez etc.). Norris has shown himself to be competent, but his absolute peak level is not yet established. Given his average ranking should improve over time (as he is still inexperienced), I’ve predicted the gap will be closer than the model predicts.

My prediction:

Ricciardo 54%

Norris 46%

Aston Martin: Vettel vs Stroll

Vettel’s form is somewhat erratic year-to-year, but the model thinks that even his disappointing 2020 campaign was a cut above Stroll’s. If Vettel finds a more harmonious atmosphere at Aston Martin, there’s no reason he can’t be back to his best. Stroll, meanwhile, still needs to prove that he deserves a place on the grid, regardless of family relations.

Alpine: Alonso vs Ocon

Alonso’s reputation proceeds him, and the model sees this as the most one sided match up on the grid. Given Alonso is returning from a two year absence, and is now approaching 40, I’m less convinced that it will be such a whitewash.

My Prediction:

Alonso: 68%

Ocon: 32%

Ferrari: LeClerc vs Sainz

Given the gap between LeClerc and Vettel last year, the model is very complimentary of LeClerc right now. He’s now taken on the role of team leader and will be expected to perform. I’d expect Sainz to get a bit closer to LeClerc than the model predicts, due to the fact that Vettel was generally not on his A-game throughout the last couple of years.

My prediction:

LeClerc: 60%

Sainz: 40%

Alfa Romeo: Räikönnen vs Giovinazzi

The match-up so far has suggested an edge to Räikkönen, at least in terms of points scoring and place finishes. I’m sticking my neck out on this one and predicting it will swing the other way, due to a combination of Giovinazzi’s experience and Räikkönen’s age related decline.

My prediction:

Giovinazzi: 47%

Räkkönen: 53%

Williams: Latifi vs Russell

This one should be considered highly suspect, as it is based off a single pointless year. Russell demonstrated his speed in qualifying last year, but Latifi actually came out ahead based purely on race results with three 11th place finishes. Hopefully the Williams car will be able to score some points so that we can assess their relative abilities more accurately.

My prediction:

Latifi: 40%

Russell: 60%

And that’s a wrap. I’m looking forward to the end of the year where I can assess these predictions, including whether my adjustments were actually productive or not. It’ll also be great to see some data on the rookie drivers too (although 2 rookies at Haas will mean they still can’t be properly integrated into the model yet). Finally, I should have updated the model to incorporate age and experience effects by then, so I’ll be able to see if these updates improve the predictions or not.

5 thoughts on “Mathematical Predictions for 2021 F1 Season

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