At this point the model is up to speed with Formula One – everything up to the end of the 2018 season has been included in the input data. Any predictions it has now are just as much predictions for us. So what does the model suggest for the intra-team battles in 2019?

Williams

Right off the bat, this is a challenge for the model. The Williams pairing in 2019 consists of George Russell, a debutant, and Robert Kubica, who although confidently rated, has been out of F1 since 2010, having sustained life-threatening injuries in a rallying accident. How will Kubica’s time out and the physical (and perhaps mental) effects of his accident effect his abilities?

As discussed in the previous post, I have given a Russell a rating equivalent to Sergio Perez at the same age, based on his similar speed of progression through junior series, at a similar age, giving him a rating of 88.56. For Kubica, there is perhaps even more of a question mark over an appropriate ranking, so I have checked three possible values. The model’s prediction for a Kubica who had remained in F1, uninjured, is a rating of 107.25. To consider his possible reduction in abilities, I’ve also done comparisons assuming ratings of 97.25 and 87.25. The model suggests that even a severely affected Kubica should at least break even over the season with Russell – although we will still see Russell come out on top in some races even if Kubica is near his best.

Russell 32.14% 67.86% Kubica (unaffected)

Russell 42.11% 52.78% Kubica (moderately affected)

Russell 50.00% 50.00% Kubica (severely affected)

Sauber

This intra-team battle presents the intriguing prospect of a driver at the start of his F1 career, Antonio Giovinazzi, facing off against a real veteran, Kimi Raikkonen. Giovinazzi’s junior career suggested that he is about one year ahead of Stoffel Vandoorne in development, and on that basis I have given him an assumed rating of 86.89 for 2019. Interestingly, with the model seeing Raikkonen’s driving ability as now in a period of age-related decline, the prediction is for a close match, with the edge slightly going to Giovinazzi. I would certainly apply one caveat to this, which is that it will likely take the first few races for Giovinazzi to get into his stride, which will even things in Kimi’s favour.

Giovinazzi 52.78% 47.22% Raikkonen

Haas

Romain Grosjean and Kevin Magnussen are entering their third year as teammates, and their relative abilities should be modelled fairly well at this point, as both have had champion teammates at least once in their careers. In both their previous seasons together, Magnussen lead the head-to-head, and his margin increased in 2018 relative to 2017, as might be expected from a younger driver still building up experience. The model sees this trend continuing into 2019.

Grosjean 44.44% 55.56% Magnussen

Racing Point

Both Sergio Perez and Lance Stroll are now considered confidently rated by the model, although for Stroll this is entirely dependent on whether his performance against Massa in 2017 was really indicative of his ability at that age. Stroll has taken a fair amount of flak among followers of F1. While it is probably valid to say that he was the weakest driver on the grid in 2017, that’s hardly unexpected for a teenager in his debut season, moving straight up from Formula 3, in his fourth season racing cars. The question is how far he will develop, which last year’s match up against Sirotkin couldn’t cast any light on. The model suggests that Stroll could develop into a solid midfield driver, but that Perez’ greater experience at this stage of their respective careers will give him the advantage in 2019. This may be a boon to Perez, who despite coming out on top in the points battle over Ocon in 2018 was beaten 9-5 in the head-to-head.

Perez 58.82% 41.18% Stroll

The Red Bull driver cluster

I need to pause at this point to address the issue of the Red Bull-supported drivers, and their rankings relative to the rest of the field. While Sainz, Kvyat, Verstappen, Ricciardo, and Vergne have all raced against at least two of the others, their only connections to the rest of the field are Ricciardo’s single season against Vettel in 2014, and his partial season against Liuzzi in 2011. The fact that Ricciardo demolished Vettel 11-3 in 2014 has meant that with no other data to work from, the model assumes Ricciardo to be a much stronger talent than Vettel. By extension, Verstappen and Kvyat, who both have winning seasons against Ricciardo, must be even stronger, and their former teammate Sainz not far behind. When Gasly pairs up with Verstappen next year, his ranking will similarly be boosted by his connection to Ricciardo’s dominant season over Vettel.

When I say that the model overrates these drivers, don’t misunderstand me. I have no doubts that all of these drivers are talented, that Ricciardo is close to or among the top flight of drivers, or that Verstappen has the potential to be one of the all-time greats. But when the figures suggest that peak Verstappen would beat peak Senna in three races out of four, I think that the model needs more data to work from.

Last year’s pairing between Sainz and Hulkenberg has provided some valuable insight into where these drivers really rate. Adding this one season of data dropped the model’s estimate of Sainz’s career peak by twenty points. To look at how this additional data contributes to his overall rating, I checked Sainz’s score on the metric of ‘equivalent seasons with a champion teammate’ (SCT), which is part of how the model calculates confidence ratings. For each season with a teammate who won the championship at some point in their career, a driver scores one. For a season with a teammate who had another teammate that won the title, they score 0.5, and if there are two intervening connections, they score 0.25. This essentially illustrates how well-connected a driver is to the pool of world champions on which the rankings are based. Prior to his move to Renault, Sainz had scored 2.00 on this metric. His 2018 season has increased that to 5.75, so nearly three times more confident – but this still means that only two-thirds of the model’s over-inflation has been accounted for. On that basis, I have assumed that Sainz’s ranking at the end of 2017 was over-inflated by around 30 points.

The model incorporates the expectation that for each intervening teammate connection between a title winner and a particular driver, the margin for error increases. It seems reasonable to assume that the degree of over-inflation would be similarly affected. At the end of 2017, Verstappen and Kvyat had similar SCT scores of 2.00 and 2.50 respectively, so I have made a similar assumption for their ratings. Ricciardo, having been Vettel’s teammate, had a higher SCT of 5.50, so I have assumed that his ratings were over-inflated by a lower figure of 20 points.

These rating changes would indicate that Verstappen’s career peak would be among the greats, close to Schumacher, with Ricciardo closer to Nico Rosberg. Sainz and Kvyat would be good drivers in the next tier, similar in talent to Jenson Button.

In the affected team sections below, I have included the model’s actual current predictions, and what the predictions would look like if my assumptions on over-inflation are correct.

Mclaren

Next season’s partnership of Carlos Sainz and Lando Norris will be an interesting one. Sainz performed well against the mercurial Verstappen, but has since been let go from the Red Bull factory, and failed to make strides against Hulkenberg. Norris, on the other hand, has had his own talents called into question by his failure to win the F2 championship last year – a statement that demonstrates how hyped he has been in the last couple of seasons. As discussed in the previous post, I think that criticisms of his talent in 2018 are perhaps too sharp. Based on his rapid ascent of the junior series, I have assumed that Norris is marginally ahead of Russell in career peak ability, but slightly behind in 2019 once their respective ages are taken into account – Norris will still be 19 until the very end of next season, while Russell will turn 21 just before testing begins. The predicted results are for a balanced season, with Sainz having the edge but Norris pipping his teammate in a decent number of races. Like the other debutants, Norris may take a few races to find his feet, giving his more experienced teammate a headstart.

Sainz (current rating) 65.38% 34.62% Norris

Sainz (adjusted) 57.42% 42.86% Norris

Toro Rosso

2019 will see the return of Daniil Kvyat for a third – or is that a fourth – stint at Toro Rosso, alongside debutant Alexander Albon. As discussed in the previous post, Albon’s slow progress through the junior series means that I have given him an assumed rating for next year equal to that of Jolyon Palmer at the same age, of 83.42, the lowest of 2019’s new drivers, but not the lowest in the field. The model predicts a victory over the season for Kvyat, although a fairly close one if my estimates of over-inflation are accurate. This could be a key battle for both drivers, with Red Bull seemingly grooming Dan Ticktum for an F1 seat in 2020.

Kvyat (current rating) 85.71% 14.29% Albon

Kvyat (adjusted) 58.51% 41.49% Albon

Renault

Ricciardo’s move to Renault takes him away from an intra-team battle with Verstappen that probably wasn’t going to do either driver, or the team, any favours. The pairing with Hulkenberg is a mouth-watering prospect, to see two of the drivers touted as the most talented in the field go head-to-head as they move towards the peak of their abilities. On the flip side however, 2018’s results suggest that Renault are not going to be challenging for podiums in 2019, which could prove tiresome for both drivers. Allowing for over-inflation of Ricciardo’s current rating in the model, he should still lead Hulkenberg marginally in the head to head. If the model’s assumptions based on 2014 are correct, however, it will be a Ricciardo walkover.

Ricciardo (current rating) 77.78% 22.22% Hulkenberg

Ricciardo (adjusted) 60.00% 40.00% Hulkenberg

Red Bull

Next season will see former GP2, and near Superformula, champion Pierre Gasly go up against Formula One’s wonderkid, Max Verstappen. Despite entering only his second full season of Formula One, Gasly is still a year older than Verstappen, for whom it will be a fifth season. Gasly’s debut season against Hartley didn’t connect him to the rest of the field, but as Hartley’s success in endurance racing didn’t seem to translate to open-wheel cars, it is likely that neither driver was among the best in the field. Gasly’s junior career progress has led me to give him the same estimated ability as Albon this season, with both drivers turning 23 at the start of the coming season. Allowing for the over-inflation of the Red Bull drivers, I’m still expecting Verstappen to dominate Gasly over the season, with a small number of races going in Gasly’s favour.

Verstappen (current rating) 93.75% 6.25% Gasly

Verstappen (adjusted) 66.67% 33.33% Gasly

Ferrari

In a step away from their traditional approach of relying on tried-and-tested drivers, Ferrari have promoted Charles Leclerc to a first-team seat for 2019 in only his second year in Formula One, alongside Sebastian Vettel. Last year saw Vettel matched head to head by the now ageing Kimi Raikkonen, and the F1 community has been rife with speculation over whether this means that Leclerc will outshine the four-time champion from the get-go. As exciting a story as this would make, the model disagrees. Vettel’s formbook shows that he has been noticeably more erratic in his career than other highly-rated drivers like Hamilton and Alonso, with alternating peaks and troughs. For Vettel, these have been almost annual, with 2014, 2016, and 2018 being his weaker seasons, compared to 2013, 2015, and 2017. The model smoothes out these variations. As discussed in the previous post, Leclerc’s rating has been assumed from his junior career showing a similar curve to Vandoorne’s and Hulkenberg’s, but three years earlier at each step. Allowing for his age next year, that gives him a rating of 86.59, slightly lower than the older Giovinazzi and Russell, but ahead of Norris and Albon. This is higher than Raikkonen’s rating this year, suggesting that Ferrari have timed the changeover well. The model suggests that Vettel will beat Leclerc in 2 out of every 3 races. Given Vettel’s tendency to peak in alternating years, the dominance may be slightly stronger. There may be additional pressure on Leclerc at Ferrari, but on the other hand, he will be back in the position he became accustomed to in his junior days, at the front of the field.

Vettel 65.38% 34.62% Leclerc.

Mercedes

After a promising start in 2017, last year Valtteri Bottas was comprehensively trounced by Lewis Hamilton in what was probably one of his strongest seasons. The model has revised Hamilton upwards and Bottas downwards as a result, although it still expects Bottas to do better this year. As a result, while Hamilton should lead the intra-team battle, the dominance is not as great as at Ferrari. Interestingly, the model thinks Hamilton’s chances would reduce to 58.51% against Ocon. Assuming that Mercedes don’t lose faith in Ocon as a reserve driver, Bottas will need to get a step closer to Hamilton to keep his seat in 2019.

Hamilton 61.54% 38.46% Bottas