Category Mathematical models

2018 f1metrics end of season report

2018 proved a wonder of a season, with two close to evenly matched cars dicing for the drivers’ and constructors’ titles across most of the season; a rare delight in Formula 1. Mercedes took the spoils for the fifth season on the trot, but that achievement was as much attributable to driver as team — […]

Historical hypotheticals: Part II (Kubica, Clark, Donohue, Revson)

Welcome to the second part of this five-part series, in which I apply the f1metrics model of driver and team performance to simulating historical hypothetical situations. Consider this a quantitative approach to tackling some popular but difficult to resolve talking points in Formula 1 history. The point of this series is not to be taken […]

Historical hypotheticals: Part I (Senna, Pryce, Brise)

What if Ayrton Senna had survived the crash at Imola 1994? What if Robert Kubica had never entered that fateful rally? The history of Formula 1 is sadly abundant with drivers cut down at or before their peak. In this five-part series, I will apply the f1metrics model of driver and team performance to simulating […]

2018 preseason analysis

With the wraps off the new halo-adorned cars, we launch into 2018. There are several major sources of intrigue at the dawn of the season. Can Renault, with three top-budget teams now in their ranks, take the fight to the Mercedes or Ferrari works teams? By what margin can 2018 cars exceed the already record-breaking […]

2017 f1metrics end of season report

The 2017 Formula 1 season will be long remembered and debated. Could Vettel have stayed in championship contention with better reliability or fewer driver errors in the critical stages, or was the Mercedes advantage too much for Vettel or any driver to bridge? Is this a step on the road to recovery for Ferrari, or […]

2017 Preseason analysis

2017 marks one of the largest changes in the history of Formula 1. Not since 1966, when engine sizes were doubled, have the sport’s rule-makers introduced full-format changes with the primary intent of making the cars faster and more exciting. Instead, we have become accustomed to changes designed to curb speeds and improve safety, which […]

2016 model-based driver rankings

A key question at the end of every Formula 1 season is: who was the best performing driver? There’s never a straightforward answer to this question, and usually only two or three teams could realistically win the drivers’ title, regardless of the quality of their drivers. This year, it was probably just one team, such was the […]

Experts versus models: How do we rank drivers?

Who was a greater Formula 1 driver: Nigel Mansell or Elio de Angelis? Expert panels have uniformly selected Mansell. Raw statistics of success — wins, championships, and the like — also clearly favor Mansell. Yet, every mathematical model of driver rankings developed to date resoundingly answers de Angelis. Examining the data table below helps to […]

2015 model-based driver rankings

Last year, I presented model-based rankings for all the 2014 season drivers. These rankings are derived from a mathematical model, described here, that statistically estimates the strength of driver and team performances in each year, as well as overall career performances for drivers. It achieves this by finding the best fit to all race result […]

The most dominant teams in F1 history

Recent years in Formula 1 have been challenging for viewers, with Red Bull dominance in 2011 and 2013, followed by Mercedes dominance in 2014 and 2015. Periods of team dominance are not new to Formula 1, since differences in car performance have always trumped differences in driver performance. Nevertheless, the level of dominance achieved by Mercedes […]