3 papers
stat.AP2026
Benchmarking Formula 1 results using a normal model
John Fry, Silvio Fanzon, Mark Austin +1
There is enduring interest in disentangling the effects of skill and luck in sport. A key issue in Formula 1 is distinguishing between car-level and driver-level effects. Four elit…
stat.AP2024
Elementary econometric and strategic analysis of curling matches
John Fry, Mark Austin, Silvio Fanzon
We develop a Markov model of curling matches, parametrised by the probability of winning an end and the probability distribution of scoring ends. In practical applications, these e…
stat.AP2023
Faster identification of faster Formula 1 drivers via time-rank duality
John Fry, Tom Brighton, Silvio Fanzon
Two natural ways of modelling Formula 1 race outcomes are a probabilistic approach, based on the exponential distribution, and econometric modelling of the ranks. Both approaches l…