Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Determining the best track performances of all time using a conceptual population model for athletics records
AU - Stephenson, Alec
AU - Tawn, Jonathan Angus
PY - 2013/3
Y1 - 2013/3
N2 - What is the best male and female athletics performance in history? We seek to answer this question for Olympic distance track events by simultaneously modelling race performances over all Olympic distances and all times. Our model uses techniques from a branch of statistics called extreme value theory, and incorporates information on improvements over time using an exponential trend in addition to a process which identifies the changing ability of the population of athletes across all distances. We conclude that the best male performance of all time is the 1968 world record of Lee Evans in the 400 m, and that the best female performance of all time is the current 1988 world record of Florence Griffith-Joyner in the 100 m. More generally, our approach provides a basis for deriving a ranking of track athletes over any distance and at any point over the last 100 years.
AB - What is the best male and female athletics performance in history? We seek to answer this question for Olympic distance track events by simultaneously modelling race performances over all Olympic distances and all times. Our model uses techniques from a branch of statistics called extreme value theory, and incorporates information on improvements over time using an exponential trend in addition to a process which identifies the changing ability of the population of athletes across all distances. We conclude that the best male performance of all time is the 1968 world record of Lee Evans in the 400 m, and that the best female performance of all time is the current 1988 world record of Florence Griffith-Joyner in the 100 m. More generally, our approach provides a basis for deriving a ranking of track athletes over any distance and at any point over the last 100 years.
KW - athletics
KW - Bayesian inference
KW - extreme value distribution
KW - extreme value theory
U2 - 10.1515/jqas-2012-0047
DO - 10.1515/jqas-2012-0047
M3 - Journal article
VL - 9
SP - 67
EP - 76
JO - Journal of Quantitative Analysis in Sports
JF - Journal of Quantitative Analysis in Sports
SN - 1559-0410
IS - 1
ER -