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Reading: A Prediction for the Olympic Men’s 100m Sprint
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SmartData Collective > Analytics > Predictive Analytics > A Prediction for the Olympic Men’s 100m Sprint
Predictive AnalyticsR Programming Language

A Prediction for the Olympic Men’s 100m Sprint

DavidMSmith
DavidMSmith
1 Min Read
A Prediction for the Olympic Men's 100m Sprint
Illustrative image generated with OpenAI gpt-image-1.
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R user Markus Gesmann used the gold-winning times from the Olympic Men’s 100m sprint since 1990 as the basis of the following prediction for the London Games:

R user Markus Gesmann used the gold-winning times from the Olympic Men’s 100m sprint since 1990 as the basis of the following prediction for the London Games:

100mFinal
My simple log-linear model forecasts a winning time of 9.68 seconds, which is 1/100 of a second faster than Usain Bolt’s winning time in Beijing in 2008, but still 1/10 of a second slower than his 2009 World Record (9.58s) in Berlin.

Markus used the readHTMLtable to scrape the data from the web into R, and the lm function to fit a regression model and make the prediction (the red line above). (The R code is provided at Markus’s blog.) He admits the model is overly simplistic: it doesn’t use data from non-Olympic competitions, and a model like this implies that 100m sprint times will skrink indefinitely. But you can see how well this prediction pans out this Saturday, in the men’s 100m final.

Images’ blog: London Olympics and a prediction for the 100m final

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