Maths professor David Spiegelhalter from the University of Cambridge has a track record of predicting unlikely victors in the world’s most famous steeplechase. He correctly selected Mon Mome in 2009, and also successfully predicted the winners Neptune Collonges in 2012 and Aurora’s Encore in 2013.
This year, Spiegelhalter is picking the 66-1 shot Milan Native to triumph in the race. The horse is trained by Irishman Gordon Elliott, who has previously won the race with Tiger Roll in 2018 and 2019.
Spiegelhalter’s prediction is based on a statistical analysis of previous winners, which takes into account factors such as age, weight and form. He has developed an algorithm that uses this data to identify potential winners, with a particular focus on horses that have been overlooked by bookmakers and punters.
Despite his impressive track record, Spiegelhalter acknowledges that picking the winner of the Grand National is notoriously difficult. With 40 runners competing over a distance of four miles and two furlongs, the race is a gruelling test of stamina and jumping ability.
Nevertheless, he believes that his mathematical approach can help to tip the odds in favour of long shots like Milan Native. Regardless of whether his prediction proves correct, Spiegelhalter’s insights are a reminder of the value of data and analytics in predicting sporting outcomes. As more and more data becomes available in the world of sport, it is likely that we will see a continued rise in the use of maths and statistics to gain an edge over the competition.