After a weekend of nail-biting sports finals, in which England won the Cricket World Cup and Novak Jokavic beat Roger Federer in SW19, for the boffins it was a case of “close but no cigar”, showing that – in some cases at least – artificial intelligence and machine learning are not quiet there yet.
And, with the business world and his wife planning to embrace AI, this weekend’s results should serve as a valuable lesson that the latest technology alone is not as accurate as some would have you believe.
Ten days ago, Decision Marketing reported on how a predictive model, built by Alteryx using over 100 years of historic match data, had forecast that eight-time Wimbledon champion Federer would emerge triumphant.
Admittedly, the model did correctly predict the final would be between “Rog” and “Nole” but suffered a double-fault when it came to the result after Jokavic retained his title with a 7-6 (7-5) 1-6 7-6 (7-4) 4-6 13-12 (7-3) win over the 37-year-old Swiss national.
Meanwhile, a separate project – carried out by data scientist KNV Ashok on GitHub – attempted to predict the result of the Cricket World Cup 2019 using AI and machine learning.
This model was based on the historical data collected for the ten participating teams, with Ashok – under the name of “Turing551”- saying: “I believe this predictive analysis strategy would be useful for viewers, sponsors and team strategists.”
Based on the data collected from 1975-2015 World Cups, the model forecast that the final would be between India and England, with India easing to victory.
However, as anyone who spent yesterday watching the nine-hour marathon game will tell you, this forecast was also stumped with England edging a “super over” by the tightest of margins to see off New Zealand at the Lord’s final.
And, while these two examples might show data science is not an exact science, Marketing Metrix would no doubt beg to differ. In 2016 and 2017, the data analytics firm predicted the Great British Bake-Off champion, two years on the trot.
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