Football tacticians bowled over by quick-fix data risk being knocked for six

England won the second Test against South Africa comfortably enough, but there was a frustrating spell before tea on the first day as Kagiso Rabada and Anrich Nortje added 35 for the ninth wicket. Having bowled relatively full earlier in the day, England switched to a short-pitched attack to no great effect. Notably it was a full-pitched ball from Ollie Robinson after tea that delivered the breakthrough as Nortje was lbw.

So why had England changed approach? Perhaps they had been swayed by the Test against India at Lord’s when they had successfully bounced out the tail, or perhaps it was a reaction to the nature of this season’s Dukes cricket balls which have been losing menace more quickly than usual, demanding something different from the bowler. But there was also, seemingly, data that the South Africa tail was susceptible to short-pitched bowling. The problem is that if every ball is short-pitched, batters come to expect it and can set for it; far more dangerous is the surprise short-pitched ball.

As the CricViz analyst Ben Jones put it: “You can’t just look at dismissals” – the Jimmy Anderson inswinger is all the more dangerous for following a series of outswingers. CricViz’s expected wickets model shows that good balls tend to take wickets regardless, but Jones acknowledges that context matters and sees that was one of the areas in which the use of data in sport has to improve.

Or take the yorker, which nobody doubts is the most effective ball in one-day cricket. The problem is that there is a tiny margin for error: too full and it’s a low full-toss, too short and it’s a half-volley, both very hittable. A batter anticipating a yorker can advance or retreat to change the length.

As Tim Wigmore and Freddie Wilde