There is a scene in Moneyball, the story of how the Oakland A’s defied a tiny budget to come close to reaching the 2002 World Series, that neatly encapsulates the friction between gnarly, gum-chewing scouts and the newer wave of analysts who seek truths in spreadsheets.

“You don’t put a team together with a computer,” the A’s scouting director, Grady Fuson, scoffs at the general manager, Billy Beane, who has begun deep-mining data to find undervalued – and thus cheap – players. “Baseball isn’t just numbers. It isn’t science … there are intangibles that only baseball people understand.” Beane’s terse response? “Adapt or die.”

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Times have changed – a bit – since Michael Lewis wrote Moneyball but many in sport still prefer to trust their gut over any algorithm. Which is why a tweet last week from Thomas Bjørn, Europe’s 2018 Ryder Cup captain, was so unusual. After linking to a piece titled “How analytics helped reclaim the Ryder Cup”, written by Blake Wooster of the golf consultancy 15th Club, an enthusiastic Bjørn wrote “Stick to the plan!!! These guys played a vital role. Thanks for your hard work.”

Bjørn, it turned out, had embraced data and analytics as “a useful addition to his toolbox” shortly after being named captain in December 2016, when he asked 15th Club whether he should pick two, three or four wildcards. The answer? Four. Because the data showed wildcards tend to perform better than those who qualify in the last couple of automatic spots. And so began a relationship that culminated in Europe’s thumping 17½ – 10½ victory over USA in September.

Analytics also helped Bjørn answer tricky questions such as how important is experience versus form in the Ryder Cup, and which factors help determine success in foursomes and fourballs. They also reassured him that picking Sergio García as a wildcard made sense because the Spaniard’s underlying performance was better than his bare results implied.

15th Club’s influence continued in Versailles, with analysts suggesting the ideal fourballs and foursomes pairings for every player based on the format, their strengths, and the course layout – which included the strong recommendation Francesco Molinari and Tommy Fleetwood should play together. Crucially they also had enough of Bjørn’s ear to reassure him and his vice-captains to “stick to the plan”’ on the first morning when Europe were about to go 3-1 down and were considering last-minute changes to the afternoon foursomes.

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As Wooster relates: “This was a critical moment, and one where all those months spent establishing relationships and trust came to the fore. We knew the foursomes was a very different format and our statistical simulations gave us a high level of confidence the afternoon would be ours.” Bjørn listened and stuck to the plan. Europe won the session 4-0 and never looked back.

Such insight and influence is rare. Analytics in sport is increasingly mainstream – even Match of the Day shows expected goals – yet organisations guard even minor insights like diamonds. True, back in the day Sam Allardyce hailed his “fantastic four” metrics at Bolton, including the realisation that inswinging corners were much more successful than outswingers. Most teams, however, prefer to stay schtum.

Anyone who has read another Lewis book, The Undoing Project, will understand how hard it can be for outsiders to convince old pros to embrace new ideas. The first chapter outlines howthe Houston Rockets general manager, Daryl Morey, a man smart enough to build statistical models to predict performances of pro basketball players, led the Rockets to the third-best record of the 30 NBA teams in his decade in charge. Yet as Morey admitted to Lewis, “there’s an intense feeling among basketball people that I don’t belong – they remain silent during periods of success and pop up when they sense weakness”.

As Lewis relates, when the Rockets headed into the 2015 Western Conference finals, the former Olympic dream team player Charles Barkley dismissed Morey and analytics as “crap”, telling viewers: “All these guys who run these organisations who talk about analytics have one thing in common. They’re a bunch of guys who ain’t never played the game and they never got the girls in high school.”

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There are plenty of Barkleys out there. So how were 15th Club able to make such a difference? Much of it was down to Bjørn, who encouraged rigorous and open discussion and, despite being a golf professional for 25 years, was intrigued by fresh ideas. But Wooster’s team also understood that, having failed to make an impact when part of Team Europe at Hazeltine in 2016, they had to forge deeper friendships and better understand when to intervene. As he came to realise: “The strength of your models is really just one part of the jigsaw – it is as much about emotional intelligence as analytical expertise.”

This speaks to a wider point. The best teams know the choice between art and science is a false one. It is a combination of the two that works best, along with the mindset to be open to new ideas, whether they come from someone with 30 years in the trenches or a PhD in advanced algebra.

Incidentally this is something Beane has long recognised. Despite his differences with Fuson over analytics, he recognised the scout’s unique talents when he brought him back to Oakland to be his special assistant in 2010.