The increasing importance of data analytics has been seen in the transfers of Raheem Sterling and Dimitri Payet, the Web Summit heard yesterday.
Roy Campbell of West Ham United explained how data helped the club take on French international Payet.
“He was signed because everybody agreed on the things that made him a good signing and data analytics was one of those things,” Campbell said.
“The quality of the work being done in and outside the game has improved, but there is still a major challenge in how that’s used internally to make decisions.
“Part of that is moving away from the analysts being just an additional voice in the room, which it is now, whether that’s in filtering out players for scouts to look at or error-checking at the end of transfers.
“But to maximise data it has to be strategic and be aligned with the club’s defined strategies.
“Liverpool signing Sadio Mane is a sign of that — they have a very sophisticated data team and they identified him as a player who fit what they needed.
“All our metrics (at West Ham) are based on taking every single action on a pitch increasing or decreasing your chance of scoring.
“It’s weighted on where it happens, how close to the goal, whether opponents are near and so on. Dimitri Payet came out very high on those scores.
“The manager liked him anyway, it wasn’t a hard sell, but you often have to show the manager that convincing piece of information — I showed the stats on the top 10 players who could use through balls, which was important to how the manager wanted to play, and Payet was on it. It was an easy sell.
“How you communicate the data, as I say, can be the biggest challenge.”
Lawyer Ian Lynam of Charles Russell Speechlys, who works extensively in sport, outlined the advantages of data in player negotiations.
“The most obvious way is identifying the player — clubs use data to identify a good player but it’s wider than that.
“The first stage is for the club to identify what it needs, and data can help with that and with finding the group of players that may suit that.
“Data also helps in terms of what the fee and salary should be for that player, and with contract structure — how it should balance risk/reward and incentivise the player.
“Finally, it can be used in negotiations for a contract — if you represent a player and a club is using data to evaluate him, then you use data to negotiate on a level playing field.
“Raheem Sterling’s move a year and a half ago — there were two negotiations. There was a negotiation with Liverpool and when Liverpool decided do sell, there was a negotiation with Man City.
“They’re two of the more sophisticated clubs around, they have data teams, so to negotiate you want to meet them on that level playing field by using data if you’re a player.”
Blake Wooster of the 21st Club pointed out that American club owners have improved the standing of data analytics in English football.
“There’s a big range of work going on — it often depends on the structure at a club. We work with US investors who’ve invested in UK clubs.
“Historically, an investor would look at legal and financial implications but now, more commonly, they see the playing squad as central.
“The new owners of Crystal Palace are former Goldman Sachs partners, they’re involved in US sports franchises, so they really understand about valued/overvalued assets and the use of data in getting value.
“But a club can have the best analyst in the world, but if he or she isn’t listened to or isn’t influencing the club, it’s no good.
“Bill James’ breakthrough came when the baseball club owner or GM understood what he did and gave him an influence on how the club was run.
“It’s the same in football — it’s the owners and chairmen who understand this who realise data analytics is used to benefit the club.”
Campbell concurred: “It’s up to analytics people to add value. The presumption is that it’s binary, you do it or you don’t, but that’s wrong.
“People in data analytics have to convince the manager. It’s risk management.
“The assets are young players, often moving from a different country on a transfer, and you have imperfect information.
“But if analytics can take a 60% success rate with transfers to 70%, then that’s how it needs to convey itself.”
Lynam added that US sports, contrary to general belief, are not necessarily miles ahead of their European counterparts.
“When I started to visit North American clubs, we saw baseball and basketball as miles ahead in data analytics.
“But in other areas they’re miles behind — in sports science. Evaluating injury prevention, conditioning, sleep, all of that — they were 10 years behind football.
“They’re only getting there now in some areas.”
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