Artificial intelligence can drive a car, curate the films and documentaries that you watch, develop chess programmes capable of beating grandmasters and use your face to access your phone. And, one company claims, it can also predict when footballers are about to suffer an injury.
Off the field, football has gone through a huge transformation in the 21st century, with the emergence of GPS-driven player performance data in the early 2000s, followed in the 2010s by the advanced analytics that now form a major part of every top club’s player recruitment strategy. Just last month, Manchester City announced the appointment of Laurie Shaw to a new post of lead AI scientist at the Etihad Stadium, taking him from his role as research scientist and lecturer at Harvard University.
Football has always searched out innovations to make small, but crucial, differences. Many have become staples of the game, including TechnoGym to improve biomechanics, IntelliGym to improve cognitive processing and cryogenic gym sessions to ease the strain on muscles. Others have fallen by the wayside. Anyone remember nasal strips or the ball-bending properties of Predator boots?
The use of AI to predict when players are on the brink of suffering an injury could prove to be the next game-changing innovation that becomes a key component at the elite end of the game.
In a game dominated by clubs wanting to discover the extra 1% in marginal gains, keeping a player fit is arguably the most important challenge facing any coach. A depleted squad can lead to negative results and, if a team suffers too many, the manager or coach is generally the one who pays the price. This season has been more challenging than most, with the COVID-19 pandemic leading to fixtures being crammed into a reduced time frame, and players being forced to play 2-3 games a week on a regular basis.
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The toll on players’ fitness is borne out by the injury lists. Crystal Palace and Southampton fulfilled their midweek Premier League fixtures with 10 first-team squad members sidelined. Champions Liverpool lost to Brighton on Wednesday with eight absentees, including long-term injury victims Virgil van Dijk, Joe Gomez and Joel Matip. Research by premierinjuries.com shows that up to and including match-week 21 of the Premier League this season, there has been a five percent increase in time lost to injuries this season. At the same stage last season, there were 356 “time-loss absences” (a player missing at least one league game), but the number has jumped to 374 this time around. With COVID-related absences, the number is 435.
Liverpool had suffered 14 time-loss absences at this stage of last season, but they’re now up to 29 in 2020-21. Their league position — fourth place, seven points adrift of top spot — suggests they are paying a price for their sharp increase in players lost to injury.
Liverpool’s title defense is struggling thanks to their increase in injuries, with Joel Matip joining Virgil van Dijk and Joe Gomez on the sidelines for the foreseeable future. Clive Brunskill/Getty Images
But finding reliable injury prevention technology is the holy grail of sports scientists and fitness coaches. By November, ESPN reported a 16% rise in muscle injuries in the Premier League compared to the same stage last season. So can AI successfully predict when players are about to be injured?
Since the start of the 2017-18 season, La Liga side Getafe have partnered with the California-based AI company Zone7 to break down performance data and predict when players are at risk of injury. In simple terms, clubs like Getafe in Spain, Scottish Premiership leaders Rangers and MLS sides Real Salt Lake and Toronto FC send their training and match data to Zone7, who analyze it using their algorithm and send back daily emails with information about players who may be straying close to the so-called “danger zone.”
Between the start of the 2017-18 season and March 2020, when La Liga was suspended due to the COVID-19 pandemic, Getafe recorded a substantial reduction in injuries.
“Three seasons ago, during the first year with Zone7, we saw a reduction of 40% in injury volume,” Javier Vidal, the Getafe’s Head of Performance, said. “As the Zone7 engine became more reliable and we had access to more data in the second year, we saw a reduction of 66 percent in the volume of injuries.
“This means that of every three injuries we had two seasons ago, we now have only one.”
Getafe have been using the technology for four seasons and seen an impressive reduction in injuries due to the enhanced analysis over their players’ fitness. David S. Bustamante/Soccrates/Getty Images
Jordi Cruyff, the former Barcelona and Manchester United midfielder, told ESPN that he has become a “minor, minor investor” in Zone7 after trialling the AI tool during his time as sporting director at Maccabi Tel Aviv in 2017. But he admits that he was only convinced by the AI technology after monitoring the data, even though Maccabi’s then-coach declined to use it.
“I presented the tool to our then-coach and he wasn’t too interested.” Cruyff told ESPN. “So for the four to five months the coach was in charge, he would follow his own plan, but we would still give our performance data to the company, which they would run through their algorithm. I would then receive an email before training each day with which players were at risk and it actually predicted five of seven injuries.
“I thought ‘wow.’ Once or twice could be a coincidence, but catching five out of seven muscular injuries is a different thing. I would wait until after training to be told if a player had been injured. I would then go back to look at my email and there was the name. We were lucky in some ways that the coach wasn’t interested in it because it gave us the chance to test it.
“It was the perfect test, although I wish the coach would have listened, because then we would have avoided some injuries.”
Tal Brown, who founded Zone7 with Eyal Eliakim in 2017 having worked together in the Israeli Defense Forces Intelligence Corps, spoke to ESPN to explain how AI can be used to detect injury risk.
“Every single player is now using a GPS vest, they are being tested for strength and flexibility at their clubs, many teams distribute watches to their players to measure sleep, so the reality is that somebody working for a club needs to look at two dozen dashboards every day — multiplied by 20 players, multiplied by six days a week,” Brown said via Zoom. “It is becoming a puzzle that a human brain wasn’t really meant to solve.
“We can use a chess metaphor. Chess programmes used to be pretty simplistic and the experts could beat them, but today, a Google chess programme is unbeatable. It’s not because Google has taught that chess programme 10,000 equations manually, it is because the programme has automatically studied every recorded chess game played in the history of mankind and, using AI, has developed its own understanding and interpretation.
“We are not there yet as a company. We don’t have access to every single football injury that ever occurred, but we are getting much better and there will be a point where a programme focused on injury risk will out-perform humans in interpreting data.”
More than 50 clubs across the world now use Zone7’s AI programme. Many wish to remain anonymous, in an effort to protect any competitive advantage that the tool may provide — football clubs are notoriously protective of such proprietary data — while others simply do not wish to discuss any pros or cons they have discovered while using it. Despite repeated attempts by ESPN to speak to Real Salt Lake and Toronto, neither MLS team responded to enquiries.
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Rangers, 23 points clear at the top of the Scottish Premiership and on course for a first domestic title since 2011, adopted Zone7’s AI tool last summer and, while keen to make a broader assessment after a full season of use, they believe it’s been a valuable addition to their injury prevention strategy.
“I believe AI, coupled with the experience levels of those using it, will eventually become a bedrock within clubs’ decision-making as data and technology advances,” Jordan Milsom, Rangers’ head of performance told ESPN. “Given our players had been exposed to one of the longest lockdowns of all [93 days] and the unknowns associated with such prolonged layoffs, we felt investing in such a system may well provide another layer of support for how we managed the players on what would clearly be a challenging season.
“We haven’t used the system long enough compare season-to-season analysis, and it’s important to understand we are a department that is data-informed and not data-driven. But it is my opinion that if such systems are used in this way, it can have many positive benefits.”
Rangers are dominating the Scottish Premiership this season and have been encouraged by the early returns of Zone7 when used in conjunction with other existing sports science tools within the club. Alan Harvey/SNS Group via Getty Images
Rangers manager Steven Gerrard has praised the club’s fitness and sports science department, saying in December that the team were enabling his players to “hit top numbers,” and Milson says that the AI data is helping to inform player rotation, even to the extent of highlighting which players should be substituted during games.
“All of our GPS and heart rate training load data from sessions and games is uploaded automatically into the Zone7 system,” Milsom said. “The platform digests this, performs its modelling and provides us with risk alerts each day for players.
“Generally, there would be 1-2 players who may be flagged [for further monitoring]. Sometimes, these flags relate to overload — other times it’s under-load. This allows us to have a deeper dive into why specifically they are at risk. This information will feed into our general staff discussions to determine if any further areas support this information. As we typically compete every 3-4 days, if risk is associated with overload, I can often use that information to help support in-game substitutions as a means of maximising player availability, whilst potentially reducing risk through reduced minutes if and when possible.”
The key to the success of the AI tool is the amount of data Zone7 are able to upload and analyse. While Brown stresses that “nobody ever sees your data. We don’t own it and we’re not allowed to retain a copy of it, post-relationship, so it’s very strict,” the volume of information provided by each client club is used to create a huge database that then enables the programme to predict injury risk.
“We can use 200 million hours of football data because we are working with 50-60 clients,” Brown said. “As a result, we have 50-60 times more data than a typical team has, so the data set is very large. But what is important is that it’s not just the injury in the sense of the date it occurred and what happened, it is every single day of training and games and medical data leading to the injury, going back as much as a year prior.
“That amount of information gives us the ability to look at the daily data leading to an incident and, using AI and deep learning, to find patterns that repeat themselves before hamstring injuries or groin injuries or knee injuries happen. That’s how it works.
“If you are trying to forecast an event, which is an injury, you need to have a big database of incidents. A typical team would have something like 30-40 incidents a year for a squad, so multiply that by several years of historical data.”
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ESPN has spoken to people in sports science who believe that AI is a positive innovation if used alongside existing methods. “Their results are impressive,” said one sports scientist, who has worked with several Premier League clubs in the past and spoke on condition of not being named. “The issue is the level of individualisation with injury results is high, so lots of variant data only gives you a small answer. Therefore, it definitely has to be a blended approach.”
Zone7’s AI tool is not restricted to sports. In tandem with Garmin wearable devices and Zone7, medical staff in Israel are having their health and well-being monitored during the COVID-19 pandemic and there is a similar project with a major hospital in New York City. There are also projects ongoing with military and special forces. In football, however, Getafe are the best example of AI being used successfully to improve the fitness record of a team, as explained by head of performance Vidal.
“It would take 200 people all day to analyse the data, but with this, I get the recommendations within minutes.” Vidal said. “We use our own high-quality ultrasound to clinically to evaluate players that show predefined risk indications. After starting to use Zone7, some players would report feeling fine despite the engine identifying immediate risk for them.
“In many cases, our ultrasound tests confirmed muscular damage, allowing us to address this before the injury occurred. These players could have sustained injury but for the AI detection.”
Cruyff, now coaching in China with Shenzhen FC, believes AI can become a key component for teams, but he makes clear that AI alone cannot be regarded as the silver bullet to prevent all injuries.
“It’s not a deciding tool,” he said. “You can see a risk of injury and decide to take the risk or not. It’s part of the modernisation of sport. You have so many things — video analysts, GPS tracking devices — and I think this is a part that maybe we missed, but it is coming, little by little.”