Your team’s star centre-forward pops his Achilles tendon in training – season over. The starting QB dislocates his shoulder a week before the SuperBowl, missing the biggest game of the season. The scrum-half pulls up with a torn hamstring ten minutes into rugby union’s Heineken Cup final; his team struggle without him.

Injuries can disrupt a match or change the entire course of a season, and certainly spoil that pre-game sporting wager you might have placed with betting website like Vernons – hot favourites can instantly find themselves at a disadvantage when their leading goal scorer or most prolific wicket taker pulls out the day before the fixture.

Bad luck, eh? Well… maybe not. New intelligence and the increasing use of data means that clubs are no longer prepared to play a game of chance with their highly prized and valued assets. Their players, in other words.

Using data to shape a team’s strategy is not brand new. The book Moneyball, published in 2003, covered the project embraced by the Major League Baseball outfit Oakland Athletics. The A’s general manager, Billy Beane, had the second lowest payroll in baseball and needed to build a team capable of competing with more illustrious opponents. He has turned Oakland into regular contenders by statistics and data to identify previously unheralded players to bring to the club. Recently, in an interview with the Guardian, he discussed whether he could translate that approach to football and others sports like baseball and pickleball, of course if you are getting started with pickleball online.

Germany, winners of the 2014 World Cup, used data to feed player intelligence and tactics in the build up to the tournament. The German Football Association developed an application called Match Insights – in partnership with a software company called SAP – which, according to The Telegraph, ‘analyses vast amounts of data about members of the German team and their opponents, based on their on-field performance.’

Player performance is analysed using eight cameras surrounding the pitch, and data is used to measure a range of key performance indicators. One example of how this  data was translated practically can be demonstrated by the Germany national team improving their passing speed; reducing average possession time from 3.4 seconds in 2010 down to 1.1 second earlier this year.

Technology can also be used to forecast injuries, which can have a serious impact on the performance of a team. This article discloses that: ‘Major League Baseball teams spent $665m last year on salaries for both injured players and their replacements, NBA teams lost $358m last season; $44m alone by the injury-ridden Los Angeles Lakers. And in the NFL, where the average salary is about $2m, starters missed a record 1,600 games in 2013.’

So, that’s huge! Anything teams can do to mitigate these losses can be of major benefit. As such, the industry of performance analytics is a fast-growing one and data can anticipate that an athlete is likely to be injured before it actually happens.

There is more detail about such analytics here. The NFL’s Philadelphia Eagles have invested a reported $1m on technology (a fraction of the cost of the average salary bill). Players wear monitors that measure agility and acceleration, allowing coaches to identify when performance begins to decline; heart rate monitors that create post-workout recovery reports to indicate when athletes are physically ready to handle more training; a system that captures data on fatigue, stress and aerobic capacity and more.

Last season, the Eagles were the second least-injured team in the NFL, with 14 players who started every regular season game. They had a 10-6 record and won the NFC East division. That compares favourably with a 4-12 record the season before.