How are sports teams using analytics to drive performance on the field?
We recently looked at how sports clubs and venues are driving more profitable business activities off the field, but what about how sports teams and athletes are using analytics to better their performance?
It really is eye-opening when you start looking into the multitude of ways in which sports clubs are starting to build analytics into their training sessions and matches. One thing is for certain: analytics in sports is becoming so ingrained in day to day activities that its presence can only increase. We are even seeing analytics coming through to the consumer level with Fitbit type trackers which are driving training behaviour through the delivery of analytics to our smart phone.
So just how are sports clubs employing analytics for better results?
Separate the best from the rest
Clubs are now utilising algorithms to not only help decide which players to purchase in the first place, but on which players to send onto the pitch based on a wide range of factors.
Historically, decisions about players may have been down to the coach and manager’s personal knowledge about an individual player’s strengths and weaknesses versus a particular opposing team. However, as more data becomes available, more factors are tipping decisions in one direction or another.
Details such as player performance based on weather or pitch conditions are now starting to be taken into consideration.
Biometric data at a player level
UK football clubs are starting to invest in wearable technology, where sensors are placed in clothing to monitor field position and biotmetric data such as heart rate, hydration and distance covered during a match in order to deliver more holistic analytics.
Without this data, information about where a player spent most of his time on the field during a match would be purely anecdotal whereas now coaches can get real-time data about player positions in order to make decisions on the fly.
If the data is not collected in the first place, then it cannot be analysed and measured in order to spot important trends. Without collecting the data and placing it alongside other data streams, how can a coach see what impact factors such as hydration levels or stadium capacity have on player performance?
It is now common for stadiums to have upwards of 8 cameras installed around the arena, whose core focus is on capturing information about the game – by analysing player performance during the pitch, locations, movements and general developments. This is a huge amount of information to dissect (8 cameras recording over circa 3 hours of footage each) which means that having analytics is critical for getting a high level view of key events during the match.
Accuracy in umpire decisions
Analytics is playing a big part in helping umpires to be more accurate in their decisions, or at least to have a degree of data to back up their (sometimes controversial) rulings.
In tennis in the UK, we regularly see Hawkeye being employed to provide not only umpire decision clarifications but also analytics about player shot success rates.
Making sports safer
Clubs are now turning to analytics to make sporting events safer for their athletes, by tracking hydration levels, alongside trend analysis for injuries to predict when players should be brought off the pitch to best reduce the risk of injury.
Additionally, in sports such as rugby where there is a lot of physical contact, sensors are being employed to track how many knocks or high-impact contact situations occur to reduce the risk of serious personal injury to the player.
Individual performance improvement
Analytics can be utilised in sports to drive small performance increments at the individual athlete level. IBM helped ultracyclist, David Haase, in his 2015 Race Across America, to look at the best times based on historical data for him to sleep and rest – due to headwinds and tailwinds. This helped to make his time spent cycling more efficient, and without this simple piece of data, he would have used much more energy trying to cycle in less than optimum conditions. As David Haase himself put it, previously, he just relied on “fitness and luck”.
In the field of swimming, athletes are utilising on-body sensors to track each component part of their training to make small efficiencies, such as monitoring stroke technique or kick frequency. Small changes at this level can make the difference between finishing a few seconds ahead of your competitors.
The amateur athlete
One interesting point is that big data hasn’t just started with the large, multinational clubs and filtered down slowly to the public, there is in fact a two way trend taking place where consumers are tracking their own personal fitness at an individual level; relying on data and analytics to deliver better insights into their training regimes. Technologies such as Fitbit are now delivering in-depth analytics across sleep, exercise, activity and nutrition to help amateur athletes track their progress and make improvements.
only listed a handful here. From Nascar drivers using sensors to Olympic athletes employing “data not doping” to drive huge performance increases, analytics is becoming central to every training session and live sporting event.