So far in our series, we have covered the difference between the various types of electronic performance and tracking systems (EPTS) and the importance of connecting condition, workload and tactics-related insights.
The next stop is real-time analysis. By now everyone involved with performance analytics is acutely aware of the need to observe data in real-time to the point it has become the topic “du jour” in the sector. However, there appears to be limited understanding of which types of real-time data can and needs to be observed and how best to apply it in practice.
There are plenty of tools (optical and wearable systems, various statistical services etc.) which are able to collect live data, but in many cases it is limited to raw parameters or at best some rudimentary indicators. Because of these limitations, coaches have been forced to develop their own shortcuts using these basic data points, such as time spent in heart rate zone or distance in the different sprint zones, to gauge the performance of their players.
This level of an analysis is only a minor step up from using a naked eye to see how sweaty and red a player’s face is to decide if they are too tired to continue playing.
What’s more, even on occasions where there are available numbers, people tend to trust their eyes over the data – after all, the action is happening on the field, not on the tablet. They approach data as a way to validate what they believe they are seeing instead of helping them predict what may happen.
Such a mindset limits the data’s usefulness in real-time situations where quick decisions need to be made. This is especially true on matchdays where so many variables are out of the coaches’ control, whether it’s opposition tactics, the pace of the match, media obligations or fan engagement. And training sessions pose their own challenges since you are now observing not only the 11 people on the pitch but the entire squad.
The information avalanche from a variety of sources can be absolutely overwhelming. This is why it is imperative to invest time in establishing the connections leading from raw data to parameters to indicators to insights.
Raw data is simply the thousands of data points that any system collects, such as distance covered or time on the field. One level up from this are the parameters with which most of us are familiar – heart rate in different zones; max and average heart rates; distance in speed zones; total distance; counts of sprints, acceleration, deceleration and direction changes.
The number of parameters tracked is just as overwhelming, and a point of pride for many data, analytics and systems providers. This is why combining them into higher order indicators and insights is the data-driven way to give coaches the shortcuts they require to make decisions and in-game adjustments on the fly.
The hard part then becomes convincing the coaches to abandon their eyes and trust the science.
The benefits, however, can be enormous when considering the mounting costs of injuries. According to one study, injuries across Europe’s five major soccer leagues (the Premier League, Serie A, LaLiga, Bundesliga and Ligue 1), rose by 20 per cent and cost teams more than UK£500 million last season. Another report claimed the cost of hamstring injuries alone was UK£100 million in the same five divisions.
Coaches and analysts need to be able to understand and explain data during games as quickly as possible
Team executives and coaches need to ask themselves several key questions when it comes to the performance of their players:
- Is our team’s physical performance better than the benchmarks for the whole match and the entire season?
- Do we have zero non-contact injuries?
- Are we able to train the group and the individual? Are we able to create the best possible personalised regime for training intensity, duration, recovery, nutrition, sleep, supplements, physio and medical care based on position, age, fitness and condition level?
- Do we have precise daily, weekly, and monthly thresholds, targets, and alerts, and do we know when our players have reached or achieved them? Do we always achieve all our annual targets for player development and periodisation?
- Do we know the exact fatigue level for every single player stepping on the grass before the match? Is our in-game management perfect? Do we always identify any less in performance and the cause, whether it’s a temporary issue or fatigue?
- Do we always know how to control match pace? Does our team has enough “juice” for the extra press or counter-press, how high can our line be, who can do it most efficiently right now? Or do we need to “kill” the match tempo?
- Are we able to communicate quickly to players when individual limits are reached, and what they should do to recover?
- Do we know what is the exact tactical execution in real-time? Can we see how ‘free’ somebody’s ‘free-role’ is by looking at a heatmap, how fluid the transitions are during the match and the exact distance between players or important tactical lines? Is it possible to see exactly how wide we play?
- Can we see during the game if a player is as offensively or defensively oriented as we want them to be, or how our tactical changes or specific events affect the match? How do we react after scoring, conceding, or a red card?
- Do we know at every single moment which players are have a positing impact on performance and who isn’t?
- But above all, can we verbally explain the adjustments we need to make at half time and are they well received, understood and visualised by the players during that short period of time?
If a team can answer positively to the above then they have cracked the code. For everyone else, the answers to these questions should determine how much time, energy, and money they need to invest in measuring what matters the most.
At the very least, there are two main outcomes that should be prioritised. The first is a detailed knowledge of the connections amongst the various parameters so that coaches can focus on the key indicators of individual and team performance.
This outcome will lead to the second one: the ability to use these insights in real-time to make the best possible decisions. And, contrary to popular belief, these two outcomes do not require significant expenditure.
The key is preparation. Teams will gain control over player fatigue, decrease non-contact injuries and improve game management – all in real-time.