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How does GPS help us construct a representative training environment?

Updated: Feb 5, 2022

A reverse engineering training process. Adapted from product engineering. GPS can help us to 1) assess game demands, 2) monitor training and 3) inform modifications.

What is the purpose of technology in sport? In a line, I would say it is to enhance the efficiency of coaching processes.

What is the purpose of GPS in sport? In a line, I would say the purpose of GPS is quantify movement demands of the sport - both training and games.

Looking at other sports, especially the "stopwatch" sports - long-distance running, swimming, cycling for example, it is much easier to quantify training and race demands. In team sports, specifically rugby union, it is much more difficult because there are up to 30 players on the pitch at once, with everyone moving on a different path and at different speeds. It is a very chaotic environment, which makes extremely difficult and time-consuming, near impossible to calculate the distance every player has moved, never mind the speed they move at.

To put it further into context - how easy do you think it would be to predict the distance a tennis player moved in a game of tennis. You can see every move they make and they are on a smaller playing area. Now apply the same task to one player in a rugby game. You could only see every move the player makes if you were present at the game, or you were watching from a far out camera angle. And the size of the playing area dwarfs that of a tennis court. So at a basic level, GPS tells us the movement demands of a player. I feel it is important to clarify that from the outset, a "back to basics" if you will. From here, we can start to define how GPS can help us.

Mechanical work vs metabolic cost

Looking back on my conditioning post from a few weeks back, GPS quantifies movement demands or mechanical output, but does not give us information about the metabolic processes that underpin the mechanical output. In that post on conditioning for performance, I also said:

Athletes win medals for the mechanical work they do (winning a race), not the metabolic response to the mechanical work - no player has ever won a medal for having the highest VO2 max.

Another way to say this would be that GPS is a measure of external load, but not internal load.

From a rugby union perspective (or any other sport where the result is not determined by a stopwatch), the mechanical work a player does on the field is often an emergent behaviour of the task they have to complete at any given moment, rather than something that exclusively determines the result of the game. Often, losing teams will run harder and faster than winning teams, but also, winning teams could run harder and faster than losing teams. Looking at GPS data in isolation, tells a practitioner nothing. This for me highlights the benefit of having an integrated approach to player and team preparation, and it is not an integrated approach unless there are clear (and healthy) lines of communication between all key stakeholders: medical-performance-coaching staff (players too, depending on the context). Like any skills, they must be developed within the context of the game.

Load management v performance optimisation

For me, there are 2 uses of GPS (credit Dean Benton, read more here):

  • load management

  • performance optimisation

In both cases, we start by quantifying game demands. From a GPS persepective, we want to identify total load of a game, total load of a half, peak half demands, worst case scenario across a large pool of metrics, for a range of periods (1-10 mins). With this information, we get a clear picture of the game demands, and we can then make a better evaluation of our training demands.

We have 3 view points within our load management, metaphorically labelled as:

1) 40,000ft view

Our philosophy is pretty clear: 1+1. We play a game at the weekend (1) and we train (the equivalent of) a game during the week (+1). Taking all the individual components of a game - technical skills, contact elements, movement demands - we identify these and then put them together to formulate a training week.

2) Birdseye view

Here we would use a traffic lights system: a red session would constitute over 75% of a game load; an amber session would constitute between 50-74% of a game load; and a green session would be less than 50% of a game load.

3) On the ground

This would refer to the individual games and activities we do during a session.

Possible metrics to assess load management can include: High Speed Running; Very High Speed Running; High Metabolic Load.

When looking at the performance optimisation side of the coin, the key question is: are we preparing for the game demands? Or better yet, are we training above game demands?

Take Olympic weightlifting for example, on a competition day, an athlete might complete 6 reps in 4 hours (granted, there would be multiple preparatory lifts behind the scenes). Training, on the other hand, is much more taxing. So an athlete trains much harder than the competition, making the competition somewhat of a breeze. In running, a common phrase is "train hard, race easy". We want to apply the same concept to our training. We want training to be at such an intensity, that either a) the game becomes easy or b) the opposition cannot compete for the duration of the game. For us, our intensity target is 130% of a game, we want to train at 130% of match intensity, at a minimum.

Going back to the practice design aspect of training, this gives coaches a target to hit. When the objective of an activity or a session is to train at 130% of game demands, coaches can manipulate aspect of their activities to promote a greater physical intensity. This could include increasing pitch size, reducing the number of players or having a second ball to reduce "dead time" between plays. However, the entire support staff (coaches and performance staff) cannot solely have GPS metrics as their objective for a session or a week. This is a classic case of the tale wagging the dog. Goodhart's law comes to mind (see image below) - GPS, in my opinion, should never be a target. Instead, it is something to measure the efficacy of training:

An important point here is that the objective must be defined before a session or activity within a session. If the aim is to promote movement demands, then increasing pitch size would help to achieve this. If the aim is to promote the number of player contacts in a game (from a rugby union point of view), increasing pitch size is likely to have a detrimental effect. Starting with the end in mind is critical to practice design. Always keeping my skill acquisition hat on allows me to really evaluate the effectiveness of our program.

Isolating and grouping various aspects of performance can allow practitioners an opportunity to overload that aspect. For example, if the aim is to have a "fast" session, where the key physical performance metric we are looking to train is high speed running, then we can tailor all activities within the session for that, including all conditioning games and activities, and even the warm-up. Once you have the ultimate goal (in this case the session objective), you can break that down into smaller stepping stones (training games/activities). Players don't typically get an overload in a full game, whether that is a physical component, like a specific energy system or a technical component, like a skill. Therefore, practice has to be designed to isolate that component. This does not mean to train the component in isolation with tasks that are unrepresentative of the sport.

Looking back on that conditioning post (linked above):

  • Training isolated physical components can occur through representative tasks, this would be classed as conditioning, as an example - small sided games.

  • Training isolated physical components can occur through unrepresentative tasks, this would be classed as fitness/energy system development, as an example - tempo running.

We have used high intensity interval training (HIIT; MAS or tempo runs) in the past to supplement our training intensity within a session or over a week. This has led to some huge benefits to our training intensity, and the simple fact is, a HIIT block will physically overload players much more than any game block, no matter how well the game block is designed. However, I would classify using a HIIT block to increase the intensity of a session as "artificial intensity" (AI for team preparation). This is not to say it is not valid, or that a team should never do it - any team can train however they like; but looking at it from a skill acquisition point of view, a HIIT block improves the performance potential of a player, it does not make a better player.

Possible metrics to evaluate performance optimisation can include: m/min; HSR m/min; Acceleration Impulse (average accelerations).

A sample activity cycle from training.

Intensity v Density v Volume

Intensity and density are two terms often used interchangeably (at least in our environment, but both have different meanings. Throw volume into the mix and with these 3 variables, there are up to 8 different combinations of a session you could have. Here some examples:

  • Speed session: high intensity; low density; low volume.

  • Conditioning session: low-high intensity; high density; low-high volume.

  • Recovery/flush session: low intensity, low density, low volume.

Intensity refers to the relative workload of an individual. The easiest was to look at this is in relation to a person's max velocity. If a player jogs at 30% of their max velocity, this would be classed as a low-intensity effort. If a player sprints at 95% of their max velocity, this would be classed as a high-intensity effort.

Volume refers to the overall workload of an activity, a session, or a week. This would typically be measured in absolute metrics - total distance, high speed running, number of accelerations etc.

Density refers to average volume per unit of time. Simply, a 4000m session completed over 30 minutes is more dense than a 4000m session completed of 60 minutes. Here, we are looking at the density of exposure. Metrics used density could be: m/min, HSR m/min, Acc/min.

From a skill acquisition point of view, the greatest cognitive load will likely come from a high density session, and even more so from a high density and high intensity session. When players have to constantly jump from one activity to the next, or even moving on to the next rep within an activity without rest time, they are experiencing contextual interference, where the player executes multiple motor tasks in either a repetitive or interleaved format. It is important to stress that this interference will come from an activity with variable components (like a game), rather than just a drill with no decision making involved. Establishing the physical demands to a games-based approach to training is the most complete way to establish how representative (both cognitively and physically) training is of the sport.

Final thoughts

A final key point about representative design and GPS. This does not refer to the activity cycle of the training session (see example above), and if the activity cycle was similar to that of a game. From this justification, it would make sense to alternate every aspect of training - 30s of a conditioning game, one clear out, one repetition of an interval running set, followed by a set-piece. This is a random, chaotic session that is visually representative to the game based on the activities of players. Not that this is a wrong thing to do, but this would misrepresent what representative training/task design is. Representative task design has the purpose of teaching the individual to be attuned to relevant cues, to identify affordances based on their action potential, within their environment. One aim of representative task design is to make better problem solvers on the field of play. Telling a players a list of things they have to do and then having them go do it may stress them physically, but it will not stress them cognitively.

An alternative route is for coaching teams to design training in a way that is representative of the game, couples perception and action, and is at the optimal challenge point of the players involved - a games based approach. While the physical outputs of players are under less control, the cognitive demands placed on players will make them better problem solvers on the field. Utilising GPS then to feedback on the physical demands of this representative training can enable support staff to make suitable tweaks to the tasks (in the form of players numbers, game rules, pitch size etc.). This represents the optimal strategy for preparing a team, in my opinion.

This piece has discussed the use of GPS within a team sport setting. For coaches who view themselves as "architects of the environment", GPS is an awesome tool to measure how representative the training environment is of the game environment, from a movement quantification stand point. I am happy to share some data to illustrate how this looks in practice. If interested, please reach out.

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