Fitness coach Mattia Vincenzi shares his experience of how he started using the gpexe system, initially monitoring the matches to create a model and then setting up a database of individual exercises to plan the weekly training sessions.
1) How often do you utilise gpexe?
We use it every day: indistinctly, from training to matches, seeing that the open structures of the stadiums allow it.
2) Which parameters supplied by gpexe are you particularly interested in and why?
We choose different parameters for coaches and players, and others for the fitness coaches. At the end of each session we create a report and hang it in the locker room, displaying the 8 parameters we consider the most important for the players to understand the performance:
total distance, average power, acceleration and deceleration events, power events, total running distance, total walked distance and maximum speed. We also check the recovery time between two different power events, the power expressed in the active phase and in the recovery one.
3) What type of feedback do you gain from the parameters of interest?
We only started using the system this year, so we are now focused on collecting some data from official games to create an individual performance model, which depends on different factors.
For example: how was the score during the game, which was the tactical strategy, the module of the opponent, etc… Therefore, for every single player, we average the most useful parameters in order to compare them with the work they did during the week.
“we created an exercise database, so we can weekly schedule the exercise on the basis of the tactical-technical goals the coach aims to achieve”
Mattia Vincenzi
PFK Levski Sofija Fitness Coach
4) In what way does the monitoring of the data impact on the planning of your work?
By monitoring the average values of the game, I create references that I use to measure the individual workload during training. For example: if a player, during the weekly training always has much lower values than during the game, I will make sure to train him so that he can reach the average values measured during the game.
All this, however, taking into account the coach’s specific training objectives; i.e. in a training session, the technical-tactical goals may not require power or loads comparable to the competition’s ones. In any case, there will always be a comparison of the data collected with the coach, at the end of each session, in which we will evaluate the data collected and how to proceed for the next sessions, optimizing our time.
5) Do you use the live and for which purpose?
We use the live during every match, so as to have cuts every 15 minutes and averages ready at the end of the game.
6) Is there any significant data collected, as an example of analysis, which you can share with us?
The horizontal trend allows me to assess the decrease in performance during a match and there can be two different scenarios:
1 – the performance does not decrease (flat trend) because the intensities are quite low;
2 – the performance decreases (markedly decreasing trend) because the intensities at the beginning are high and it is not possible to maintain them for the whole duration of the game, or because the intensities at the end are particularly low due to a so-called “result management strategy”.
On the contrary, the vertical trend allows me to assess the course of the game for every 15-minute period during the season. In this case, the evaluation on the intensities cannot be separated from the technical-tactical aspects.
The staff can be interested both in verifying an increase in the intensity of the game during the season (the team or the specific role is able to sustain higher intensities), and in verifying a decrease in the intensity of the game (the team/role manage the intensity to optimise the overall efficiency of the team without affecting the technical-tactical goal).
7) What type of interaction do you have with the coach relative to the data collected?
At the end of the match, there is a post-game analysis of the subjective and visual perceptions the coach had during the competition about both technical and physical elements. Then, we compare these perceptions with the recorded data; sometimes, for some player, it happens to find differences between our impression and his values.
We find a correlation between physical performance and the type of game for the match just ended. We created an exercises database, so we can weekly schedule the exercises on the basis of the tactical-technical goals the coach aims to achieve, taking into account the relationship between training values and game values.
8) What type of interaction do you have with the player relative to the data collected?
At the end of each training and match, my coworker Petar Peev and I explain the report to all players. Little by little, they have become familiar with the parameters and this allows each of them to create a personal data archive, having an idea of all the progress each one is making, comparing with the other teammates based on the position.
Then, if there is something specific to deal with, either on my part or from a specific player, because he feels the need for clarification, we have a one-to-one conversation. This helps each player understanding his personal condition.
9) How much time do you utilise on average for the operative phase of the system and on the data analysis?
Downloading the data and having them ready on the web app takes about 15 minutes, whilst delivering and collecting the vests for all players for about half an hour.
The data analysis takes 15-20 minutes at the end of each game and session, with the staff and all players involved. Finally, at home, I review the data more thoroughly for the necessary time.
10) What pushed you to choose gpexe and have you had any experience with other GPS systems, and if so, what differences did you find?
The first time I had the opportunity to use a GPS system was in 2008. The systems at that time were relatively immature, slow, complex and inaccurate. Then, I haven’t used them for a long time. Still, when the time came to choose, I wanted a quick and easy to use the system, based on the metabolic power model (which in my opinion is the most evolved) and therefore extremely accurate.
By gathering some information and asking my colleagues from other teams, I chose yours, which, among other things, gave me the added advantage of the data storage on Cloud, that allows me to always have the data at my fingertips.
