After the experience with the Albanian national team, the promotion to the Lega Pro with the Triestina Calcio and after having missed the play-off by a whisker, the trainer Luca Bossi shared his experience with gpexe, not only in terms of monitoring the athletic performance but also regarding experimentation, looking for correlations between technical and physical aspects of the match.

1) How often do you utilise gpexe?

I use the gpexe during every session and in all the matches: home, away, cup and friendly games, except during training on the day before the match, so about 5/6 times per week.

During the week to monitor training workloads and during games to analyze, in particular, if there are large swings on the performance peaks.

2) Which parameters supplied by gpexe are you particularly interested in and why?

It’s important for me to give both the coach and the players that request it, numbers that are intuitively easy to understand and that can be a reference for performance both on the volumes and on intensities.

There are 3 parameters: total distance, average power, number of power events. As for my analysis, I use all your default parameters, especially power events.

3) What type of feedback do you gain from the parameters of interest?

I compare game with game, the players are divided by role and I make comparisons between the wings.

During training, I use gpexe to evaluate workloads. If I find big differences, then I investigate why this could have happened.

“my goal is to create targets. I know the load expected for each day and we try to stick with that”

Luca Bossi
Triestina Fitness Coach

4) In what way does the monitoring of the data impact on the planning of your work?

My goal is to create targets. I know the load expected for each day and we try to stick with that.

If during a session the load is too intense or too light compared to the work done previously, I talk with the coach to calibrate the following days.

5) Do you use the live and for which purpose?

For the moment we do not have live, but I had the chance to use it with the Albanian national team. In our specific case, we had set individual energy expenditure targets, and in real time we were able to verify player by player if the goal was achieved.

I also see the great potential for use in the game where you could check the parameters at 5 minutes intervals in order to understand, based on the trend of his performance, when a player may have reached its limit.

6) Is there any significant data collected, as an example of analysis, which you can share with us?

I collected the match data taking into consideration only those having a very good GPS signal (on some occasions, the type of stadium conditioned the quality of reception). I tried to understand if there was any relationship between the physical data (distance traveled, average metabolic power and number of power events) and some technical data (match result, time of possession, average center of gravity of the team, shots made and shots taken). Often in commenting the game, it happened to me that the physical data were commented taking for granted that “… if I made a lot of possession then I have traveled a lot …”, or that “… if I have produced a high power then I kept the team’s center of gravity high … “.

In the chart below I have tried to summarize some of these quantities to highlight that it is really difficult to find systematic relationships:

• there is a rather obvious relationship between the average metabolic power (X axis) and the distance traveled (Y axis), but not always so direct;
• there does not seem to be a specific reason for me to win (▲), draw (●) or lose (▼);
• there does not seem to be a criterion that allows me to keep possession for more time (intensity of color);
• there does not seem to be a criterion that allows me to do more shots on goal (the bigger the symbol and the more shots were made).

In short, it was always more advantageous to look for feedback in the physical data behind a precise request or curiosity of the coach and comment on the match data with him!

7) What type of interaction do you have with the coach relative to the data collected?

In addition to providing the data I have indicated in the second question, I combine 3 physical parameters with 4 technical parameters.

Then, with the coach, we try to find a correlation between the result and physical performance.

8) What type of interaction do you have with the player relative to the data collected?

All players receive a daily report with the 3 parameters previously mentioned.

To those who request it, I give access to the web app, so that they can keep an eye on their own data. If any of these data seems to be inconsistent, we discuss them together.

9) How much time do you utilise on average for the operative phase of the system and on the data analysis?

I have a device for each player and it takes:

• 4 / 5 minutes to switch them on and get the players to put the vests on;
• 15 minutes to download the data and send both the technical staff and the players the daily report after each session and the games report, on the bus for the return journey;
• half an hour / an hour for three times a week. In my opinion, it makes no sense to have data and not study them, and for this reason, I always try to find the correlation between what I collect and the results we achieve.

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?

I had no experience with other GPS and I chose gpexe simply because I’ve heard great things about it and I knew the work done by Cristian Osgnach.