Session Report Analysis

Are you tracking the right metrics to maximise team and individual performance?

Using GPS in team sports is a valuable tool for tracking key metrics in team and individual performance. The ability to analyse this data using different report types such as single sessions and multiple sessions across a season can give a useful insight into individual players and their performance within the team as well as the team as a whole. This can also highlight any areas of improvement required. These reports are beneficial for gaining knowledge in a range of areas which will be discussed in this blog post. Firstly, monitoring players performance for training optimisation1. This is useful for understanding individual players' performance and comparing against the team for areas of improvement. Coaches can use this to implement training strategies to improve individuals performance.  This data can also be used for tactical analysis of the team's performance. The use of positional maps including heat maps and average player positions can give further insight to coaches on the team formation in a game and highlight areas of weakness2. Finally these reports can also be useful for injury prevention by tracking if players are at risk of an injury or for those returning to play from a previous injury 3,4.

Session Reports will show all the key metrics recorded across specific games and also throughout specific time periods. Firstly, single session reports, which can be seen in Figure 1 show an in depth analysis of the whole team performance and also individual players  from one match session. By looking at the single sessions you can compare players within the team to observe any areas of strong performance and areas of weakness. 

Figure 1 - Single session report for an individual athlete within a team.

The 5 key benchmarks that can be seen are total distance; high intensity running; sprint distance; metres per minute and top speed. These give an insight into the volume and intensity of a match for each player. For example a match with a high total distance but low sprint metrics would be a high volume session but low intensity. Benchmarks give a good understanding of where this individual athlete is performing in comparison to the rest of the team average; this also gives a clear visual for areas of improvement required. These are also useful for clubs with academy teams of different levels to see if players are over performing and ready to progress to a higher level within the academy. 

Another report type that is useful for team and individual analysis are Summary reports. These show an athlete's training load over a period of weeks. An example of this can be seen in Figure 2, which shows a two week period of an athlete and their training load recorded. This is beneficial for long term analysis of a specific player for their performance progression across a season or to highlight if they are at risk of an injury. For example, if their goal was to increase top speed over the season.

Figure 2 - Summary report of individual player over a two week period.

Monitoring Workload 

Figure 3 - Athletes benchmarks data for key performance metrics 

Monitoring players' training load is useful for tracking any changes in performance over time and identifying areas to improve (e.g endurance/agility). These are also useful for monitoring a player against the rest of the team to check they are maintaining and performing to the right standard for the team. By looking at a player's benchmarks this can give a great insight into their performance in a match session and areas for improvement. This can be seen in Figure 3.

This athlete is performing to a similar level  compared with the team average. The total distance and top speed are expected for this gender and age group5 (male player aged 21). However, this player is above average in the category for high intensity running and sprint distance.These values could indicate two different options. The athlete is performing to a higher ability compared to the rest of the team overall or they are overtraining and at risk of injury. This can be assessed by looking at his previous sessions and what is expected of someone of this age group.

The average sprint distance in professional male footballers is 213±111m6  (speed above 25.2kph). From this data it can be seen that the player is performing to a competitive level with a good effort performed in all metric areas of external load. This player may be at risk of burnout due to the high intensity metrics. It is therefore important for coaches to look at recent sessions to see if there is a spike in these metrics.

Figure 4 - Athletes benchmarks data for key performance metrics 

Furthermore, benchmarks can also highlight players who are potentially underperforming and any key areas of improvement that are needed. Figure 4 shows a player's key metrics and highlights that they are performing a high volume of work with  their total distance and metres per minute which are close to the team average. However, the intensity metrics are much lower and can clearly be seen this is an area for improvement. This data can show coaches that this player’s training should focus more on improving their intensity metrics so that they can increase their performance over the season. Useful training drills to improve speed can include plyometric movements such as squat jumps and box jumps. 

Tactical Analysis 

Reports can also give insight into players movements and positioning on the pitch during a game. This can be observed through heatmaps, intensity maps and average player positions. The use of positional maps to track movement on the pitch of players is useful for identifying the strengths and weaknesses of the team in a match. For example, heat maps show areas on the pitch where players had frequent movements. This can highlight if a player was in their correct position and  if their movements up and down the pitch played into successful play of the team. 

Tactical analysis using heat maps has been previously  studied7,8. These heat maps can highlight players' tactical zones and if they kept to the strategy planned ahead of the game. This is also useful to highlight variability of each positional group (defence midfield and forwards). Coaches can extract this data for useful insights and implement a development plan. For example, coaches could monitor defensive players' positions across multiple games and look for any variability in their heatmaps. This could be paired with knowledge from the match such as if it was a win or loss to further interpret areas of improvement. Defenders may have a low variability in their heat maps meaning they are maintaining the pattern of the tactics set by the coaches. However, this could turn into predictable performance by players and useful for coaches' insight to change team tactics. On the other hand if the defenders heatmaps are constantly changing from game to game this could highlight they have difficulty in finding successful formations across multiple games.

Previous studies that have monitored players' heat maps over a season reported findings that wing midfielders and wing defenders had the most variance in their positioning on the field across games. This variance may have been running to support other players on the field at important times in a match. However, the frequency that they returned to their correct formation on the field was varied by a change in the red area on the heat map2

Figure 5 - Strikers heatmap from first and second half of game. 

Figure 5 shows the heatmap of the striker during a competitive game. From the map the above player spends a lot of time in and around the opposition box, particularly focusing on the penalty spot and 6-yard area where they can get the highest chance of scoring. Heatmaps also help show how players have implemented the tactical plan set out by their positional demands and whether they have been able to stay in the correct position throughout the game. The opposite is also true and heatmaps are valuable for observing if they have strayed from their normal position by highlighting any infrequent runs which can also be observed in figure 7. From figure 5 we can see that this is a striker who largely focussed on ensuring they ended up in high scoring areas of the pitch indicated by the yellow and red areas. It can be seen by the greener areas where the player has made channel runs and the areas in which they pressed the opposition back line. 

Figure 6 - Average player position from match data 

Furthermore, along with heat maps, average player position maps, seen in Figure 6,  are useful for further insight into team strategy on formation and performance. If the team performed poorly this can highlight formation issues and where the team can improve. 

Injury Prevention

Analysing data from session reports  across a period of time is also useful for injury prevention of players in the team. By tracking their data and observing performance their workload across a weekly period can be monitored. The risk of injuries in football will be discussed in more detail in our upcoming blog series. A quick way to use reports for injury prevention is by monitoring their workload across a weekly and monthly period and looking for any abnormalities in the data that may put players at an increased risk of injury. Previous studies have found that in match play over 60%  of sustained injuries are non contact9.

The relationship between sports injury and training load has been studied frequently in recent years with many findings suggesting that identifying high risk activities that could lead to an injury such as a sudden rise in high speed activities such as sprint distance and top speed and accelerations/ decelerations4. These are key metrics coaches can observe to see if any players are at risk of sustaining an injury such as a hamstring injury. This data collection method is also useful for analysing a player's return to play after an injury. Using GPS metrics can monitor a players progression back to training to ensure they are not over working and determine along with speaking to doctors and the players when they are ready for a full return. 

Figure 8 - Athlete summary report across a two week period 

From the data in Figure 8  over a two week period of training and games you can observe a player's external load. From the data it can be seen that this athlete's total distance has increased on week two but sprint distance, top speed and accelerations have all reduced. 

This data suggests that the athlete should focus on improving their intensity metrics in training to optimise performance and reduce any risk of injury occurring. 

To conclude, using session reports for a deeper insight into a match session and over a season is useful for coaches and players to easily assess performance in different areas. This includes external load performance and also tactical performance of the whole team. These reports are extremely useful for long term tracking of teams performance and progression across a season in several areas. 

See how you can give your team the EDGE and train like the pros.

References:

  1. Ravé G, Granacher U, Boullosa D, Hackney AC, Zouhal H. How to use Global Positioning Systems (GPS) data to monitor training load in the “Real world” of elite soccer. Frontiers in Physiology. 2020;11.  
  2. Moura FA, Santana JE, Vieira NA, Santiago PR, Cunha SA. Analysis of Soccer Players' Positional Variability During the 2012 UEFA European Championship: A Case Study. Journal of Human Kinetics. 2015;47:225-36.
  3. Ehrmann FE, Duncan CS, Sindhusake D, Franzsen WN, Greene DA. GPS and Injury Prevention in Professional Soccer. J Strength Cond Res. 2016;30:360-7
  4. Martins F, Marques A, França C, Sarmento H, Henriques R, Ihle A, de Maio Nascimento M, Saldanha C, Przednowek K, Gouveia ÉR. Weekly External Load Performance Effects on Sports Injuries of Male Professional Football Players. Int J Environ Res Public Health. 2023 Jan 8;20(2):1121.
  5. Del Coso J, Brito de Souza D, Moreno-Perez V, et al. Influence of Players' Maximum Running Speed on the Team's Ranking Position at the End of the Spanish LaLiga. Int J Environ Res Public Health. 2020 Nov 27;17:8815
  6. Ingebrigtsen J, Dalen T, Hjelde GH, Drust B, Wisløff U. Acceleration and sprint profiles of a professional elite football team in Match Play. European Journal of Sport Science. 2014;15(2):101–10.  
  7. Moura FA, Martins LE, Anido RO, Ruffino PR, Barros RM, Cunha SA. A spectral analysis of team dynamics and tactics in Brazilian football. Journal of Sports Sciences. 2013;31(14):1568–77.  
  8. Okihara K, Kan A, Shiokawa M, Choi CS, Deguchi T, Matsumoto M, Higashikawa Y. Compactness as a strategy in a soccer match in relation to a change in offence and defence. J Sports Sci. 2004;22(6):515.
  9. Owoeye, O.B.A., VanderWey, M.J. & Pike, I. Reducing Injuries in Soccer (Football): an Umbrella Review of Best Evidence Across the Epidemiological Framework for Prevention. Sports Med. 2020; 6,46.
PLAYERDATA APP

UNLOCK YOUR PERFORMANCE DATA

The PlayerData app enables coaches, players, and any other critical staff to access performance data immediately from anywhere.

Session Report Analysis

February 23, 2023
PlayerData Session Report Analysis

Using GPS in team sports is a valuable tool for tracking key metrics in team and individual performance. The ability to analyse this data using different report types such as single sessions and multiple sessions across a season can give a useful insight into individual players and their performance within the team as well as the team as a whole. This can also highlight any areas of improvement required. These reports are beneficial for gaining knowledge in a range of areas which will be discussed in this blog post. Firstly, monitoring players performance for training optimisation1. This is useful for understanding individual players' performance and comparing against the team for areas of improvement. Coaches can use this to implement training strategies to improve individuals performance.  This data can also be used for tactical analysis of the team's performance. The use of positional maps including heat maps and average player positions can give further insight to coaches on the team formation in a game and highlight areas of weakness2. Finally these reports can also be useful for injury prevention by tracking if players are at risk of an injury or for those returning to play from a previous injury 3,4.

Session Reports will show all the key metrics recorded across specific games and also throughout specific time periods. Firstly, single session reports, which can be seen in Figure 1 show an in depth analysis of the whole team performance and also individual players  from one match session. By looking at the single sessions you can compare players within the team to observe any areas of strong performance and areas of weakness. 

Figure 1 - Single session report for an individual athlete within a team.

The 5 key benchmarks that can be seen are total distance; high intensity running; sprint distance; metres per minute and top speed. These give an insight into the volume and intensity of a match for each player. For example a match with a high total distance but low sprint metrics would be a high volume session but low intensity. Benchmarks give a good understanding of where this individual athlete is performing in comparison to the rest of the team average; this also gives a clear visual for areas of improvement required. These are also useful for clubs with academy teams of different levels to see if players are over performing and ready to progress to a higher level within the academy. 

Another report type that is useful for team and individual analysis are Summary reports. These show an athlete's training load over a period of weeks. An example of this can be seen in Figure 2, which shows a two week period of an athlete and their training load recorded. This is beneficial for long term analysis of a specific player for their performance progression across a season or to highlight if they are at risk of an injury. For example, if their goal was to increase top speed over the season.

Figure 2 - Summary report of individual player over a two week period.

Monitoring Workload 

Figure 3 - Athletes benchmarks data for key performance metrics 

Monitoring players' training load is useful for tracking any changes in performance over time and identifying areas to improve (e.g endurance/agility). These are also useful for monitoring a player against the rest of the team to check they are maintaining and performing to the right standard for the team. By looking at a player's benchmarks this can give a great insight into their performance in a match session and areas for improvement. This can be seen in Figure 3.

This athlete is performing to a similar level  compared with the team average. The total distance and top speed are expected for this gender and age group5 (male player aged 21). However, this player is above average in the category for high intensity running and sprint distance.These values could indicate two different options. The athlete is performing to a higher ability compared to the rest of the team overall or they are overtraining and at risk of injury. This can be assessed by looking at his previous sessions and what is expected of someone of this age group.

The average sprint distance in professional male footballers is 213±111m6  (speed above 25.2kph). From this data it can be seen that the player is performing to a competitive level with a good effort performed in all metric areas of external load. This player may be at risk of burnout due to the high intensity metrics. It is therefore important for coaches to look at recent sessions to see if there is a spike in these metrics.

Figure 4 - Athletes benchmarks data for key performance metrics 

Furthermore, benchmarks can also highlight players who are potentially underperforming and any key areas of improvement that are needed. Figure 4 shows a player's key metrics and highlights that they are performing a high volume of work with  their total distance and metres per minute which are close to the team average. However, the intensity metrics are much lower and can clearly be seen this is an area for improvement. This data can show coaches that this player’s training should focus more on improving their intensity metrics so that they can increase their performance over the season. Useful training drills to improve speed can include plyometric movements such as squat jumps and box jumps. 

Tactical Analysis 

Reports can also give insight into players movements and positioning on the pitch during a game. This can be observed through heatmaps, intensity maps and average player positions. The use of positional maps to track movement on the pitch of players is useful for identifying the strengths and weaknesses of the team in a match. For example, heat maps show areas on the pitch where players had frequent movements. This can highlight if a player was in their correct position and  if their movements up and down the pitch played into successful play of the team. 

Tactical analysis using heat maps has been previously  studied7,8. These heat maps can highlight players' tactical zones and if they kept to the strategy planned ahead of the game. This is also useful to highlight variability of each positional group (defence midfield and forwards). Coaches can extract this data for useful insights and implement a development plan. For example, coaches could monitor defensive players' positions across multiple games and look for any variability in their heatmaps. This could be paired with knowledge from the match such as if it was a win or loss to further interpret areas of improvement. Defenders may have a low variability in their heat maps meaning they are maintaining the pattern of the tactics set by the coaches. However, this could turn into predictable performance by players and useful for coaches' insight to change team tactics. On the other hand if the defenders heatmaps are constantly changing from game to game this could highlight they have difficulty in finding successful formations across multiple games.

Previous studies that have monitored players' heat maps over a season reported findings that wing midfielders and wing defenders had the most variance in their positioning on the field across games. This variance may have been running to support other players on the field at important times in a match. However, the frequency that they returned to their correct formation on the field was varied by a change in the red area on the heat map2

Figure 5 - Strikers heatmap from first and second half of game. 

Figure 5 shows the heatmap of the striker during a competitive game. From the map the above player spends a lot of time in and around the opposition box, particularly focusing on the penalty spot and 6-yard area where they can get the highest chance of scoring. Heatmaps also help show how players have implemented the tactical plan set out by their positional demands and whether they have been able to stay in the correct position throughout the game. The opposite is also true and heatmaps are valuable for observing if they have strayed from their normal position by highlighting any infrequent runs which can also be observed in figure 7. From figure 5 we can see that this is a striker who largely focussed on ensuring they ended up in high scoring areas of the pitch indicated by the yellow and red areas. It can be seen by the greener areas where the player has made channel runs and the areas in which they pressed the opposition back line. 

Figure 6 - Average player position from match data 

Furthermore, along with heat maps, average player position maps, seen in Figure 6,  are useful for further insight into team strategy on formation and performance. If the team performed poorly this can highlight formation issues and where the team can improve. 

Injury Prevention

Analysing data from session reports  across a period of time is also useful for injury prevention of players in the team. By tracking their data and observing performance their workload across a weekly period can be monitored. The risk of injuries in football will be discussed in more detail in our upcoming blog series. A quick way to use reports for injury prevention is by monitoring their workload across a weekly and monthly period and looking for any abnormalities in the data that may put players at an increased risk of injury. Previous studies have found that in match play over 60%  of sustained injuries are non contact9.

The relationship between sports injury and training load has been studied frequently in recent years with many findings suggesting that identifying high risk activities that could lead to an injury such as a sudden rise in high speed activities such as sprint distance and top speed and accelerations/ decelerations4. These are key metrics coaches can observe to see if any players are at risk of sustaining an injury such as a hamstring injury. This data collection method is also useful for analysing a player's return to play after an injury. Using GPS metrics can monitor a players progression back to training to ensure they are not over working and determine along with speaking to doctors and the players when they are ready for a full return. 

Figure 8 - Athlete summary report across a two week period 

From the data in Figure 8  over a two week period of training and games you can observe a player's external load. From the data it can be seen that this athlete's total distance has increased on week two but sprint distance, top speed and accelerations have all reduced. 

This data suggests that the athlete should focus on improving their intensity metrics in training to optimise performance and reduce any risk of injury occurring. 

To conclude, using session reports for a deeper insight into a match session and over a season is useful for coaches and players to easily assess performance in different areas. This includes external load performance and also tactical performance of the whole team. These reports are extremely useful for long term tracking of teams performance and progression across a season in several areas. 

See how you can give your team the EDGE and train like the pros.

References:

  1. Ravé G, Granacher U, Boullosa D, Hackney AC, Zouhal H. How to use Global Positioning Systems (GPS) data to monitor training load in the “Real world” of elite soccer. Frontiers in Physiology. 2020;11.  
  2. Moura FA, Santana JE, Vieira NA, Santiago PR, Cunha SA. Analysis of Soccer Players' Positional Variability During the 2012 UEFA European Championship: A Case Study. Journal of Human Kinetics. 2015;47:225-36.
  3. Ehrmann FE, Duncan CS, Sindhusake D, Franzsen WN, Greene DA. GPS and Injury Prevention in Professional Soccer. J Strength Cond Res. 2016;30:360-7
  4. Martins F, Marques A, França C, Sarmento H, Henriques R, Ihle A, de Maio Nascimento M, Saldanha C, Przednowek K, Gouveia ÉR. Weekly External Load Performance Effects on Sports Injuries of Male Professional Football Players. Int J Environ Res Public Health. 2023 Jan 8;20(2):1121.
  5. Del Coso J, Brito de Souza D, Moreno-Perez V, et al. Influence of Players' Maximum Running Speed on the Team's Ranking Position at the End of the Spanish LaLiga. Int J Environ Res Public Health. 2020 Nov 27;17:8815
  6. Ingebrigtsen J, Dalen T, Hjelde GH, Drust B, Wisløff U. Acceleration and sprint profiles of a professional elite football team in Match Play. European Journal of Sport Science. 2014;15(2):101–10.  
  7. Moura FA, Martins LE, Anido RO, Ruffino PR, Barros RM, Cunha SA. A spectral analysis of team dynamics and tactics in Brazilian football. Journal of Sports Sciences. 2013;31(14):1568–77.  
  8. Okihara K, Kan A, Shiokawa M, Choi CS, Deguchi T, Matsumoto M, Higashikawa Y. Compactness as a strategy in a soccer match in relation to a change in offence and defence. J Sports Sci. 2004;22(6):515.
  9. Owoeye, O.B.A., VanderWey, M.J. & Pike, I. Reducing Injuries in Soccer (Football): an Umbrella Review of Best Evidence Across the Epidemiological Framework for Prevention. Sports Med. 2020; 6,46.