use of (physical) data at psv eindhoven · – development from a football conditioning point of...
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Use of (Physical) Data at PSV Eindhoven
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RUUD VAN ELK
2004
Fieldlab
2004 – First Collaboration with TNO
2005 – Installation 1st Inmotio sytem
2012 – Start “Fieldlab” Project
2014 – New Inmotio LPM systems
2015 – Fully operational Fieldlab
Organization
• Involvement from all over the club
• Innovation committee
• Departments involved:
– Board
– S&C
– Sport Science
– Medical & Mental
– Video Analysis
Goals of data usage
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• Getting SIMPLE, CLEAR and FUNCTIONAL data to the coaches!
Simple visual
tool for coaches
Physical Data - Distance
- Number of Sprints
- Heartrate
- Physical Testing
Tactische Data - Passing
- Goals
- Bookings
- Distances within team
Medische Data - Antropometry
- Injuries
‘Wellness’ Data - Sleep
- Muscle “feeling”
- RPE Scores
General Data - Adress details
- Partental data
- Absence/attendance
Mentale Data? - Mindset?
- Reactiontime (specific)?
- Learning capacity?
PSV Database Overige Data?
- School data?
- Weather data?
- Ticketsales?
- Fanstore?
Data on the trainingground
Data in the stadium (SportVU, STATS)
Real-Time Data
What do we measure? (1)
• Positioning data alone tells NOTHING about
football performance!
– Combination with tactical view of the coach
– Combination with video
– Combination with tactical datasets (ORTEC)
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What do we measure? (2)
In general:
Position data (1000 Hz!)
- Speed / Distance / HID
- Acceleration / Decelaration
Heart rate
Football specific
Amount of football actions (per min)
Covered distance of the football actions (per min)
Accelerations
(Heart rate)
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• Physical input instead of output!
Data (Filtered)
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Databases and Coaches?
Database (1) – Player info
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Database (2) – Measurement info
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Database (3) – Physical Load Data
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Data Workflow
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Reporting Coaches
Collection
Analysis
Reporting
During the training- Physical
• Individual details on:
– Decrease in labor (fatigue) – e.g. #football actions/min in combination with heart rate (recovery)
– Direct feedback on supplied labor
– Monitoring individual labor (e.g. in rehabilitation)
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After the training - physical
• Individual – Monitoring individual development
– Football conditioning, speed, power.
– Objective information about reached intensity
– Direct feedback to players about (physical) performance
– Motivating / confronting
• Team – Comparing different exercises
– For instance, the difference in load between 11v11 – 5v5 or between passing exercises vs. position games
– Objective information about build up of the training week
– Development from a football conditioning point of view
• Youth Academy – Comparing the training load between the first team and the youth teams.
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Report per player / Team
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Physical Testing
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Physical Testing – Dressing Room Report
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Physical Testing – Individual Report
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How do we use these reports in daily practice?
• Monitoring of individual development
• Support in choice of individual programs
• Feedback to staff about program
• Support medical department
• Building of normal values per position / age group
• Scouting
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Future: Blending in different streams of data
Tactical Data
Scoring, Passing, effectivity
Medical Data
Injury, Antropometric data
Welness Data
Sleep, RPE scores
Conignitive Data
Reaction Timing, Learning Skills
Maybe even more?
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Challenges we face
1. Developing a smart IT infrastructure to gain, save and backup data and couple different
input sources in real time
2. Matching tactical data on physical data
3. Developing smart models and algorithms to analyze the data
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Data and Statistics – considerations and limitations
• Interpretation of variables
• Data of different systems not comparable
• Not all actions can be measured in a practical situation
(e.g. shooting, tackling)
• Specialist help necessary
• Budget considerations
• Rules (FIFA/UEFA/KNVB)
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