Use of (Physical) Data at PSV Eindhoven RUUD VAN ELK 1 2004 - - PowerPoint PPT Presentation

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Use of (Physical) Data at PSV Eindhoven RUUD VAN ELK 1 2004 - - PowerPoint PPT Presentation

Aug 06, 2023 380 likes •682 views

Use of (Physical) Data at PSV Eindhoven RUUD VAN ELK 1 2004 Fieldlab 2004 First Collaboration with TNO 2005 Installation 1 st Inmotio sytem 2012 Start Fieldlab Project 2014 New Inmotio LPM systems 2015 Fully

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Use of (Physical) Data at PSV Eindhoven

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RUUD VAN ELK

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2004

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Fieldlab

2004 – First Collaboration with TNO 2005 – Installation 1st Inmotio sytem 2012 – Start “Fieldlab” Project 2014 – New Inmotio LPM systems 2015 – Fully operational Fieldlab

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Organization

  • Involvement from all over the club
  • Innovation committee
  • Departments involved:

– Board – S&C – Sport Science – Medical & Mental – Video Analysis

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Goals of data usage

11-4-2016

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  • Getting SIMPLE, CLEAR and FUNCTIONAL data to the coaches!
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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?
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Data on the trainingground

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Data in the stadium (SportVU, STATS)

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Real-Time Data

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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!
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Data (Filtered)

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Databases and Coaches?

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Database (1) – Player info

11-4-2016

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Database (2) – Measurement info

11-4-2016

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Database (3) – Physical Load Data

11-4-2016

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Data Workflow

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Coaches

Collection Analysis Reporting

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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

11-4-2016

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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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Contact: Ruud van Elk MSc. +31631099912 r.vanelk@psv.nl