Small sensors - Massive impact

Playermaker utilizes advanced AI and machine learning technology to accurately measure foot-ball interaction performance.

THE IMPORTANCE OF THE LOCATION OF THE SMART SENSORS

The most advanced measurement for foot specific interactions. 

In Football, every interaction involves the foot and is the reason why the location of the sensor on the boot is vital for the accurate measurement of foot-ball interactions. It allows the sensors to measure all data like technical ability, physical ability and gait parameters of a player. 

The sensors can measure any movement of the foot including rotations of the ankle or contact with the ground; making it the only technology measuring foot specific interactions. 

MORE THAN JUST CONNECTED FOOTWEAR

With a real-time machine learning algorithm, every step and every ball touch counts. Playermaker's 6-axis motion smart sensor is built with a gyroscope and accelerometer that samples movement events at 1000 times/sec.

Validated by top universities around the world, Playermaker is constantly being put to the test in meeting the highest academic research standards.

800M+

Motion Data
Samples

1.5M+

Running
Meters

400K+

Motion Data
Events

PLAYER PERFORMANCE BENCHMARKING CAPABILITIES

Benchmarks can be set for:

  • Position-Identify benchmarks for every position and parameters that identify with each position. A effective Central midfielder needs to meet a certain number of individual ball possessions and have less time on the ball with a certain level of accuracy of pass completion.
  • Team-Set benchmarks for the team and adapt to team playing style. A team playing long ball football need to achieve a 80% level of accuracy of longpasses from the defensive line in every match.
  • Age Group-Identify benchmarks across all age groups in clubs and academies. Compare age groups playing level and develop players more effectively for first team level.
  • Club (First Team, Academy, Youth)-Develop more home grown players across all age phases and increase player investment in transition phases.

RUNNING A MACHINE-LEARNING ALGORITHM ON A DIVERSE DATABASE TO IMPROVE THE SQUAD

A powerful algorithm identifies trends within a diverse database by collecting performance data sets from different age groups, male and female players, different locations (mainly from U.S, Europe and Latin America) and players from all levels (Elite, Professional, Semi-professional, Non-League, Academies and youth teams). 

Connecting the Steps

Data is gathered and processed on the spot, due to the sensor being attached directly to a player's boot.

Advanced and powerful processing capabilities ensures data accuracy and security.
Machine learning algorithms recognize different movements where data is instantly sent to the analysis platform.
User-friendly dashboards visualize the collected data for easy analysis of player and team performance over time.


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PlayerMaker solution?