GPS AND TEAM SPORTS
• • • • Objective measures Valid and reliable Running based sports 450 elite clients worldwide
– – – – – – 17 Rugby Union teams 17 AFL teams 12 NFL teams 7 EPL teams 8 NBA teams 25 major NCAA programs
Rugby League Tackle example
Velocity 1.1 m/s
Player Load 5.5
Registered 1 moderate tackle lasting 3.8 sec
Application RHIE & Tackles
Gabbett et al, 2012
Pattern Recognition
Why Develop Algorithm’s?
• GPS monitoring in team sports:
– Distance – Velocity banded distance/efforts – GPS based Accelerations/Decelerations
• All the measures above are GPS derived. BUT….GPS is limited to running events.
Application Note: Sprint Parameter Definitions
Basic Programming & Workflow
• The main software interface is the Organize tab. Only stay on this tab for new user. • What to do once turn the units off? – Ensure correct units are assigned – Set periods (if not done in RT) – Setup report preferences – If >12 units download data ONLY first then “Build Report” • Demo Files – AFL files from 7th and 14th April Refer to application notes/material:
• Basic parameter sets to begin include:
– – – – – Odometer Player Load Player Load/Meter (good metric for American Football) Max Velocity (may need to change units in settings tab) Speed Zone (distance / distance %) – can choose up to 8 but I recommend only settings 4 to start (ie: the same bands for realtime and download data). As per Gabbett et al. – IMA Accel/Decel/ Left & Right COD (High intensity)
Rugby
Running
Acc/Decel/turns
Impact Events (tackles)
40%
35%
25%
LIMITATIONS OF GPS
• Catapult not just a GPS device. • Work with many sports in completely non-GPS environments. • Running events are the least significant part of the puzzle.
• Hotkeys
Excel document: Module 1: Data Capture V1 & V2
DATA PROCESSING
Part 1: NEEDS ANALYSIS PARAMETERS BASIC PROGRAMMING/WORKFLOW ALGORITHM DEVELOPMENT
Football
Running Acc/Decell/Turns Impact Events (tackles)
10%
25%vide allencompassing analytics platform to measure everything. • GPS data is limited to running events. • Lots of other target sports involve large parts of non running activities
• Identify what we can do to assess this? – What do you feel the system will provide your program?
Parameters
• There are many parameters within the Sprint software. Selecting the right ones is important when showing a new or prospective client (see application note on „Parameters in Sprint’) • For beginner‟s/demo situations it‟s important to try and keep it simple but let the user know there is many more parameters to choose from.
Needs Analysis
• Evaluate the Sport • Identify what is important for the sport as a whole
• Identify what is important for the team within the sport – Which areas were you weak in last season? – Do you feel the athlete‟s were over-trained / undertrained at various times throughout pre-season or inseason? – Did you have a higher than normal soft tissue injury rate
• • • • Configure daily & longitudinal CTR templates in Sprint Catapult Download and Report Changing ‘Positions’ in Sprint Excel doc: Module 2: Data Processing
GPS AND TEAM SPORTS
• High-collision sports • Repeat High Intensity efforts • Tackles • Algorithm that combines data from 11 sensors to count and describe each tackle
GPS doesn’t measure everything
• High Collision Sports
• Quantifying the nonrunning based components: – RHIE – Tackles
• Valid
(Gabbett, Jenkins &
Abernethy, 2010) & Reliable (Boyd, Ball & Aughey, 2011)
RUNNING THE SYSTEM
SPRINT SOFTWARE
OPTIMEYE S5 UNITS
DATA CAPTURE
Part 1:
• Garments/Pouches/Pockets • Receiver & Tripod • MCC/Cradle
• Optimeye
• Sprint Software
DATA CAPTURE
Part 2:
• Training/Game/Testing Environment • Troubleshooting • Logistics • Firmware • Computer
• Internet
• Field/Environment • Player
• Staff
Basketball
Running
Acc/Decel/Turns Impacts Jumps
15% 10%
20%
55%
INERTIAL MEASUREMENT ANALYSIS (IMA)
• Quantification of micromovements. • Algorithm that uses raw data from accelerometers, gyrosc opes and magnetometers. • Advanced Kalman filtering techniques. • Complex pattern recognition that quantifies explosive movements.
• Moves beyond just GPS • Combination of inertial sensor data and GPS • Creates movement signatures to automatically detect and quantify performance. • Application for both GPS & non-GPS environments.