2/20/2016 1 Developing Athlete Monitoring Systems: Theoretical basis and practical applications Professor Aaron Coutts Ph.D. University of Technology Sydney (UTS), Sydney, AUSTRALIA @aaronjcoutts Overview Theoretical basis monitoring training in athletes Markers of fatigue and recovery Model for monitoring training Examine simple tools for monitoring: Training load Fitness Fatigue Model for integrating into sport Sport Science in Daily Practices: imbedded evidence‐based systems CK Strength/Power DXA Nutrition Wizard Variables Physio screening Wizard Variables Kicking coding Recruiting 5‐5’ Session / Match Summary Medical Database Performance Data Drills Database Custom Reports Rexy’s App Speed/Agility TRAINING & GAME LOAD FATIGUE & WELLBEING FITNESS PERFORMANCE & INJURY Training Theory 101 Time Capacity Training Adaptation Optimum time between bouts Training Overload & Adaptation Fatigue Fitness Time Training Effect Training Dose‐Response: Fundamentals of Fatigue and Recovery PERFORMANCE Performance = Fitness – Fatigue [Banister et al., 1975, Busso et al., 2003]
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HR and Blood Lactate Correlates of RPE during Football:
851 sessions of soccer small‐sided games (4 x 4 min bouts)
Heart Rate and Blood Lactate Measures during bouts
RESULTS
43.1% of the adjusted variance in RPE could be explained by HR alone.
The addition of [BLa‐] data allowed for 57.8% of the adjusted variance in RPE to
be predicted
These results suggest session‐RPE a better indicator of global exercise intensity
Coutts et al., (2009) JSAMS.
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QuantifyingExternalLoads:Training&MatchPlay
Commercial Products Automated Camera Systems GPS Accelerometers Gyroscopes, magnetometers…. Metabolic power estimations Isoinertial movement analysis ……
QuantifyingExternalTrainingLoad
SummaryTrainingLoads
RPE, heart rate and microtechnology (GPS and accelerometers) used widely in practice
Understand noise in your load measurements
Ensure the method is valid and reliable!
Monitor training response using internal training load
MeasuringFitness&Fatigue
ModelforMonitoringTraining
RESPONSE
Feedback Loop
TRAINING PLAN DOSE
Fatigue
Fitness
PERFORMANCE
QuantifyingFitnessSubmaximalHeartRateResponses
4 min submaximal run @ 14 km/h
HRex
HRR
HRVresponse
HRex – Fitness changes
HRrecovery – Tolerance to training load
HRV – Fatigue
Buchheit et al (2011) EJAP
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MethodsforQuantifying‘Fatigue’
Talk to athletes: ‘Are you tired / fatigue / sore etc….?’
Psychometric questionnaires DALDA [Rushall, 1991]
RESTQ‐Sport [Kellmann & Kallus, 2001]
POMS [McNair et al., 1971]
BRUMS [Terry et al 1999]
Wellness questionnaires [Hooper et al., 1995]
Training distress score [Main et al., 2009]
Blood measures: endocrine, muscle damage etc…?
Borrensen & Lambert (2009) IJSSC
WellnessQuestionnaires
2
2
2.5
3
2
11.5
MuscleDamage
Time course in recovery from matches Relationships between measures
SeparatingtheSignalfromtheNoise
Need to understand “normal” variations in the measures
within‐athlete, day‐to‐day variability
Understanding Acute (recent) and Chronic Changes (long‐term) within Individuals & Team (spike risks)
Common Approaches:
Understand the Smallest Worthwhile Changes in each test
Use within individual Z‐scores analysis
InterpretingChangesinVariables
Biomarkers & Performance measures Assess clinical likelihoods of change
75% Chance of a ‘Real Change’: Week‐to‐Week variation + SWC [0.2 x test‐retest CV]
Subjective markers Convert to Z‐scores (standard difference scores)
Individual acute response: (Current score‐baseline)/SD of individuals baseline
Individual chronic response: (4 week rolling average ‐ baseline)/SD of individual baseline
AnalysisofMonitoringData
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Fundamentals of a training monitoring system:
i. based on a theoretical framework;
ii. consistently & easily to implement;
iii. not easily manipulated;
iv. not too demanding for athletes;
v. affordable; and,
vi. analysed thoroughly
Summary
MAKINGAMODELWORK:
1.PlanningandImplementingLoads
PlanningLoads
1. Provide loading guidelines for week (intended)
a) Account for chronic loadings and acute spikes
2. Coach chooses drill according to tactical requirements / goals
a) Check if meets intended technical /tactical goals
b) Determine projected loading to meet periodisation goals/rules:• Training variation (monotony)
• Awareness of within‐week spikes (accelerations, high speeds and legs‐legs)
• Recovery after previous and before next match (inseason)
3. Modify individuals to meet fitness / medical / physiotherapy / wellness goalsa) Plan additional running or strength and conditioning
b) Modify drills deemed to be of risk (screening)
4. Compare actual loads to predicted loads
Tactical Goals
Physical LoadingLoad Constraints (GOAL ±2SD)
Running Loads Total distance High Speed Running Sprint load
Global Load sRPE
WEEK PLAN
G +1 G +2 G +1 G ‐2 G ‐1 G
Proportion planned load over the week
Adjust daily based on: Wellness (soreness,
fatigue) Medical screening
(squeeze, lunge) Collective feedback
(coach & fitness/medical)
PhysicalLoadingControlModel
ModelIntendedLoads
Coutts et al (2011) ECSS.
0.0
2.0
4.0
6.0
8.0
10.0
ses
sio
n-R
PE
(C
R-1
0)
Very Hard
Hard
Moderate
0.0
0.6
1.2
1.8
2.4
3.0
Kic
ks
(n
/min
)
15
18
21
24
27
30
Pe
ak
Sp
ee
d (
km
/h)
0
15
30
45
60
HS
R (
m/m
in)
0
50
100
150
200
Sp
ee
d (
m/m
in)
Ball Movement Game SenseGame Sense (Moderate)Line Specific Handball SSGs Kicking SSGs Skill Acquisition Tackling / Combat0.0
5.0
10.0
15.0
20.0
25.0
Drill Name
Tim
e (
min
)
sRPE
KickingRate
PeakSpeed
HSR
Speed
Time
AssessingTrainingDrillDemands
Stoppage
Motion
Crush
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SelectingTrainingDrillsToMeetTactical&LoadGoals
Stoppage
Motion
Crush
We have ball
Ball in dispute
Opponent has ball
DrillIntensity: LowModerate
High
TacticalGoal:
Live GPS Data Kicking Load Data
Cumulative Projected vs. ActualLoad Data
Cumulative Proj vs. Actual GPS & Kicking Data
Training Drills
Training Load Data
TrainingLoad– InjuryRelationships
Colby et al (2014) JSCR, Rogalski et al (2013) JSAMS, Blanch & Gabbett (2015) BJSM
UnderstandInjuryRiskLoadThresholds
Higher chronic loads associated with increased risk: 3‐wk cumulative distance and s‐RPE load associated with increased
injury risk
Lower chronic loads associated with increased risk
Load ‘spikes’ associated with injury risk. acute:chronic load ratio: = previous week last 4 week load