2/29/2016
Tennis Science 2016What you need to know
to keep your players on
the courtImplications and
implementations
W. Ben Kibler, MD
Medical director
• Serve volume- ? Concern
• The shoulder’s reaction to
tennis play
• Relationship- tennis
mechanics to performance
and injury risk
• Effective biomechanically
based serve analysis
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HANAVAN MODEL
1
BODY AS
A SYSTEM
OF LINKS
(SEGMENTS)
2
6
7
3
8
9
4
10
11
5
12 13
14
15
Adapted from Hanavan, EP. Mathematical Model
of the Human Body. Wright-Patterson Air Force
Base, Ohio, 1964, AMRL-TR, 64-102.
THE KINETIC CHAIN
Wrist
Elbow
F
O
Shoulder
R
Trunk
and Back
C
E
Legs
0
TIME
Adapted From Groppel
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Kinetic Chain
•
•
•
•
•
•
•
Transfer of Forces
Ground – Foot
Up Leg  Knee
 Hip
 Back
 Scapula
 Arm
 Ball/ Racquet
Serve volume
Good, bad, or who
cares
USTA serve volume
project
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Serve volume project
• Male, female professionals
• High ranked/skilled juniors
• Tournament match play
– Hard court surface
– US Open- 2013, 2014
– Orange Bowl 2014
Serve volume project
• Umpire, computer records
• Males, females
• Professional- ranking
• Juniors- age groups
• All serves- 1st, 2nd, per set,
per match
Professionals- match
Rank
1- 50
51- 200
Male Female
152
95
158
97
No diff- ranking
Sig diff- males> females
Males- best of 5, females- best of 3
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Professionals- set
Rank
Male 1/2 Female 1/2
1- 50
30/12
29/11
51- 200
31/13
30/12
Slight sig diff- males> females
Rank- sig diff- lower> higher
Professionals- set
• Small difference in absolute
number of serves/set
• Larger difference in total
number of serves when
performed over entire
season
Professionals
• “Dose” of serves per set- 43
• Average 55 matches, 138
sets per competitive year
• Low rank- ~ 6072 serves/yr
• High rank- ~ 5796 serves/yr
• Baseball- ~ 3614 pitches/yr
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Implications
• No known relation- injury,
performance
• However, this is a large load
on shoulder/kinetic chain
• Load may be managedpractices, matches
Implementation
• Can use “dose” as training/
conditioning assistance
• May use as guide- planning
play- “green(total serve
amount OK)/yellow(close to
high load)/red(high load- ?
modify playing/training)”
Juniors- match
Age
13- 15
16- 18
Males
98
93
Females
91
83
Sig diff- age- young> old
Sig diff- males> females
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Juniors- set
Age
Males 1/2 Females 1/2
13- 15 30/10
29/9
16- 18 30/10
28/9
No diff- age level
Sig diff- males> females
Juniors
• “Dose” of serves per set- 38
• Variable matches, sets
• 30- 80 matches, 60- 190 sets
• Frequently- high number
sets, matches- short time
• Serves- younger> older
Professional/juniors- set
Level
Pro
Junior
Male
43
40
Female
41
38
Sig diff- males> females- both pro
and junior
Sig diff- pro> juniors
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Implications
• We have a general idea of
the demands of the serve
• Potentially concerning due
to high amount in a season
• More thought to how much
of a load is imposed
Implementation
• Unit dose around 40+/- 5
serves per set- pros, juniors
• Use this number- planning
exposure- matches, practice
• Junior> pro- expect more
serves per set, match
Implementation
• Use dose as guide
– Training- correlate- match
– Conditioning
– Planning tournaments
– Green/yellow/red light as
guide for possible overload
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Implementation
• High volume- known riskmodify load- periodization
• Tournament, season plans3 months off per year
• Condition- serve efficiencymechanics, kinetic chain
Implementation
• Return to play protocol
• Based on anticipated load
• Return after injury
• Return after periodized rest
• Progressions- intensity,
strokes, volumes, games
Interval-Based Return to
Tennis Program
Contact: [email protected] for details
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Limitations
• No relation of this datainjury risk/prevention,
performance capability
• No data- total serve volumematch, practice
• No knowledge ideal program
Future directions
• Other surfaces
• Relation- injury risk
• Guidelines- green/yellow/red
zones of concern
• ?- feedback- doctors/PT/ATC,
coaches, players
The effect of an acute
episode of tennis play
on shoulder (GH)
range of motion
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Background
• GH ROM has large influence
on GH joint kinematics
– GIR, TROM > GER
• Increased translations
• Associated with increased
injury risk
Background
• ? Most important way to
measure GH ROM
– Static, dynamic
– ? Same number
– When in activities
– Number/change in number
Background
• Baseball
– GIRD, TROMD key
– GIR a dynamic number
– Pre/post acute throwing
– “Curve of change”- short
and medium term
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Baseball
2009-2010 Percent Change Throwing Arm N=92
ER
IR
TAM
Percent Change (%)
0.05
0
2.0%
1.9%
0.0%
Pre
1.8%
0.3%
Post
24h
1.6%
0.1%
1.1%
48h
72h
-5.2%
-0.05
-7.6%
-0.1
-14.5%
-0.15
-15.1%
-19.8%
-0.2
-0.25
Time Interval
Change in Measures Early to End of Season
Pitchers with 50+ innings
Early
15
12
Late
10.25
10
5
D egrees
0
-5
ER
IR
TAM
-3.25
-10
-15
-20
-25
-13.25
-15.25
-23.5
-30
Background
• Baseball
– GIRD > 18 deg, TROMD > 5
deg- significant risks
– Curve of change towards
significant risk
– Acute ROM change after
play
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Background
• Tennis
– Overhead motion
– Long term ROM changes
similar to baseball
– ? Short/medium term
changes- acute episodes
Background
• Shoulder range of motion
key element in tennis
performance, injury risk
• Required- max serve/stroke
• Key- shoulder/elbow injury
• ROM- insight- joint health
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Interactive Moments
• Forces from position/
motion of adjacent
segments
Equation for the proximal segment:
JMpp
+ (rpMpsinθp + lpMasinθp + ramasinθd)App
- (rpmpcosθp + lpmacosθp + ramacosθd)App
- (lp2md + rdlpmjcosØ) θp
- rdlpmasinØθp2
- (rdlpmdcosØ + lcd + rd2md) θd
+ rdlpmdsinØ θd2
- (rpmpcosθp + lpmdcosθp + rdmdcosθd)g
= (lcp + rp2mp) θ = lppθp
= Net moment on proximal segment
JF(aau)
JF(as)
IMp app
IMp app
IMp app
IMp app
IMp app
IMpg
JF(aau)
JMs
JF(as)
Putnam,C.A. Journal of Biomechanics 26: 125-135, 1993
“EPIDEMEOLOGY”
• Occurs early in intense
competitive athletes
Shoulder Flexiblity
Internal Rotation
56
60
Percent
50
34
40
30
20
20
20
12
12
28
18
10
0
Pre Stretching
14-15 Y.O.
Poor
Post Stretching
Fair
Good
Excellent
DIR
GIRD vs. PLAY
70
65
60
55
50
45
40
35
30
25
0
2
4
6
8
10
12
14
16
18
20
Years Played
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65
DOM. SHOULDER
I.R.
Degree
60
55
50
45
40
T0
T1
T2
Time
Control
Expermental
Tennis study
• WTA pros
• ROM before/after acute
serving episode, 24 hr
• Tournament play
• One examiner
• Reliability 0.88
60
*
Mean Glenohumeral Internal Rotation (°)
50
†
40
30
20
10
0
TP1
TP2
Time Point
TP3
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Tennis- group mean GIR
Change= (-) 4 deg
Baseball/
tennis
curve of
acute
change
Baseball/
tennissame slope
of change
29%
47%
Decreased GIR (≤MDC)
Increased GIR (≥MDC)
No changes in GIR (within MDC)
Mean Change: 11±7°
24%
Mean Change: 8±3°
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36%
50%
Decreased TROM (≤MDC)
Mean Change:14±7°
Increased TROM (≥MDC)
No changes in TROM (within MDC)
14%
Mean Change:17±9°
Implications
• Similar curve of ROM
changes after tennis play
• Significant % of playershigh amount of (-) change
• ? factors involved- intensity,
recent play, player factors
Implementation
• Evaluate ROM in all
competitive players
– Several times/year
– Curve of change
• Interventions in players with
high negative changes
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What is the relationship
between tennis
mechanics and injury
risk and performance
Tennis study
• 20 professional players
• Biomechanical analysis of
serves
• 2 year follow-up- injuries
• 9/no injury, 11/injury- 8
shoulder, 4 elbow, 2 wrist
Tennis study
• Injured players
– Dec ball velocity
– Inc shoulder ant force, inf
force, h-add torque
– Inc elbow medial force,
flexion torque
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Tennis study
• Injured players- later in:
– Pelvis rotation
– Trunk rotation
– Torso rotation
– Trunk flexion
– H-add/max ext rotation
Tennis study
• “Energy flow”- mechanical
energy generated, absorbed,
transferred in serve
• Inc “quality” (efficiency)
flow > inc ball velocity, dec
joint kinetics (less joint load)
“Quality” of energy flow
• Higher rates of energy
outputted from trunk > arm88% (non) vs. 71% (injured)
• Energy content dissipated
(absorbed) in shoulder/arminjured
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Tennis study
• Injured players
– Lower quality of flow
– Lower ball velocity
– Shoulder/arm- larger
amount energy produced,
higher rate of energy
absorbed- inc joint load
Implications
• Close relationship between
mechanics and its result
• Performance/injury risk- 2
sides of the same coin
• Knowledge/instruction in
most efficient mechanics
Implementation
• Know principles of efficient
mechanics- serve, strokes
• Effective stroke analysis
• Appropriate conditioning
• Periodization/prevention
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SCKY/WTA serve
analysis study
Serve analysis
• Relevant to serve mechanics
• Portable, on court
• Minimal equipment
• Easily used- coach, player
• Quick feedback
• Reliable between observers
SCKY/WTA Serve analysis
• Based on biomechanics
• Specific positions, motions“nodes”- efficient force
production, transfer
• Direct observation, video
• Specific visual criteria- yes/no
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Nodes- tennis serve
• Foot placement, usageup/back, forward
• Knee flexion to extension
• Hip/trunk counter rotation,
back hip tilting downwards,
front hip not leaning forward
Nodes- tennis serve
• Hip and trunk rotation
• Hip/trunk synchronycocking (“X” angle) and
acceleration
• Arm cocking- scapular
plane- “hyper, hypo”
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OBSERVATION
• Legs- knee bend,
hip counter
rotation away from
court, back hip
down
OBSERVATION
• No hip counter
rotation away
from court, no
downward tilt
“X” angle
• Hip/trunk separation angleBruce Elliott
• Optimum 30 degreestrunk/shoulders > hip
• Measured- max arm cocking
• Related- hyper/hypo cocking
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S
H
S
H
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Intra-rater reliability
node
1- foot
2- knee
3- hip 1
4- hip 2
5- hip 3
kappa
1.00- p
.75- s
.63- s
1.00- p
.83- a-p
agreement
13/13
12/13
12/13
13/13
12/13
Intra-rater reliability
node
kappa
6- hip/trunk 1.00- p
7- trunk
1.00- p
8- arm
.75- s
Push/pull
.58- m
Median
agreement
13/13
13/13
12/13
11/13
.83- s
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Inter-rater reliability
node
1- foot
2- knee
3- hip 1
4- hip 2
5- hip 3
kappa agreement
.77- s
25/28
.42- m
22/28
.83- a-p 27/28
1.00- p 28/28
.77- s
25/28
Inter-rater reliability
node
6- hip/trunk
7- trunk
8- arm
9- push/pull
Median
kappa agreement
.78-s
25/28
.47-m
23/28
.51-m
24/28
.86- a-p 27/28
.77- s
Implications
• Biomechanics based formathow forces are developed
• Highlights reasons for
observed poor mechanics
• Correlates- injury
• Basis for interventions
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Implementation
• Evaluations- video, on court
• Feedback- video, personal
• Intervention suggestions
– Clinical exam- deficits
– Conditioning
– Mechanics, training
Implementation- WTA
• Follow up- changes
• Results
– Positive player attitudes
– Requests for evaluation
– Difficult to change at this
current stage- minor
Implementation
• Wider group of coaches
• Training in use- classroom,
web based
• Wider group of playersjunior, recreational
• Effectiveness in teaching
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Conclusions
• Much new information
• Coaches- key in useconsistent application
• Injury risk reduction
• Performance improvement
• Better coaching, better play
THANK YOU
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