3. Sportscotland Institute of Sport
• Sportscotland
– Government agency for sport
– “world class sporting system for all”
– 3 directorate strands:
• Sport development
• Performance
• Corporate services
• Institute of sport
– Provide high performance expertise to sport and athletes in
Scotland
– Support athletes to compete and perform on the world stage
– Regional centres across Scotland
5. Aims of todays session
• Provide case studies of applied sports science support to
team sports
– Professional football
– International Hockey
– Paralympic team sports
– Using interventions from other sports to inform practice
• Understand background, rational and context for support
provision
• Questions and discussion
7. Practicalities for support provision
• Club/team
– Aspirations
– Level – full time/part time
• Managers & coaches
– Previous experience/education of support
– Style of play & tactics
• Players
– Stage of career
– Motivation to embrace support/improve
• Time
– With players
– Stage of season
• Resources
– Finances
– Equipment
8. 8
Seasonal Variation in Fitness
• Season 2005/2006
– Under 21, Under 19, Under 17
• Reserve fixtures closely mirrored 1st XI
• Under 19 and Under 17 fixture congestion in
final 3rd of season
– Natal Rebelo & Soares (1995) indicated the
importance of matches in improving/maintaining
aerobic capacity
9. 9
Seasonal Variation
• Few top level teams use periodical lab assessments
• Anecdotal theory that fitness decreases in final half of season
• Casajus (2001)
– 15 La Liga players (Values are means + SD)
– No significant differences (p<0.05) and parameters apparently maintained
– Heller et al. (1992) VO2max remained unchanged (60.1 + 2.8 and 59.3 + 3.1
ml.kg-1.min-1)
– Fitness decrement over final half of season?
Test 1 (Sept) Test 2 (Feb)
VO2max (ml.kg.min-1
) 65.5+8.0 66.4+7.6
Hrmax (bpm) 185+4.0 185+7.0
CMJ (cm) 41.4+2.7 40.8+2.7
CMJ (with arm swing; cm) 47.8+2.9 46.7+2.8
10. 10
Training
• Aerobic Training
– Helgerud et el. (2001)
• 4x4 mins interval running @ 90 – 95% Hrmax
• 3 min active recovery 60 – 70% Hrmax
• 10 – 30% increase in VO2max over 8 weeks
• No changes on measures of speed, power or strength
• Strength Training
– Hoff & Helgerud (2002)
• 85% 1RM
• 5 reps x 4 sets
• Increases Squat over 8 week period (161kg – 215kg)
• Improved speed and jumps
• Improved running economy
11. 11
Methods
• Subjects
– 33 players – Under 17, Under 19 and under 21 squads
– 19 completed all tests (U17 = 5; U19 = 6; U21 = 8)
• Informed consent & ethics
• Procedure
– 3 times throughout the season
• Day 1
– Jump tests
– Sprint test
– Submax (9kmh at 5%) and max aerobic test (VO2max)
• Day 2
– One repetition maximum (1RM)
12. 12
Summary
• VO2max scores among the highest reported for
professional footballers after preseason
– Maintained throughout season
• General maintenance of sprint, jump and aerobic
capacities
• Decrease in submax VO2
– negative correlation between squat strength and economy
(r= -0.59)
• Poor relationship seen between leg strength markers
of power.
15. Role of the Sports Scientist
Introduce/Review
Structure
Innovation &
Research
Physiological
Testing
On field
conditioning
Strength &
Power
Recovery
Prehab
Nutrition
Hydration
Monitoring
End
Stage
Rehab
Sports
Scientist
16. 16
Season 1 – Strategic plan
Review
Introduce
Change
Review existing
Programmes
First impressions!
Quick & tangible results
Get to know team
Influence
Build relationships
Reflect & evaluate. Review current
research, experience & innovate
Subjective & objective. Review
current research & experience
Start Pre Season
End Season
Review
Introduce
Change
Review existing
Programmes
First impressions!
Quick & tangible results
Get to know team
17. 17
Educational intervention
Chievo Verona F.C,
Italy
Hot/dry (20–25°C)
7 days
Monitoring
Osmocheck
Body weight
monitoring
Powerade & water
0
1
2
3
4
5
6
7
8
9
10
11
1 2 3 4 5 6 7
Day
Number
of
samples
Dehydrated Euhydrated Well hydrated hyperhydrated
18. 18
Conditioning for Football
Perform and last 90 minutes
Perform repeated high
intensity work
Ability to sprint, jump, kick
and tackle
Perform movements/changes
of direction at speed
Shield and protect the ball
Ability to stay injury free &
healthy all season…….
19. 19
Testing and monitoring
No testing completed at start of pre season
Heart rate monitors worn in training on an
ad hoc basis
Needed quantitative evidence!
Average VO2max (ml.kg.min-1) at start season
St Mirren First Team Squad Celtic Reserve Squad (2005/2006) La Liga Squad (2001)
Defenders 64.1 69.4
Midfielders 67.2 70.6
Attackers 61 70.7
Squad 63.9 70.4 65.0
21. 21
Intervention
Helgerud et el. (2001)
4x4 mins interval running @ 90 – 95% Hrmax
10 – 30% increase in VO2max (8 weeks)
McMillan et el. (2005)
Soccer specific running circuit
Mean VO2max 63.2 – 69.8ml.kg.min-1 (10weeks)
South Korea world cup preparation (Verheijen, 2007)
Used small sided games as interval training
Semi finalists of World Cup Finals
Personal experience
22. Small Sided Games (September 2008)
50
55
60
65
70
75
80
85
90
95
100
5x10 10x15 15x20 20x25 25x30 30x35 35x40
Pitch Dimensions
Average
heart
rate
(%
of
maximum)
1 v 1 2 v 2 3 v 3 4 v 4 5 v 5
26. 26
Retest
Average VO2max (ml.kg.min-1)
Start Season Mid Season
Percentage
increase
Number
tested
Defenders 64.1 67.2 4.8% 6
Midfielders 67.2 69.8 3.9% 7
Attackers 61 64.1 5.0% 4
Squad 63.9 67.1 5.0% 17
27. The importance of recovery
Rule changes to the game
Increasing number of games across the season
Risk of overloading/overuse injuries
Several facets to recovery and approaches to
this vary e.g.
Muscle glycogen stores are usually depleted up to 75
per cent during a match (Bangsbo, 2000)
Mechanical load of intermittent, high intensity field
sports
Psychological
27
30. Recovery strategy protocols
Post match active recovery
Cold water immersion
Nutrition to repair and refuel
CHO - 1 – 1.2g/kg/hr (Coutts, 2007)
food or fluid asap
Supplementation
Creatine (Cooke et al., 2009)
Fluid to rehydrate
fluid losses during match play are usually between 600–1400
mL/hr (Broad et al. 1996)
Compression garments
Sleep (Leader et al., 2012)
30
31. Evening training and games
Anecdotally players/athletes struggle
with sleep after performing in training
and games
Fight/flight response
Muscle damage/pain
Supplements
However, recent study in elite youth
footballers does not show this (Robey
et al., 2014)
31
36. 36
Relative On Field Success
Avoided League relegation
11th place (2008/2009)
10th place (2009/2010)
Scottish cup Semi finalists (2008/2009)
CIS (League) Cup Runners up (2009/2010)
Questions?
37. International Hockey
• Mens National team (Post Delhi CWG)
– Annual planning & periodisation
– Understanding demands of international match play
– Fitness Testing
– Conditioning prescription & monitoring
– Wellbeing monitoring
• Womens National team
– Specific training intervention
38. Understanding International hockey
• Catapult GPS system
• What parameters are KPI’s?
• Normative data
No of
sprints (>18
km/hr)
% of high
intensity
running (%
time spent
above 18kmh)
Total Distance
Covered
Intensity
(meters per
minute)
Australian National Team
Standards 18 - 20% 150
Averages from NZ national
team (Lythe, 2006)
22
(>20km/hr)
7320
39. Overview of matchplay (m/min)
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
01/06/2011 04/08/2012 05/08/2012 06/05/2013 07/05/2013 09/05/2013 11/05/2013 12/05/2013 15/06/2013 22/06/2013 23/06/2013
England Austria Poland Canada Belgium Poland France Portugal Wales England England
40. Overview of matchplay (m/min)
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
01/06/2011 04/08/2012 05/08/2012 06/05/2013 07/05/2013 09/05/2013 11/05/2013 12/05/2013 15/06/2013 22/06/2013 23/06/2013 26/07/2013
England Austria Poland Canada Belgium Poland France Portugal Wales England England Spain
42. Planning
• Many challenges
– Club calendar
dominates calendar
year
– Majority of players
compete in foreign
leagues
• Differences in styles
and intensities
– Financial constraints
43. National programme - monitoring
• L,m,h,vh training weeks
– Build 3 weeks: 1 week recovery
• TRIMP monitoring (Foster et al., 2001)
– Training load, monotony & strain calculated from RPE and
training time
46. Fitness testing
• Used to identify players individual strengths and
weaknesses
• Conditioning prescribed based on test deficiencies
• Tests:
– 30m max sprints (0m, 5m, 10, 30m)
– Repeated sprint ability - 6 x 30m on 25s
– Aerobic marker – MSFT or 30:15
48. Training prescription
SPRINT (0-30m) SPEED ENDURANCE BLEEP
Alan Forsyth no previous data for this season Excellent - improved target Excellent - improved target Excellent - improved target
Chris Grassick Excellent - improved target Excellent - improved target Hit target but decreased performance Good - maintained target
Chris Nelson Regressing and below target Improving but still below target Regressing and below target Hit target but decreased performance
Dan Coultas Improving but still below target
David Forrester Excellent - improved target Maintained below target
David Forsyth Regressing and below target Regressing and below target
Fergus Dunn Excellent - improved target Excellent - improved target Excellent - improved target Poor - Area to improve
Gareth Hall Improving but still below target Regressing and below target
Unnacceptable level of fitness for position and training
history
Gavin Byers Excellent - improved target Excellent - improved target Improving but still below target no previous data for this season
Gordon McIntyre Improving but still below target
Ian Moodie Excellent - improved target
Kenny Bain Improving but still below target Improving but still below target Excellent - improved target
Michael Bremner Excellent - improved target Excellent - improved target Excellent - improved target
Niall Stott
Phil Carr Regressing and below target
Wei Adams Regressing and below target Improving but still below target Excellent - improved target
William Marshall Improving but still below target Improving but still below target Excellent - improved target
no previous data for this season
no previous data for this season
no previous data for this season
50. Aerobic/RSA session
• Adapted from Edge &
Bishop (2006)
• Utilised in conditioning
practices and individual
non-supervised running
• Similar to 4 x 4min
interval utilised previously
in football
52. Considerations
• Chronic training load
– Normally considered over 4 weeks (28days)
• Acute training load
– Last 7 days
• Ratio often normalised as z-score to show relative
changes
53. Training Stress Balance (TSB)
• Rogalski, B., Dawson, B., Heasman, J., and Gabbett,
T.J. (2013). Training and game loads and injury risk in elite
Australian footballers.Journal of Science and Medicine in
Sport, 16:499-503.
• Gabbett, T.J. and Ullah, S. (2012). Relationship between
running loads and soft-tissue injury in elite team sport
athletes. Journal of Strength and Conditioning
Research,26:953-960.
• Gabbett, T.J. and Jenkins, D.G. (2011). Relationship
between training load and injury in professional rugby league
players. Journal of Science and Medicine in Sport,14:204-
209.
55. Monitoring training load to minimise
injury risk
• Establish moderate chronic training loads and ensure these
are maintained
• Be aware that injuries can be latent following increased
training loads
• Minimise large week-to-week fluctuations
• Establish a floor and ceiling of safety
• Ensure training loads are appropriate for your athlete and
their current situation
56. Summary
• Rudimental level of support can achieve
success:
– Understand demands of sport
– Train toward identified key parameters
– Plan and monitor training
• Why, what, how, when
– Evaluate progress
– Plan and monitor training
• Why, what, how, when
57. Womens hockey – pushing the boundaries?
• Use of hypoxic training becoming more prevalent in team sports (BJSM
consensus statement, 2013)
– Effects of Hyperoxic training are less clear
• Reduced blood lactate concentrations have been observed when inhaling
hyperoxic gas of varying concentrations (FiO2 = 30 % to 100%) after
exercise at 70 % VO2max and at 130 % of the anaerobic threshold.(Maeda
& Yasukouchi, 1997)
• Kayakers breathing hyperoxic (100 % FiO2) air substantially improved the
recovery time of SpO2 but did not change performance measures, RPE or
blood lactate during 3-min maximal aerobic intervals compared with
normoxic recovery. (Peeling & Andersson, 2011)
• Cyclists performing 5 x 30 s sprints whilst breathing hyperoxic air during a 6
min recovery period found an increased partial pressure of oxygen, however
there was no effect on mean or peak power (Sperlich et al., 2012)
58. Novel intervention - Hyperoxic Training in Elite Female Hockey Athletes
• High-intensity, intermittent exercise causes a reduction in the
oxygen saturation of haemoglobin and an increase in tissue hypoxia
• An attenuation of this oxygen de-saturation during exercise has
been shown to increase the average power output, and to reduce
the perceptual effort of work registered by the athlete.
• Hyperoxia may enhance the recovery rate of haemoglobin saturation
levels and or control the increase in [H+]. There is evidence to
suggest that inhaling a hyperoxic air mixture prior to exercise more
than doubles whole body oxygenation.
• This may lead to increased O2 delivery to muscle cells and
increased diffusion of O2 into the mitochondria
59. Methods
• 15 female international hockey players
• 3 groups undertook a 6 week intervention
– HXA – received 100% O2 during rest periods
– NXA – received a sham treatment of compressed air
– Control group received no treatment of supervision
• All subjects undertook training based around a work rest ratio of 2:1.
– This equated to 120 s work periods interspersed with 60 s rest.
• Intensity was set at 85 % of MAS as determined by the 30-15 test.
• The session consisted of 7-12 reps running on a tartan running track. Each
session was split into sets of 3-4 reps of 120 s:60 s work:rest with 2 min rest
between sets
• During the 2 min recovery periods subjects inhaled the appropriate gas from a
covered cylinder via a mask that covered the nose and mouth
• LA, GPS, RPE, Hr measured through out.
64. Supervised v non supervised
• A major difference between groups was that HXA and NXA
were supervised during training and CTR unsupervised.
• There were small effects of training on MAS in the supervised
group and to a lesser extent in the CTR group
• Change in MAS was also greater in the supervised group
(supervised = 1.4% and CTR = 1.1%).
• Based on the SWC threshold of 0.5% we can conclude that
supervised training led to greater gains in MAS compared to
CTR.
71. CP Football - Cooling interventions during simulated matchplay
36.50
37.00
37.50
38.00
38.50
39.00
39.50
40.00
40.50
41.00
Pre-w arm-up Post w arm-up End 1st half End half-time
cooling
Mid 2nd half End 2nd half End 2nd
cooling period
Core
Temperature
(
0
C)
Athlete 1 (Fanning/Hand Immersion) Athlete 2 (Hand immersion/Fanning)
72. Jet Lag – The Problem
• Macau
– 12 hour flight
– 7hr time difference
– Eastward travel
• Body adjusts more efficiently to day
lengthening than day shortening
• Potential impact on athlete wellbeing
and ability to train optimally
• BPA guidelines
– Manipulate times when individuals
seek/avoid bright light
– Avoid high intensity training early in the
camp, especially in the afternoon.
73. How much jet-lag do you have?
0
1
2
3
4
5
6
7
8
9
10
1 2 3 4 5 6 7
Day
Perceived
jet-lag
Morning Lunchtime Evening
n = 103
74. • BPA guidelines can minimise jet lag
• Educated sports on time to acclimatise to the new time zone
– Training schedules during camp
– Holding camp 2008
• Identified athletes with prolonged response to long haul travel
– Manipulate individual training at holding camp 2008
– Greater intervention required pre-travel
– Sleeping/relaxation techniques (Psychologist)
76. Individual athlete approach for team sports
• Can we learn lessons from other sports?
• Can we really individualise training schedules? If so,
how?
• 2 examples to consider from other sports:
– Wellbeing & Sleep
– Training monitoring to predict injury risk
77. Sleep physiology
• Not a resting state of the brain
• Active dynamic cycling
through multiple sleep specific
states
• NREM & REM
• 2 main functions:
– Recovery from previous
wakefulness
– Prepare for functioning in
subsequent wake period
• Direct Link to performance??
78.
79. Injuries & illness
• Adolescent athletes who sleep on average <8hrs per night are 1.7 times
more likely to have an injury compared to athletes who slept >8hrs (n = 112,
mean age = 15, Milewski et al, 2014)
• Similar dose-response relationship between sleep and immune system
80. Dr Charles Samuels (BJSM, November 2014)
“If your athletes go to bed and fall asleep within 30 minutes,
sleep through the night with brief awakenings, feel
refreshed within 60 minutes of waking most days (5/7 days
per week) then congratulations: your athletes are normal
sleepers ”
81. Dr Charles Samuels (BJSM, November 2014)
“If your athletes go to bed and fall asleep within 30 minutes,
sleep through the night with brief awakenings, feel
refreshed within 60 minutes of waking most days (5/7 days
per week) then congratulations: your athletes are normal
sleepers ”
82. Dr Charles Samuels (BJSM, November 2014)
“If your athletes go to bed and fall asleep within 30 minutes,
sleep through the night with brief awakenings, feel
refreshed within 60 minutes of waking most days (5/7 days
per week) then congratulations: your athletes are normal
sleepers ”
83. Dr Charles Samuels (BJSM, November 2014)
“If your athletes go to bed and fall asleep within 30 minutes,
sleep through the night with brief awakenings, feel
refreshed within 60 minutes of waking most days (5/7 days
per week) then congratulations: your athletes are normal
sleepers ”
84. Dr Charles Samuels (BJSM, November 2014)
“If your athletes go to bed and fall asleep within 30 minutes,
sleep through the night with brief awakenings, feel
refreshed within 60 minutes of waking most days (5/7 days
per week) then congratulations: your athletes are normal
sleepers ”
Note: No mention of sleep time?!
85. Quantifying sleep
• 3 main methods to quantify sleep
– Polysomnography (PSG)
– Actigraphy
– Self reported
• Markers consider:
– Sleep quality
– Sleep quantity
– Routine – bed, sleep (mid-sleep) and wake times
86. PSG
• Gold standard measurement
• Conducted in a sleep-lab for 2 nights
• EEG measures change in the electric
potential of the scalp as a result of
brain activity
• EOG is a measure of corneo-retinal
standing potential - measures REM
sleep
• EMG is a measure of electrical activity
produced be skeletal muscles
• HR/HRV
87. Self-reported sleep
• Included in morning monitoring or training diaries
– Currently using smartabase app
• Pittsburgh Sleep Quality Index (PSQI) commonly used to
identify sleeping habits
– Can be used monthly as a reflective tool
• Chronotype
88. Actigraphy
• Digital tri-axial accelerometer
• Small, low energy, light-weight, waterproof device with
direct USB connected.
• Activity plots (with specialised software) quantify activity
89. Actigraphy - Quality & Quantity
• Quantity
– Study in USA (2005) average self reported sleep 6.8 – 7.4hrs
– In athletic population:
Previous research in other sports (Leeder et al., 2012)
non-athletes Canoeists Divers Rowers Speed Skaters
Time in bed 08:07 08:32 08:46 07:46 09:13
Actual sleep time 07:11 06:58 07:05 06:25 07:06
90. Actigraphy v self reported sleep
• Significant differences
between self reported sleep
and actigraphy predicted
sleep
• Can be as much as 1 - 1.5
hours
91. Actigraphy - Quality & Quantity
• Ranges:
– Efficiency 80% or more
– Latency less than 30 minutes
– Frag Index less than 40
Previous research in other sports (Leeder et al., 2012)
non-athletes Canoeists Divers Rowers Speed Skaters
Sleep efficiency (%) 88.7 81.8 80.9 82..5 77.2
Sleep latency 00:05 00:19 00:21 00:10 00:21
Mobile mins 45.4 75.6 96.5 77.9 97
Mobile time (%) 9.4 15.6 19.3 17.3 18.4
Fragmentation Index 29.8 31 39.3 35.6 37.3
92. Sleep Apps
What the experts say:
• ‘…such products had limited use beyond
"nagging" the user to go to bed earlier’
• ‘If you want to learn whether you sleep on
certain nights and not on others, then it
should be looked at as a form of harmless
entertainment,“ Siegel, UCLA Center for
Sleep Research (www.bbc.co.uk)
• +ve side: ‘Given the technology to properly
monitor their own sleep quality, consumers
can better understand the link between their
sleep and their health, and set goals for
improvement’
93. Gender Differences in Sleep Duration and Quality in National Level Swimmers
• Swimmers
• N = 10
• Wrist-Watch Actigraphy
• Sleep Parameters
94. Gender Differences in Sleep Duration and Quality in National Level Swimmers
N. Gibson and A. Sommerville
sportscotland institute of sport
1. INTRODUCTION
Sleep is an essential component of recovery for athletes due to its physiological and psychological restorative effects (Leeder et al., 2012). Reduced
sleep may compromise the quality of training sessions. Early morning training sessions, a practise common in swimming, may reduce the quality of
sleep (Sargent et al., 2014). Additionally, significant differences between sleep quality and quantity in male and female athletes have been
demonstrated. No data on sleep parameters has been published relating to gender differences specifically in swimmers.
2. AIM
• To quantify gender differences in sleep in National Level swimmers
regularly engaging in early morning training sessions.
3. METHODS
• Ten athletes (5 males; 5 females) were monitored continuously for 14
nights using wrist-watch Actigraphy (Motionwatch 8, CamNtech, UK)
• Overnight Sleep was analysed for a range of variables.
• For gender differences in all sleep parameters, an independent t –test
was used to compare means. Non-parametric data was compared using
a Wilcoxon test. Statistical significance was set at P < 0.05.
5. CONCLUSION
4. RESULTS
• There was no significant difference in Time in Bed between males and
females (08:33 ± 00:06h vs 08:04 ± 00:19h, P = 0.617), Actual Sleep Time
(06:08 ± 00:33 vs 06:54 ± 00:24, P = 0.112) or Sleep Percentage (73.51 ±
22.20% vs. 83.35 ± 4.98%, P = 0.349).
• Significant differences were noted in Sleep Efficiency, with females
having a greater efficiency than males (75.39 ± 3.67% vs. 81.18 ±
5.33%, P = 0.017), a lower Fragmentation Index (45.58 ± 6.32 vs. 32.81 ±
5.60, P = 0.010), reduced Sleep Latency (00:22 + 00:11h vs 00:09 +
00:10h, P = 0.046), and reduced Time awake (01:34 ± 00:07h vs 01:23 ±
00:05h, P = 0.043)
• National level female swimmers have an increased quality of sleep,
when compared to their male counterparts. This is in keeping with
previous research. The finding that males and females spend a similar
amount of time in bed, and achieve a similar amount of sleep hours,
but have a reduced quality of sleep indicates that males have poorer
sleep efficiency. Future research could focus upon practical
solutions and interventions to improve sleep efficiency in sports
where sleep may be compromised through early morning training.
Time in Bed Actual
Sleep Time
Sleep
Latency
Time Awake
0:00
1:12
2:24
3:36
4:48
6:00
7:12
8:24
Time
(hh:mm)
Males
Females
*
*
0
20
40
60
80
100
Sleep Percentage
(%)
Sleep Efficicency
(%)
Fragmentation
Index
Males
Females
*
*
Figure 1 illustrates the difference in sleep quantity between genders (*
indicates significant difference)
Figure 2 illustrates the difference in sleep quality between genders (*
indicates significant difference)
References: Leeder J., Glaister M., Pizzoferro K., Dawson J., Pedlar C. (2012). Sleep Duration and Quality in Elite
Athletes Measured using Wristwatch Actigraphy. Journal of Sport Sciences. 30 (6) 541 – 545. Sargent C., Halson S.,
Roach G. D. (2014). Sleep or Swim? Early-Morning Training Severly Restricts the Amount of Sleep Obtained by Elite
Swimmers. European Journal of Sports Sciences. 14 (1) S310-5.
95. Pre competition sleep (Erlacher et al., 2011)
• 632 German athletes
• Self reported questionnaire
• 65.8% reported worse sleep at least once prior to
competition
• Main issue reported was problems falling asleep (long
latency)
• Increased feeling of daytime sleepiness
96. Pre competition sleep (Juliff et al., 2015)
• 238 AIS athletes
• Competitive Sports and Sleep Questionnaire
• 64% of athletes experienced sleep problems prior to a
major competitive event
• Internal factors were reported as being the main reason
for this
– Nervousness
– Thoughts about competition
97. Pre competition sleep (Juliff et al., 2015)
• 42% reported increased daytime sleepiness as a direct
result of poor sleep the previous night
• 14% believed that reduced sleep DIRECTLY resulted in
worse performance in competition
• No significant differences between team or individual
sports
98. Applying this science
• Assuming same figures applied to professional football
squad of 25 players:
– Approx. 15 players experienced disrupted sleep prior to
competition
– Approx. 4 players performance was impaired by this disrupted
sleep
• How many players had developed sleep strategies to
combat sleep disruption as a result of stress???
99. Case study 1
• Athlete reported no sleep prior to early morning training
session
• Returned from Texas (-6hrs GMT) in previous 4 days
• Athlete had trouble sleeping at night prior to travelling
– Was sleeping more during day than at night
• ‘Hardest part of swimming is going to bed early’
• Not uncommon:
– 59% of team sports reported having no strategy to overcome poor
sleep
– 82% reported difficulty falling asleep before competition (Juliff et al., 2014)
100. Case Study 1
• Self reported chronotype suggested ‘owl’ tendencies but
not extreme
• 8 week monitoring period pre CWG trails
• Intervention based around sleep hygiene and
performance behaviours
101. Aims – Improve Sleep Hygiene
• Break cycle of day sleep being more than night sleep
• Consistent bedtime for next 9 weeks - ideally no later than 10 -
10:30pm (even in rest days)
• Stop playing computer games or watching TV at least half hour
before bed
• Establish a pre bed routine
• Turn phone brightness down low before bed and turn off completely
in bed
• Duration of morning sleep dependant on time of session but have
consistent wake up time
• Download data from watch every Tuesday and Friday
102. Monday Tuesday Wednesday Thursday Friday Saturday Sunday
04:00 04:00 04:00 04:00 04:00 04:00 04:00
05:00 05:00 05:00 05:00 05:00 05:00 05:00
06:00 06:00 06:00 06:00 06:00 06:00 06:00
07:00 07:00 07:00 07:00 07:00 07:00 07:00
08:00 08:00 08:00 08:00 08:00 08:00 08:00
Get up
09:00 09:00 09:00 09:00 09:00 09:00 09:00
10:00 10:00 10:00 10:00 10:00 10:00 10:00
11:00 11:00 SLEEP 11:00 11:00 SLEEP 11:00 11:00 11:00
12:00 12:00 12:00 12:00 12:00 12:00 12:00
13:00 13:00 13:00 13:00 13:00 13:00 13:00
14:00 14:00 14:00 14:00 14:00 14:00 14:00
15:00 15:00 15:00 15:00 15:00 15:00 15:00
16:00 16:00 16:00 16:00 16:00 16:00 16:00
17:00 17:00 17:00 17:00 17:00 17:00 17:00
18:00 18:00 18:00 18:00 18:00 18:00 18:00
19:00 19:00 19:00 19:00 19:00 19:00 19:00
20:00 20:00 20:00 20:00 20:00 20:00 20:00
21:00 21:00 21:00 21:00 21:00 21:00 21:00
22:00 22:00 22:00 22:00 22:00 22:00 22:00
BED BED BED BED BED BED BED
23:00 23:00 23:00 23:00 23:00 23:00 23:00
NO TV OR GAMING NO TV OR GAMING
Land Session
Swim
Land Session
Swim
NO TV OR GAMING NO TV OR GAMING NO TV OR GAMING NO TV OR GAMING NO TV OR GAMING
Gym
Physio Yoga
Swim Swim Swim
SLEEP SLEEP
Swim
Swim
Swim
Swim Swim
103.
104.
105.
106.
107.
108. Aims of todays session
• Provide case studies of applied sports science support to
team sports
– Professional football
– International Hockey
– Paralympic team sports
– Using interventions from other sports to inform practice in team
sports
• Understand background, rational and context for support
provision
• Questions and discussion