PhD presentation-Carlos Balsalobre

Carlos Balsalobre-Fernández

Monitorización y estudio de las relaciones entre la carga de entrenamiento, la producción de fuerza, la fatiga y el rendimiento en corredores de alto nivel

Monitoring and study of the relationships between training load, force production, fatigue and performance in high-level distance runners

Tesis Doctoral Internacional International PhD Thesis



Index1. Theoretical Background

2. Empirical work

1. Materials & Methods

2. Main results

1. Paper 1

2. Paper 2

3. Paper 3

3. Discussion & Conclusions

4. Limitations and prospectives

3. Practical applications


Theoretical background



ArtScience

Training



Art

ScienceTraining


Theoretical backgroundScientific approach

Collect data

Analyze it

Make decisions


Theoretical backgroundScientific approach

MONITORING



• MONITORING• Systematic, frequent collection

of relevant, objective data during training in order to better understand how the training process is going

• Helps to make adjustments to the training loads and prevent overreaching-overtraining

• Several neurophysiological and physiological markers have been used in the literature

RPE

CMJ

Lactate

HRV

HRR

Anxiety

Sleep qualitySpeed

TRIMPs

CPKHormones

…

Strength



DO IT SIMPLE, BUT DO IT RIGHT!



SIMPLE, NON-INVASIVE MARKERS

RPE CMJ Salivary Cortisol



• Specifically, CMJ is being widely used because of its ability to detect acute neuromuscular fatigue

• Sanchez-Medina et al. 2011



• Moreover, it has been shown that world-class runners from Kenya have better neuromuscular function while jumping than non-elite caucasians

• These variables seems to influence running economy, a key variable in distance running

Sano K, Ishikawa M, Nobue A, Danno Y, Akiyama M, Oda T, et al. Muscle-tendon interaction and EMG profiles of world class endurance

runners during hopping. Eur J Appl Physiol. 2012/12/12 ed. 2013;113(6):1395–403.




• These variables seems to influence running economy, a key variable in distance running Stretching-shortening amplitude

50

62,5

75

87,5

100

Kenyans Caucasians






• These variables seems to influence running economy, a key variable in distance running Jump height

50

62,5

75

87,5

100

Kenyans Caucasians






• These variables seems to influence running economy, a key variable in distance running Contact time

50

62,5

75

87,5

100

Kenyans Caucasians





• Thus, in the past few years the interest of strength training for distance running have raised, since ST have been demonstrated to increase RE and distance running performance

• Elite runners most likely won’t increase their VO2max levels; other variables such RE have been proposed to be more critical for elite distance running performance



Endurance+Strength Endurance

Increases in strength and RENO changes in strength nor

RE. Decrease in jump performance

No changes in VO2max nor VT2

No changes in VO2max nor VT2

14wk of heavy weight training or control



Just a few studies with high-level athletes



Purpose 1-Paper 1-

Purpose 2-Paper 2-

Purpose 3-Paper 3-

To study the relationships

between training load, CMJ, RPE and

salivary cortisol throughout a season in elite runners, and compare its values

before best and worst performances

To study the evolution of

strength throughout the season as well as to analyze its correlations with training load and salivary cortisol

To analyze the effects of the most

important competition of the

season on the CMJ, salivary cortisol and

RPE, and to study its correlations


Empirical work


Materials & Methods


• 15 (12 men) high-level middle and long distance runners from CAR Madrid

• Age: 26.3 ± 5.1 yrs• BMI: 19.7 ± 1.1 kg/m2• 1500-PB:

• 3:38-3:58 (M)• 4:12-4:23 (W)

• 10k-PB:• 29:24-31:31 (M)• 33:45-35:56 (W)

Materials & Methods-Participants-


StrengthPerformance

CMJ

Salivarycortisol

Trainingload

Materials & Methods-Study design-

General overview


PerformanceCMJ Salivarycortisol

Trainingload

Materials & Methods-Study design-

General overview

1 season follow-up (Oct-Sept)

Strength


Materials & Methods-Training load-

Km Training zone Session-RPE

External load

Training diaries

Total number of KM of each session

External load

Training diaries

Classification of the training in 1 of 3 zones designed with

respect to training pace

Zone1: 3:45-3:10min/km(long distance sets)

Zone2: 3:10-2:50min/km(middle distance sets)Zone3: <2:50min/km

(short distance/sprints sets)

Internal load

Collected after training on-field or via WhatsApp

Borg 0-10

“How hard was the training session today, with 0 being very, very light and 10 being very,

very hard?”


Materials & Methods-Salivary-free cortisol-

• Recollection tubes were given to each athlete for the collection of the saliva samples

• Immediately after they awake (8:30-9am), with an empty stomach, athletes chewed the cotton inside the tube for 60s and then stored it in their refrigerator (about -20ºC) until they came to the training center. Samples were collected at the same day of the week

• Sample tubes were then collected at the High Performance Center of Madrid and analyzed on the UPM biochemical lab following manufacturer’s instructions


Materials & Methods-Salivary-free cortisol-

Cortisol concentrations (in ng/mL) were calculated via absorbance using an ELISA kit (CV: 4.3-5.6%)


Materials & Methods-Countermovement Jump-

• Hands on hips• Countermovement until 90º of knee

flexion followed by a powerful extension of hips, knees and ankles

• Athletes were encouraged to jump as high as possible

• Knees straight during the flight-time• 3 jumps were performed, average

value (jump height, in cm.) were recorded (ICC =0.979-0.990)

• Infrared system was used (i.e. Optojump)


Materials & Methods-50m sprint-

• Standstill positon• 1 meter behind the start

photocell• Athletes were

encouraged to run as fast as possible until cutting the stop photocell

• 2 sprints were performed, the best one (time, in s) was recorded (CV: 0.33-1.2%)


Materials & Methods-Half squat force production-

• Incremental test on a smith machine

• T-Force linear velocity transducer

• 50 to 100kg (10kg increments)• 2 repetitions with each load

(2min passive rest between loads). CV: 5.4-6.7%

• Eccentric phase until 90º of knee flexion followed by an explosive concentric contraction

• Athletes were encouraged to perform the concentric phase as fast as possible


Materials & Methods-Half squat force production-

Recorded variables

Mean propulsive velocity (in m/s); Mean propulsive power (in W); Peak Rate of Force Development (RFD, in N/s); 1-RM (in kg)

MPV

(m/s

)

0,5

0,625

0,75

0,875

1

Load (kg)50 60 70 80 90 100

R² = 0,9851


Main results


Main results

PURPOSE: To study the relationships between training load, CMJ, RPE and salivary cortisol throughout a season in elite runners, and compare its values before best and

worst performances

Paper 1


Longitudinal design (39 wk Oct-Jul)15 HL athletes

Correlations & comparison of means study

Measured variablesTraining load (every day)

CMJ & salivary-free cortisol (once a week)Performance (time; every RFEA official race)

Statistical analysesPaired samples T-test

Pearson’s product-moment correlation coefficientEffect size (Hedge’s g)

α = 0.05

Main results-Paper 1-



Correlations between the season average values of the studied variables

Session-RPE Cortisol KM run Training zone

CMJ -0.489* -0.777** 0.133 -0.231

Session-RPE 0.551* 0.168 -0.130

Cortisol -0.051 -0.028

KM run -0.599*

*p < 0,05; **p < 0.001



Correlations between the weekly values of the studied variables

Session-RPE Cortisol KM run Training zone

CMJ -0.426* 0.556** -0.593** 0.437*

Session-RPE -0.037 0.444* -0.080

Cortisol -0.366 0.171

KM run -0.044

*p < 0,05; **p < 0.001



Season Best vs Worst competitions

CMJ

% o

f sea

son

aver

age

75

85

95

105

115

125

135

Best Worst

99%109%

+8.5%

ES = 0.65

p< 0.001




RPE

% o

f sea

son

aver

age

75

85

95

105

115

125

135

Best Worst

113,8%96,5%

-17.6%

ES = 0.94

p< 0.05




Cortisol

% o

f sea

son

aver

age

75

85

95

105

115

125

135

Best Worst

100,8%

130,8%

+22.9%

ES = 0.52

p> 0.05




KM

% o

f sea

son

aver

age

75

85

95

105

115

125

135

Best Worst

102,7%89,3%

-15%

ES = 0.48

p> 0.05




Training zone

% o

f sea

son

aver

age

75

85

95

105

115

125

135

Best Worst

111%105,5%

-5.2%

ES = 0.21

p> 0.05


Main results

PURPOSE: To study the evolution of strength throughout the season as well as to analyze its

correlations with training load and salivary cortisol

Paper 2


Longitudinal design (47 wk Oct-Sep)15 HL athletes


Measured variablesTraining load (every day)

Squat force production & 50m sprint (5 times over the study)Salivary-free cortisol (once a week)

Statistical analysesRepeated measures ANOVA (bonferroni post hoc)

Estimation of % of changePearson’s product-moment correlation coefficient

α = 0.05




-40

-30

-20

-10

0

10

Sprint MPV MPP RFD RM

-1,6%

-30,2%

-2,6%

3,1%

-0,4%

* *p< 0.05



RFD

(N/s

)

800

950

1100

1250

1400

P1 P2 P3 P4 P5

*

*p< 0.05



Correlations between the training periods average values of the studied variables

MPV MPP RFD RM CORT RPE KM ZONE

Sprint -0.769** -0.795** -0.247 -0.823** 0.737** 0.560* 0.072 -0.463*

MPV --- 0.910** 0.462* 0.918** -0.335 -0.650** -0.142 0.288

MPP --- 0.478* 0.960** -0.430 -0.602** 0.013 0.269

RFD --- 0.414 -0.33 -0.415 -0.117 -0.192

RM --- -0.514* -0.650** -0.134 0.408

CORT --- 0.318 0.053 -0.528*

RPE --- -0.034 -0.082

KM --- -0.597***p < 0,05; **p < 0.001



MPV

(m/s

)

0,5

0,575

0,65

0,725

0,8

RPE (0-10)4 4,75 5,5 6,25 7

r = 0.650

RPE-MPV



50-m

spr

int (

s)

5,5

6,125

6,75

7,375

8

Salivary-free cortisol (ng/mL)8 10,75 13,5 16,25 19

r = 0.737

Cortisol-Sprint


Main resultsPaper 3

PURPOSE: To analyze the effects of the most important competition of the season on the CMJ, salivary cortisol

and RPE, and to study its correlations



Observational design (National Champ + 4-week baseline)10 HL (7men) athletes


Measured variablesSalivary-free cortisol & CMJ (once a week during the BL)

Salivary-free cortisol (awakening, before and after the race)CMJ (before and after the competition)

RPE (after the competition)

Statistical analysesPaired-samples T-test

Pearson’s product-moment correlation coefficientα = 0.05


ES = 0.47

p< 0.001


% o

f bas

elin

e va

lue

95

100

105

110

CMJ

106,5%

100%

BaselineCompetiiton day

Baseline vs. competition day


ES = 1.59

p< 0.001


% o

f bas

elin

e va

lue

70

100

130

160

190

220

Salivary cortisol

217,5%

100%

BaselineCompetiiton day

Baseline vs. competition day



Cortisol increase-CMJ increase (BL to competition day)

CMJ

heig

ht in

crea

se (%

)

-3,5

0

3,5

7

10,5

14

Cortisol increase (%)0 100 200 300 400

r = 0.688p< 0.05



Jum

p he

ight

(in

cm)

31

31,6

32,2

32,8

33,4

34

CMJ

31,8

33,2

Pre Post

-3.9%

ES = 0.34

p< 0.05

Pre vs. post competition



Saliv

ary

free

corti

sol

(ng

/mL)

0

8,8

17,6

26,4

35,2

44

Salivary cortisol

43,4

26,7

Pre Post

+98.3%

ES = 0.82

p< 0.05

Pre vs. post competition



CMJ loss-Cortisol increase(Pre-post competition)

CMJ

loss

(%)

0

1,75

3,5

5,25

7

Cortisol increase (%)-75 0 75 150 225 300

r = 0.782p< 0.05



CMJ loss-RPE

CMJ

loss

(%)

-10,5

-7

-3,5

0

3,5

7

10,5

14

RPE (0-10)6,5 7,375 8,25 9,125 10

r = 0.762p< 0.05


Discussion & Conclusions


• Previous data in the literature have shown the importance of monitoring RPE, salivary cortisol or CMJ in highly trained athletes.

• For example, Jiménez-Reyes et al (2011) studied weekly CMJ performance for three consecutive seasons in high-level sprinters, and observed that there was a 6%diff between SB and SW

Discussion & Conclusions-Paper 1-


• Other studies have analyzed the relationship between salivary cortisol and muscular performance in trained athletes.

• Our results are in line with those obtained by Kraemer et. al (2004) who demonstrated that football players starting with high cortisol levels had lower CMJ heights by the end of the season




CONCLUSION 1

Systematic monitoring of CMJ, RPE and salivary cortisol may provide helpful information of the

training process and the readiness for the competition


• Our data showed that season RPE values were significantly related to season strength levels; weaker athletes being those with higher RPE throughout the season

• The strength-endurance program conducted (15-20RM) didn’t seem appropriate to increase strength in elite runners.

• This is in line with current research, that recommends explosive and/or maximal strength training to improve distance running, mainly via increases in running economy




CONCLUSION 2RPE is related to strength performance and its

monitoring could be helpful to control resistance training in elite runners

CONCLUSION 3A strength-endurance type of training doesn’t

seems appropriate to increase the force production capabilities of such athletes


• Finally, it was observed that post competition CMJ loss significantly correlates with cortisol increase and RPE

• Several studies have also found that post-exercise CMJ loss is highly correlated with markers of fatigue such as blood lactate or ammonia concentrations (Sanchez-Medina et al 2011)




CONCLUSION 4

Controlling pre-post competition CMJ decrease could help detect the degree of fatigue the

athlete has reached in the race


Limitations and prospectives



Sample size Systematicmonitoring ITL



Very difficult to recruit high-level athletes, specially for long-term studies

New technologies offer a promising future solution



ResearchKit

Largest study on Parkinson’s disease=1700 patients6h after RK announcement=+7000 patients



Wearable devices can measure physiological parameters in a non-invasive, affordable way

Systematic monitoring of ITL


HRV

Blood pressure

LactateMov. velocity

Muscle power

O2 saturationMuscle glycogen

Sweating rate

Body temperature



Practical applications


Acknowledgements


Questions & Answers

PhD presentation-Carlos Balsalobre

Education

Transcript of PhD presentation-Carlos Balsalobre