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Πώς θα είναι η επιστημονική υποστήριξη στο ποδόσφαιρο στο μέλλον;
Είμαστε έτοιμοι;
Γιώργος Νάσσης, PhD
Ποιά είναι η πρόκληση;
• Να βελτιώσουμε την απόδοση χωρίς να αυξήσουμε τον κίνδυνο μυικού τραυματισμού και κόπωσης
What we need? 1)Training (load) monitoring
2)An injury “prediction” model 3)Training methods to speed up
adaptations to training
Training load and injuries in team sports
Gabbett et al., 2010
Θα πρέπει δηλαδή να σταματήσουμε την
προπόνηση?
• Ασφαλώς όχι!
• Μάλλον πρέπει να προπονούμαστε εξυπνότερα και αποτελεσματικότερα
Is training causing injuries or is protecting
from injuries?
Gabbett. Br J Sports Med, 2016
Hard and appropriate training offers a protective effect due to its effect on
fitness
Πως θα βελτιώσουμε την φυσική κατάσταση
Μερικά παραδείγματα
• Make better use of the transition period
• Implement blocks of intensified training
Performance Development
Excellence in Football Project - George
Sprint: 3-7% decline Endurance: 10-28% decline
Προπόνηση υψηλής έντασης
16
16.5
17
17.5
18
18.5
19
19.5
PRE POST
Km
/h
MAS
SSG&HIT
TRAD
28
29
30
31
32
33
34
35
36
PRE POST
cm
CMJ
CMJ
3.5
3.6
3.7
3.8
3.9
4
4.1
4.2
4.3
4.4
PRE POST
seco
nd
s -
s
COD - R
3.5
3.6
3.7
3.8
3.9
4
4.1
4.2
4.3
4.4
PRE POST
seco
nd
s -
s
COD - L
*
* p < 0.05
Endurance Agility
Paul et al, under review
Take home message 1)Intensified training is feasible in our set-up
2)This training may lead to greater improvements in endurance
Προπονητικό φορτίο και τραυματισμοί
Αλήθεια, μετράμε ό,τι νομίζουμε ότι μετράμε
Η χρήση του RPE
Do highly-trained football players become
“fatigued”?
Either elite players pace themselves or the tools
we use to capture fatigue & load are not sensitive
enough
Tucker 2009
The Central Governor Model of Exercise Regulation and RPE regulation
Nassis, Brito, Dvorak, Chalabi, Racinais, under review
Physical performance as a function of environmental heat stress
Low intensity
(r=0.36, p<0.05)
High intensity
(r=-0.28, p<0.05)
Medium intensity
(r=-0.01, NS)
0
10
20
30
40
50
60
70
10 15 20 25 30 35
Dis
tan
ce
co
ve
red
pe
r m
in (
m)
WBGT (º)
HEAT
Summary of results
Variable Index Finding
Nature of game TD, active match time, # cards
Physical performance
HI, number of sprints
Peak speed
Technical performance
Number of passes
Rate of successful passes
Το κονφούζιο συνεχίζεται!
Future challenges-How to measure the outcome of training?
The future of the game
EPL website
28% increase
Νέες τεχνολογίες Ποιο ειναι το μέλλον
Akenhead et al (under review)
How to deal with big data?
INTEGRATE THE BIG DATA AND PROVIDE MEANINFUL RESULTS TO MANAGERS AND COACHES
FOR BETTER DECISION MAKING
An integrated data management system in
high level football
Examples of predictive analytics
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