scholarly journals An Elementary Communication Framework for Open Co-operative RoboCup Soccer Teams

2007 ◽  
Keyword(s):  
Communication Framework ◽  
Soccer Teams

How strong are soccer teams? The ‘Host paradox’ and other counterintuitive properties of the FIFA’s ranking.

2019 ◽  
Author(s):  
Marek Kaminski
Keyword(s):  
Long Time ◽  
Soccer Teams ◽  
Major Loss ◽  
Host Effect ◽  
Large Investment

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Helvetica Neue'} <p>The FIFA's ranking of national soccer teams is plagued with paradoxes. One surprising paradox is a dramatic underrating of the hosts of main tournaments. The hosts, who are absent from the preliminaries, for a long time, play only friendlies that award few points. Three models estimate the magnitude of the resulting “Host Effect” at 14.1-16.7 positions. Such an estimate goes against the intuition that a large investment in hosting a tournament should result in improvement of the host team’s standing. Host’s low ranking decreases the interest in the tournament and may result in a major loss of advertisement revenue.</p>

How does the workload applied during the training week and the contextual factors affect the physical responses of professional soccer players in the match?

2021 ◽  
pp. 174795412199561
Author(s):  
Berni Guerrero-Calderón ◽  
Maximilian Klemp ◽  
José Alfonso Morcillo ◽  
Daniel Memmert
Keyword(s):  
Prediction Models ◽  
Contextual Factors ◽  
Soccer Players ◽  
Professional Soccer ◽  
Soccer Teams ◽  
Level Of Significance ◽  
Physical Output ◽  
Physical Responses ◽  
Positive Effect

The aim of this study was to examine whether match physical output can be predicted from the workload applied in training by professional soccer players. Training and match load records from two professional soccer teams belonging to the Spanish First and Second Division were collected through GPS technology over a season ( N = 1678 and N = 2441 records, respectively). The factors playing position, season period, quality of opposition, category and playing formation were considered into the analysis. The level of significance was set at p ≤ .05. The prediction models yielded a conditional R-squared in match of 0.51 in total distance (TD); 0.58 in high-intensity distance (HIRD, from 14 to 24 km · h−1); and 0.60 in sprint distance (SPD, >24 km·h−1). The main finding of this study was that the physical output of players in the match was predicted from the training-load performed during the previous training week. The training-TD negatively affected the match physical output while the training-HIRD showed a positive effect. Moreover, the contextual factors – playing position, season period, division and quality of opposition – affected the players’ physical output in the match. Therefore, these results suggest the appropriateness of programming lower training volume but increasing the intensity of the activity throughout the weekly microcycle, and considering contextual factors within the load programming.

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