Are Linear Speed and Jumping Ability Determinants of Change of Direction Movements in Young Male Soccer Players?

The study was undertaken to investigate the relationships between linear speed, change of direction, and explosive power in the lower limbs of young soccer players. We aimed to determine the variables associated with effective change-of-direction speeds (time) based on the 30-m ZigZag (cutting maneuver) under 60° (CODS1), and 30 m sprint divided into forward-backward-forward movement (CODS2). Sixty young soccer players (age: 17.4 ± 0.7 years, height: 1.76 ± 0.06 m, weight: 68.1 ± 8.9 kg) from soccer sport clubs were included. The participants performed 30-m change-of-direction sprints and 30-m backward and forward sprints. For the maximum speed evaluation, a straight-line 30-m sprint test was performed. Counter-movement jumps and standing broad jumps were used to assess jumping ability. Pearson's linear correlation and a multiple stepwise linear regression model were used to adjust for variations related to the influence of functional speed and explosive power variables, which were analyzed based on the CODS1 and CODS2 data. Our results showed that 30-m CODS2 and standing broad jumps were associated with CODS1. The variation for the 30-m change-of-direction maneuvers under 60° could be explained by the results of 30-m forward-backward-forward change-of-direction. The standing broad jump explained 10% variation for the performances in change-of-direction sprint decrements and 9% variation for the 5-m change-of-direction with the best times, whereas straight-line sprinting was related to forward-backward-forward change-of-direction. The 10-m sprint explained 50% variation of the performances in the first 10-m forward running in the CODS2 and 12% variation for 10-m backward-forward change-of-direction. The 30-m sprint explained 36% variation for 30-m forward-backward-forward change-of-direction. The 30-m sprint and overall body mass also explained 58% variation for 10-m forward-backward change-of-direction. For coaching purposes, we report that forward-backward-forward and cutting maneuver change-of-direction movements are independent and highly useful skills. This information can help to provide better training prescriptions.

The Relationship between 200 m Performance and Selected Anthropometric Variables and Motor Abilities in Male Sprinters.

The goal of this study was the investigation of the relationship between 200 m performance and motor abilities and anthropometric characteristics of different level of male sprinters (200 m performance 23.80 ± 2.16 s--the best results 21.40 s). The physical fitness measures included: 50 m from standing and flying start, standing long jump (SLJ) standing five jump (SFJ), double and single leg countermovement jumps CMJ), flexibility (sit and reach) and 4 kg shot put throwing (over head). The Spearman correlation coefficient was applied to verify the association. The results demonstrated strong relationships (p < 0.05) between 200 m performance and experience (age) and body mass (r = 0.85, r = -0.80 respectively) As for the motor abilities strong relationship exists between 200 m and time of 150 m, 50 m from standing and flying start and CMJ on single leg. Vertical jumping displayed stronger relationship with 200 m performance that horizontal one. From a practical point of view this is very important notice.

The Relationship between Selected Motor Ability Determinants and Anthropometric Characteristics in Adolescent Athletes from Various Sport.

The main purpose of this study was to examine the relationship between speed, lower extremities explosive power, simple, and complex responses in adolescent athletes from various disciplines. Thirty nine athletes of 16.5 years old, N = 13 sprinters and jumpers, N = 13 soccer players, and N = 13 judokas participated in the experiment. Pearson correlations, a one-way ANOVA and an independent t-test for establishing differences between those three groups of athletes was applied. Additionally the Ward method of hierarchical cluster analysis also was applied. The strong correlation occurred between complex responses and speed; 20 m from standing and 20 m flying start (r = 0.62 and r = 0.65 respectively). In other cases, no strong association was found. The substantial differences between groups occurred in the 20 m run from flying start (t = 5.92) and standing triple jump (t = 4.16). The study indicates that adolescent athletes may need to be assessed differently to a certain extent, including sport specialization.

Towards application of rule learning to the meta-analysis of clinical data: an example of the metabolic syndrome.

PURPOSE: Systematic reviews and meta-analysis of published clinical datasets are important part of medical research. By combining results of multiple studies, meta-analysis is able to increase confidence in its conclusions, validate particular study results, and sometimes lead to new findings. Extensive theory has been built on how to aggregate results from multiple studies and arrive to the statistically valid conclusions. Surprisingly, very little has been done to adopt advanced machine learning methods to support meta-analysis. METHODS: In this paper we describe a novel machine learning methodology that is capable of inducing accurate and easy to understand attributional rules from aggregated data. Thus, the methodology can be used to support traditional meta-analysis in systematic reviews. Most machine learning applications give primary attention to predictive accuracy of the learned knowledge, and lesser attention to its understandability. Here we employed attributional rules, the special form of rules that are relatively easy to interpret for medical experts who are not necessarily trained in statistics and meta-analysis. RESULTS: The methodology has been implemented and initially tested on a set of publicly available clinical data describing patients with metabolic syndrome (MS). The objective of this application was to determine rules describing combinations of clinical parameters used for metabolic syndrome diagnosis, and to develop rules for predicting whether particular patients are likely to develop secondary complications of MS. The aggregated clinical data was retrieved from 20 separate hospital cohorts that included 12 groups of patients with present liver disease symptoms and 8 control groups of healthy subjects. The total of 152 attributes were used, most of which were measured, however, in different studies. Twenty most common attributes were selected for the rule learning process. By applying the developed rule learning methodology we arrived at several different possible rulesets that can be used to predict three considered complications of MS, namely nonalcoholic fatty liver disease (NAFLD), simple steatosis (SS), and nonalcoholic steatohepatitis (NASH).

Analyzing diaries for analytical relapse prevention using natural induction: a method and preliminary results.

This article briefly describes natural induction approach to knowledge discovery, and then applies it to the problem of bad habit relapse prevention by analyzing patients' diaries. Natural induction seeks patterns in data that are in forms easy to understand and interpret, because they resemble those in which humans represent knowledge, such as natural language descriptions and visual forms. The application of natural induction to the problem of bad habit relapse has produced patterns easy to understand, in some cases of surprising simplicity.