Effect of different anthropometry-driven block settings on sprint start performance.

ABSTRACTFew studies have focused on the effect of individual anthropometrics when considering "set" position posture during the sprint start. This study aimed to measure the effect of different anthropometry-driven block settings on kinetic and kinematic parameters and performance during the start in well-trained and non-trained sprinters. Front block-starting line (FB/SL) distance was manipulated between 50% and 70% of each individual's leg length at 5% intervals, whilst the inter-block distance was held constant at 45% of leg length. Thirty-six sprinters performed three maximal-effort 10 m sprints in each of the five conditions. Joint angles in the "set" position were quantified though 2D video analysis, the forces generated during block clearance phase were measured by dynamometric starting blocks, and times to 5 and 10 m were measured with photocells. The effects of the five block setting conditions were largely consistent irrespective of ability level. Shorter FB/SL distances were associated with significantly more flexed hip and knee angles in the "set" position, a significantly more plantar flexed front ankle, and a significantly more dorsiflexed rear ankle. There were no significant effects of FB/SL distance on total block time, and thus the greater rear block peak forces and impulses produced from the shorter FB/SL distances combined with no effects on the resultant front block peak forces and impulses, led to higher levels of sprint start performance from the shorter FB/SL distances. Considering FB/SL distances closer to 50% of leg length may be beneficial for coaches and athletes to explore during sprint start training.HighlightsThe effects of different front-block starting line distances on "set" position kinematics, block clearance kinetics and sprint start performance are largely consistent irrespective of ability level.When using a medium inter-block distance (45% of leg length), shorter front block-starting line distances (down to 50% of the leg length) led to improved sprint start performance.From shorter front block-starting line distances, sprint start performance was primarily improved through greater force production against the rear block which led to greater impulses due to no change in push durations or resultant front foot forces.Lower-limb length is an important consideration when adjusting anteroposterior block distances.

Discovering associations between players' performance indicators and matches' results in the European Soccer Leagues.

The application of data mining techniques and statistical analysis to the sports field has received increasing attention in the last decade. One of the most famous sports in the world is soccer, and the present work deals with it, using data from the 2009/2010 season to the 2015/2016 season from nine European leagues extracted from the Kaggle European Soccer database. Overall performance indicators of the four roles in a soccer team (forward, midfielder, defender and goalkeeper) for home and away teams are used to investigate the relationships between them and the results of matches, and to predict the wins of the home team. The model used to answer both these demands is the Bayesian Network. This study shows that this model can be very useful for mining the relations between players' performance indicators and for improving knowledge of the game strategies applied by coaches in different leagues. Moreover, it is shown that the ability to predict match results of the proposed Bayesian Network is roughly the same as that of the Naive Bayes model.

Measuring job satisfaction in the social services sector with the Rasch model.

In the present paper, the Rasch measurement model is used in the validation and analysis of data coming from the satisfaction section of the first national survey concerning the social services sector carried out in Italy. A comparison between two Rasch models for polytomous data, that is the Rating Scale Model and the Partial Credit Model, is discussed. Given that the two models provide similar estimates of the item difficulties and workers satisfaction, for almost all the items the response probabilities computed using the RSM and the PCM are very close and the analysis of the bootstrap confidence intervals shows that the estimates obtained applying the RSM are more stable than the ones obtained using the PCM, it can be conclude that, for the present data, the RSM is more appropriate than the PCM.