Optic variables used to judge future ball arrival position in expert and novice soccer players

Although many studies have looked at the perceptual-cognitive strategies used to make anticipatory judgments in sport, few have examined the informational invariants that our visual system may be attuned to. Using immersive interactive virtual reality to simulate the aerodynamics of the trajectory of a ball with and without sidespin, the present study examined the ability of expert and novice soccer players to make judgments about the ball's future arrival position. An analysis of their judgment responses showed how participants were strongly influenced by the ball's trajectory. The changes in trajectory caused by sidespin led to erroneous predictions about the ball's future arrival position. An analysis of potential informational variables that could explain these results points to the use of a first-order compound variable combining optical expansion and optical displacement.

Automatic detection and classification of football players

Color segmentation of images usually requires a manual selection and classification of samples to train the system. This paper presents an automatic system that performs these tasks without the need of a long training, providing a useful tool to detect and identify figures. In real situations, it is necessary to repeat the training process if light conditions change, or if, in the same scenario, the colors of the figures and the background may have changed, being useful a fast training method. A direct application of this method is the detection and identification of football players.

Real-time GPU color-based segmentation of football players

In this paper, we propose a multi-camera application capable of processing high resolution images and extracting features based on colors patterns over graphic processing units (GPU). The goal is to work in real time under the uncontrolled environment of a sport event like a football match. Since football players are composed for diverse and complex color patterns, a Gaussian Mixture Models (GMM) is applied as segmentation paradigm, in order to analyze sport live images and video. Optimization techniques have also been applied over the C++ implementation using profiling tools focused on high performance. Time consuming tasks were implemented over NVIDIA's CUDA platform, and later restructured and enhanced, speeding up the whole process significantly. Our resulting code is around 4-11 times faster on a low cost GPU than a highly optimized C++ version on a central processing unit (CPU) over the same data. Real time has been obtained processing until 64 frames per second. An important conclusion derived from our study is the scalability of the application to the number of cores on the GPU. © 2011 Springer-Verlag.

Key Players and Key Groups in Teams

This paper contributes to the literature on centrality measures in economics by defining a team game and identifying the key players and key groups
in the game. We extend the work of Ballester et al. (Econometrica, 2006) by incorporating a network outcome component in the players' payoff functions and prove that there is a unique interior Nash Equilibrium in pure strategies. We develop a team intercentrality measure based on alternative scenarios that capture the externality created by teammates on each player.

The health profile of football/soccer players in Northern Ireland - a review of the uefa pre-participation medical screening procedure.

BACKGROUND:
It is compulsory that domestic football/soccer teams in UEFA competitions organise players' pre-participation medicals. Although screening guidelines have been established, these remain controversial. The findings of medical examinations can have lasting consequences for athletes and doctors. No previous studies have reported UEFA pre-participation screening results in semi-professional footballers. This study aims to further knowledge regarding 'normal' data in this population.

METHOD:
Retrospective audit and analysis of records of pre-season medicals for all male first-team players at one semi-professional Northern Ireland Premiership team between 2009-2012. Medicals were conducted by the club doctor following the UEFA proforma. Height, weight, blood pressure (BP), full blood count (FBC), dipstick urinalysis and resting electrocardiogram (ECG) were conducted by an independent nurse. Only one ECG must be documented during a player's career; other tests are repeated yearly.

RESULTS:
89 medicals from 47 players (6 goalkeepers, 11 defenders, 22 midfielders and 8 attackers; mean age 25.0 years (SD 4.86)) were reviewed. Mean height of the players was 179.3 cm (SD 5.90) with a mean weight of 77.6 kg (SD 10.5). Of 89 urine dipsticks, 7 were positive for protein; all 7 were normal on repeat testing following 48 hours of rest. Of 40 ECGs (mean ventricular rate 61.2 bpm (SD 11.6)), one was referred to cardiology (right bundle branch block; prolonged Q-T interval). No players were excluded from participation.

CONCLUSIONS:
This study provides important information about 'normal' values in a population of semi-professional footballers. Urinalysis showing protein is not uncommon but is likely to be normal on repeat testing.

Expert players accurately detect an opponent's movement intentions through sound alone

Sounds offer a rich source of information about events taking place in our physical and social environment. However, outside the domains of speech and music, little is known about whether humans can recognize and act upon the intentions of another agent’s actions detected through auditory information alone. In this study we assessed whether intention can be inferred from the sound an action makes, and in turn, whether this information can be used to prospectively guide movement. In two experiments experienced and novice basketball players had to virtually intercept an attacker by listening to audio recordings of that player’s movements. In the first experiment participants had to move a slider, while in the second one their body, to block the perceived passage of the attacker as they would in a real basketball game. Combinations of deceptive and non-deceptive movements were used to see if novice and/or experienced listeners could perceive the attacker’s intentions through sound alone. We showed that basketball players were able to more accurately predict final running direction compared to non-players, particularly in the second experiment when the interceptive action was more basketball specific. We suggest that athletes present better action anticipation by being able to pick up and use the relevant kinematic features of deceptive movement from event-related sounds alone. This result suggests that action intention can be perceived through the sound a movement makes and that the ability to determine another person’s action intention from the information conveyed through sound is honed through practice.