Football Kicking Research Articles

The use of skill tests to predict status in junior Australian football

This study examined whether skill tests were predictive of status in junior Australian football. Players were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups: elite (state U18 squad representative; n = 25; 17.9 ± 0.5 years) and subelite (nonstate U18 squad representative; n = 25; 17.3 ± 0.6 years). Both groups completed the Australian football kicking (AFK) and Australian football handballing (AFHB) tests, assessing kicking accuracy/ball speed and handballing accuracy on dominant and nondominant sides. A multivariate analysis of variance (MANOVA) modelled the main effect of “status”, whilst logistic regression models were built for the predictive analysis using the same test parameters. Between-group differences were noted across all parameters, with the combination of kicking accuracy and ball speed on the dominant and nondominant sides being the best predictor of status for the AFK test (wi = 0.25, AUC = 89.4%) and the combination of accuracy on the dominant and nondominant sides being the best predictor of status for the AFHB test (wi = 0.80, AUC = 88.4%). The AFK and AFHB tests are predictive of status, suggesting that their use is warranted as a means of talent identification in junior Australian football.

Enhancing Foot Velocity in Football Kicking: The Role of Strength Training

In all codes of football, it is advantageous to be able to achieve a high ball speed or distance in a kick. An important determinant of ball speed and kick distance is the velocity of the foot at impact with the ball. Therefore, it is of interest to strength and conditioning practitioners to identify training programs that can increase foot velocity. The purpose of this review is to identify the factors influencing kicking performance and the research evidence relating to resistance training designed to enhance foot velocity in kicking. The review has been divided into 3 main sections. The first addresses the biomechanics of kicking to provide insights into the physical demands. The second section reviews the relationships between various measures of strength with performance indicators of maximum kicking, and the third part explores the research investigating the effects of resistance training on maximum kicking performance. Kicking can be described as a skill involving proximal-to-distal muscle activation. Foot velocity is determined by a complex sequencing of hip flexor and knee extensor concentric contractions and also involves hip extensor and knee flexor activation to assist with movement control. Research reporting correlations between strength and kicking performance support the importance of hip flexor and quadriceps strength. Although unclear, there is some evidence that adequate strength of the support leg, trunk muscles, hip adductors, and the muscles that control pelvic rotations are important. Strength training studies have shown that foot velocity and kicking performance can be enhanced by supplementary programs to regular football training, especially in nonelite athletes. Potentially valuable training includes plyometrics, exercises that simulate the whole kicking action, and kicking weighted balls. Exercises that isolate parts of the kicking action are not recommended because these do not appear to transfer well to kicking performance. There are many unanswered questions that await future research.

Movement differences in football kicking on natural and artificial turf

Movement differences in football kicking on natural and artificial turf

Computerized Interactive Gaming via Supporting Vector Machines

Computerized interactive gaming requires automatic processing of large volume of random data produced by players on spot, such as shooting, football kicking, and boxing. This paper describes a supporting vector machine‐based artificial intelligence algorithm as one of the possible solutions to the problem of random data processing and the provision of interactive indication for further actions. In comparison with existing techniques, such as rule‐based and neural networks, and so forth, our SVM‐based interactive gaming algorithm has the features of (i) high‐speed processing, providing instant response to the players, (ii) winner selection and control by one parameter, which can be predesigned and adjusted according to the needs of interaction and game design or specific level of difficulties, and (iii) detection of interaction points is adaptive to the input changes, and no labelled training data is required. Experiments on numerical simulation support that the proposed algorithm is robust to random noise, accurate in picking up winning data, and convenient for all interactive gaming designs.

The effect of muscle fatigue on instep kicking kinetics and kinematics in association football

The aim of this study was to examine the effect of leg muscle fatigue on the kinetics and kinematics of the instep football kick. Fatigue was induced by repeated, loaded knee extension (40% body weight) and flexion (50% body weight) motions on a weight-training machine until exhaustion. The kicking motions of seven male players were captured three-dimensionally at 500 Hz before and immediately after the fatigue protocol. The significantly slower ball velocity observed in the fatigue condition was due to both reduced lower leg swing speed and poorer ball contact. The reduced leg swing speed, represented by a slower toe linear velocity immediately before ball impact and slower peak lower leg angular velocity, was most likely due to a significantly reduced resultant joint moment and motion-dependent interactive moment during kicking. These results suggest that the specific muscle fatigue induced in the present study not only diminished the ability to generate force, but also disturbed the effective action of the interactive moment leading to poorer inter-segmental coordination during kicking. Moreover, fatigue obscured the eccentric action of the knee flexors immediately before ball impact. This might increase the susceptibility to injury.

Artificial Intelligence in Technique Analysis - Past, Present and Future

This paper reviews developments in the use of Artificial Intelligence in technique analysis over about the last ten years. I outline the potential uses of Expert Systems as diagnostic tools for evaluating technique ‘errors’ and present some example knowledge rules for such an expert system. I then compare technique analysis, in which Expert Systems appear to have found no place to date, with gait analysis, in which they are routinely used. Consideration is then given to technique analysis using Artificial Neural Networks, focusing on Kohonen self-organizing maps, which have been most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of Kohonen maps in technique analysis are presented in javelin and discus throwing and in football kicking. Shot putting is the sole technique analysis presented using multi-layer networks. An example is given of the use of Evolutionary Computation in technique optimization, rather than technique analysis, in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. I conclude with some speculations about the future uses of Artificial Intelligence in technique analysis.

Relationship Between a Modified Thomas Test and Leg Range of Motion in Australian-Rules Football Kicking

Context:Flexibility tests are sometimes thought to be related to range of motion in dynamic activities, but such a relationship remains to be determined.Objective:To determine the correlation between flexibility and hip and knee angles in Australian football kicking.Design:Correlation.Setting:Biomechanics laboratory.Participants:16 Australian Rules football players.Main Outcome Measures:Hip and knee angles of the preferred kicking leg in a relaxed position were determined with a modified Thomas test. Maximum hip extension, the knee-flexion angle in this position, the maximum knee-flexion angle, and the hip angle at this position during the swing phase of maximum-effort drop-punt kicks were determined.Results:Significant correlations were found between hip flexibility and maximum hip extension (r = .65, P < .01) and hip angle at the maximum knee-flexion angle (r = .70, P < .01).Conclusions:The data indicate a moderate association between hip flexibility and hip angles during kicking.

Kinesiological Determinants of the Path of the Foot during the Football Kick

Abstract High speed cinematography was used to gather data from 4 subjects for use in successful multiple regression predictions of the path of the foot during the kicking of an Australian rules football. The predictors used were the direction and velocity of iliac crest on the kicking leg side of the body, together with the knee and thigh angle velocities of the kicking leg. The relative importance of the predictors was measured by the beta weights of the regression equations and found to vary from subject to subject. It was also found possible to predict the direction and velocity of the iliac crest on the support side of the body from the thigh, knee, and ankle angles of the support leg. These predictions were not as successful as those of the foot path. The analysis suggested a reason for the lack of correlation between body velocity and the velocity of the kicking foot. A possible explanation was proposed for the relative lack of movement of the thigh during the period of contact between foot and ball.

Interrelationships among Reaction Times and Speeds of Movement in Different Limbs

Abstract Two movements basic to sports skills, a modified baseball throw and a football kick, were studied in 105 college men. Individual differences in ability to move an arm or leg quickly were found to be uncorrelated with the reaction time for these movements. There was only a moderately high correlation between the reaction ability of the right and left legs, and between the right and left arms. Arm vs. leg correlations were significant but low. A similar pattern of correlations between limbs was found for movement ability, but all correlations were considerably lower and movement specificity was high. The reliability of individual differences was high in all of the measures.