In professional sports clubs, the growing number of individual IT-systems increases the need for central information systems. Various solutions from different suppliers lead to a fragmented situation in sports. Therefore, a standardized and independent general concept for a club information systems (CIS) is necessary. Due to the different areas involved, an interdisciplinary approach is required, which can be provided by sports informatics. The purpose of this paper is the development of a general and sports informatics driven concept for a CIS, using methods and models of existing areas, especially business intelligence (BI). Software engineering provides general methods and models. Business intelligence addresses similar problems in industry. Therefore, existing best practice models are examined and adapted for sport. From sports science, especially training systems and information systems in sports are considered. Practical relevance is illustrated by an example of Liverpool FC. Based on these areas, the requirements for a CIS are derived, and an architectural concept with its different components is designed and explained. To better understand the practical challenges, a participatory observation was conducted during years of working in sports clubs. This paper provides a new sports informatics approach to the general design and architecture of a CIS using best practice models from BI. It illustrates the complexity of this interdisciplinary topic and the relevance of a sports informatics approach. This paper is meant as a conceptional starting point and shows the need for further work in this field.
Decision making in sport involves forecasting and selecting choices from different options of action, care, or management. These processes are conditioned by the available information (sometimes limited, fallible, or excessive), the cognitive limitations of the decision-maker (heuristics and biases), the finite amount of available time to make the decision, and the levels of risk and reward. Decision support systems have become increasingly common in sporting contexts such as scheduling optimization, skills evaluation and classification, decision-making assessment, talent identification and team selection, or injury risk assessment. However no specific, formalised framework exists to help guide either the development or evaluation of these systems. Drawing on a variety of literature, this paper proposes a decision support system development framework for specific use in high-performance sport. It proposes three separate criteria for this purpose: 1) Context Satisfaction, 2) Output Quality, and 3) Process Efficiency. Underpinning these criteria there are six specific components: Feasibility, Delivered knowledge, Decisional guidance, Data quality, System error, and System complexity. The proposed framework offers a systematic approach for users to ensure that each of the six components are considered and optimised before, during, and after developing the system. A DSS development framework for high-performance sport should help to improve both short and long term decision-making in a variety of sporting contexts.
In tennis, the accumulation of data has progressed and research on tactical analysis has been conducted. Estimating strategically important factors would have the benefit of providing players with useful advice and helping audience members understand what tennis players are good at. Previous research has been conducted into ways of predicting Association of Tennis Professionals (ATP) tennis match outcomes as well as estimating factors that are important for victories using machine learning models. The challenge of previous research is that the victory factor lacks concreteness. Since we thought the root of the abovementioned problem was that previous researchers used game summary as a feature and did not consider the process of rallies between points, this research focused on calculating the frequency of single shots, two-shot patterns, and specific effective shot patterns from each point rally of ATP singles matches. We then used those data to predict point winners and useful features using L1-regularized logistic regression. The highest accuracy obtained was 66.5%, and the area under the curve (AUC) was 0.689. The most prominent feature we found was the ratio of specific shots by specific players. From these results, our method could reveal more concretely tactical factors than previous studies.
Driven by the increased availability of position and performance data, automated analyses are becoming the daily routine in many top-level sports. Methods from the domains of data mining and machine learning are more frequently used to generate new insights from massive amounts of data. This study evaluates the performance of four current models (multi-layer perceptron, convolutional network, recurrent network, gradient boosted tree) in classifying tactical behaviors on a beach volleyball dataset consisting of 1,356 top-level games. A three-way between-subjects analysis of variance was conducted to determine the effects of model, input features and target behavior on classification accuracy. Results show significant differences in classification accuracy between models as well as significant interaction effects between factors. Our models achieve classification performance similar to previous work in other sports. Nonetheless, they are not yet at the level to warrant practical application in day to day performance analysis in beach volleyball.
Many factors are considered when making a hiring decision in the National Football League (NFL). One difficult decision that executives must make is who they will select in the offseason. Mathematical models can be developed to aid humans in their decision-making processes because these models are able to find hidden relationships within numeric data. This research proposes the Heuristic Evaluation of Artificially Replaced Teammates (HEART) methodology, which is a mathematical model that utilizes machine learning and statistical-based methodologies to aid managers with their hiring decisions. The goal of HEART is to determine expected and theoretical contribution values for a potential candidate, which represents a player’s ability to increase or decrease a team’s forecasted winning percentage. In order to validate the usefulness of the methodology, the results of a 2007 case study were presented to subject matter experts. After analyzing the survey results statistically, five of the eight decision-making categories were found to be “very useful” in terms of the information that the methodology provided.
Wearable sensors that can be used to measure human performance outcomes are becoming increasingly popular within sport science research. Validation of these sensors is vital to ensure accuracy of extracted data. The aim of this study was to establish the validity and reliability of gyroscope sensors contained within three different inertial measurement units (IMU). Three IMUs (OptimEye, I Measure U and Logger A) were fixed to a mechanical calibration device that rotates through known angular velocities and positions. RMS scores for angular displacement, which were calculated from the integrated angular velocity vectors, were 3.85° ± 2.21° and 4.34° ± 2.57° for the OptimEye and IMesU devices, respectively. The RMS error score for the Logger A was 22.76° ± 23.22°, which was attributed to a large baseline shift of the angular velocity vector. After a baseline correction of all three devices, RMS error scores were all below 3.90°. Test re-test reliability of the three gyroscope sensors were high with coefficient of variation (CV%) scores below 2.5%. Overall, the three tested IMUs are suitable for measuring angular displacement of snow sports manoeuvres after baseline corrections have been made. Future studies should investigate the accuracy and reliability of accelerometer and magnetometer sensors contained in each of the IMUs to be used to identify take-off and landing events and the orientation of the athlete at those events.
The aim of the research was to diagnose manifestations of functional and structural disorders and consider the effect of intervention on the musculoskeletal system of students of teacher’s program of physical education. A total of 40 students of Faculty of Sports Prešov University in Prešov participated in the research. As part of the experiment we designed a targeted movement program as an intervention and applied it to an experimental group of students. After 5 months of the intervention, the measurements were repeated. In experimental group we noticed that 30 % of men and 20 % of women improved from III. to II. qualitative degree of shortened muscles. The statistically significant difference (p <.05) was confirmed in group of men. From the perspective of intersexual differences, we observed a statistically significant difference among the shortened muscles in the experimental group (p ≤.05). Changes in structural disorders of the spine after the intervention were statistically insignificant. In regards to good spinal health and muscle balance, we assume that targeted movement program can have preventive effect against functional and structural disorders.
This study aims to determine the differences and to achieve better effect in the sprint training, shuttle run and agility on base of running speed of athletes softball. This study uses an experimental method with a 2×2 factorial design. Participants in this research were 42 male athletes (mean age = 16.88; SD = 1.31), Indonesian high school students. The instruments of this study were the base running test and reactive agility testing protocols. Analysis of the data is analysis of variance (ANOVA) of two pathways at a significant level α = 0.05. The results of the study are as follows: exercise sprint training give better effect to the results of base running extracurricular softball, as evidenced by the value of p = 0.036 < 0.05. Participants who have high agility level give a better effect than participants who have low agility level on the results of softball extracurricular base running, as evidenced by the value of p = 0,000 < 0.05. There is no interaction between the training model and agility on the results of softball extracurricular base running, which is evident from the value of p = 0.634 > 0.05. This research contributes to the field of softball sports, especially in creating an appropriate training program to increase the speed of base running in male students by using sprint training so that results are more effective.
The purpose of this study is to examine: (1) the difference in the effect of the method of dribbling sprinting and sprint interval training on the ability of dribbling; (2) the difference in influence between high-eye coordination and low-foot coordination on the ability of dribbling; and (3) the interaction between training methods and eye-foot coordination on dribbling skills. Participants in this study were 37 soccer students aged 12 – 13 years (M = 12.38; SD = 0.49). This research method is an experiment with a 2×2 factorial design. The instrument for measuring ankle coordination is the Soccer Wall Test and for measuring the ability of dribbling is the Short Dribbling Test. The data analysis technique used is two-way ANOVA at the significance level α = 0.05. The results of the study are as follows. (1) There is a significant difference in effect between the method of acceleration dribbling and interval running training on dribbling ability, as evidenced by the value of F = 14,032; p value = 0.002 < 0.05. (2) There is a significant difference in the effect of high eye-foot coordination ability and low-foot eye coordination on dribbling ability, as evidenced by the value of F = 27,685; p value = 0,000 <0.05. (3) There is a significant interaction between the training methods (acceleration and interval running dribbling exercises) and eye-foot coordination (high and low) on the dribbling ability of students aged 12-13 years, as evidenced by the value of F = 21,780 and the p value = 0,000 <0.05.
The aim of the study was to determine the levels of lower limb explosive strength of girls in different sport specialization. The sample consisted of 24 girls in aerobic gymnastics (n = 12) and athletic (n = 12) aged 10 to 12 years. To assess the levels of girls’ lower limbs explosive strength, we administered the following tests: countermovement jump test, countermovement jump with free arms test, squat jump test, 10-seconds repetitive jumping test. Testing sessions took place in September 2019. To obtain data about the levels of lower limbs explosive strength, we recorded step height (cm) and duration of the flight phase (s). Data about the lower limbs explosive strength were collected using the Optogait system for optical detection. We applied basic statistical characteristics, namely Student’s t-test and multivariate linear regression. There were no significant differences between girls in aerobic gymnastics and athletics. We recorded better test results in the group of girl’s athletes in the countermovement jump, countermovement jump with free arms and squat jump. In the group of girl’s involved in aerobic gymnastics, we recorded better results in the 10-second repetitive vertical jumping and vertical jump strength. According to the collected data, we may conclude that the training process of the selected girls in terms of explosive strength development is significantly different. Girls involved in aerobic gymnastics showed a higher level of performance in the 10-second vertical jump, which results from the structure of sport specificity.