Komar, John

Short-term forecasting of performance in football is crucial in week-to-week decision making. The current study presented novel contributions regarding the considerations that should be accounted for in the prediction of match actions performed in competitive matches. First, the study examined whether the quantity and recency of training data used to build a prediction model significantly influenced predictive accuracy. Three prediction models were built with the exponential moving weighted average (EMWA) method, each differing in the quantity of training data used (three, five, and seven preceding match days). Next, the study examined if contextual constraints, such as type of match action being predicted, playing position, or player age, significantly influenced predictive accuracy. Match action data from players in the top five European leagues were collected from the 2014/2015 to the 2019/2020 seasons. The model trained using less but more recent data (three preceding match days) demonstrated the greatest accuracy. Next, within the offensive and defensive phases, match actions differed significantly in predictive accuracy. Lastly, significant differences were found in prediction accuracy between playing positions, whereby actions associated with the primary task of the playing position were more accurately predicted. These findings suggest that in the forecasting of individual match actions, practitioners should seek to train the prediction model using more recent data, instead of including as much data as possible. Furthermore, contextual constraints such as the type of action and playing position of the player must be keenly considered.

In the twenty-first century the Physical Education (PE) landscape is ever changing, with students being immersed increasingly in technologically driven learning environments. Therefore, there is a need to understand how Information and Communication Technology (ICT) are impacting learning opportunities. Specifically, how pedagogical practices could benefit from the development of ICT. This study investigated the effect of using ICT in PE when it is accompanied by a pedagogical innovation to promote students’ motivation. Thirty participants from 5 different indoor climbing PE classes were involved. Three experimental conditions were used: (1) Control, a regular climbing lesson, where traditional climbing holds are used, (2) Placebo climbing lesson, where participants climbed on an instrumented climbing wall with electronic climbing holds but the content of the lesson was similar to the regular condition, and (3) Nonlinear Pedagogy climbing lesson, where participants also climbed on the instrumented wall but with technology used in this context to implement innovative tasks routed on Nonlinear Pedagogy concepts (i.e., fostering motor exploration). Participants were involved in all three conditions and at the end of each condition, and they completed a survey set on their experiences in the climbing lessons. Compared to the control and placebo conditions, external regulation and tension scores were significantly lower and enjoyment scores were significantly higher during the Nonlinear Pedagogy climbing lesson. These results indicated that when integrated with a clear pedagogical purpose, ICT could positively impact learners.

This systematic review organizes the literature regarding the influence of contextual constraints on football match action profiles, in order to inform better practice when utilized a data-informed approach towards identifying and predicting high performing football players. Furthermore, the validity of examining “on-ball” match actions in competitive matches as an indicator of performance was also investigated. Based on the studies reviewed, task and environmental constraints were highlighted to be significantly influential on match actions performed, which suggests that recruitment strategies may be more successful if there were a greater emphasis on identifying players that best fit the constraints unique to the team, rather than recruiting the “best” player in the position. Additionally, the ability to adapt and successfully produce goal-directed behaviour in a variety of contexts may therefore be indicative of future high performance. Results from existing studies suggest that match actions performed in competitive matches can significantly distinguish between higher and lower performing teams or individuals. However, given the largely retrospective study designs of existing studies, a shift towards prospective study designs utilizing machine learning or statistical modelling is proposed to increase the practical applicability of theoretical findings.

The main purpose of the research was to describe the daily screen media habits and non-screen media habits like indoor and outdoor play, and sleep of preschool children aged 2 to 6 years from Singapore, South Korea, Japan, and Finland using a content-validated online questionnaire (SMALLQ®) and unsupervised cluster analysis. Unsupervised cluster analysis on 5809 parent-reported weekday and weekend screen and non-screen media habits of preschool children from the four countries resulted in seven emergent clusters. Cluster 2 (n = 1288) or the Early-screen media, screen media-lite and moderate-to-vigorous physical activity-lite family made up 22.2% and Cluster 1 (n = 261) or the High-all-round activity and screen media-late family made up 4.5%, respectively represented the largest and smallest clusters among the seven clusters that were emergent from the pooled dataset. Finland was best represented by Cluster 2 and Japan was best represented by Cluster 3 (High-screen media-for-entertainment and low-engagement family). Parents from Finland and Japan displayed greater homogeneity in terms of the screen media and non-screen media habits of preschool children than the parents from South Korea and Singapore. South Korea was best represented by Clusters 6 (Screen media-physical activity-engagement hands-off family) and 7 (Screen media-lite, screen media-late and high-physical activity family). Singapore was best represented by Clusters 4, 5, 6 and 7, and these clusters ranged from Low all-round activity-high nap time family to Screen media-lite, screen media-late and high-physical activity family. Future research should explore in-depth reasons for the across-country and within-country cluster characteristics of screen media and non-screen media habits among preschool children to allow for more targeted interventions.