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Field referees (FRs) need to move throughout the pitch to identify any infringements of the game's laws. Their performance depends on technical, tactical, physical, physiological, and mental factors. This retrospective study aimed to examine and assess the physical and physiological parameters as a function of time in elite association football referees during official matches. Global positioning system (match time, distance in different intensity ranges [low-intensity, high-speed, very high-speed running, and sprinting], average and peak speed, distance in accelerations or decelerations) and heart rate (average and peak) data from 212 national and international football matches were analyzed. A linear mixed-model analysis was performed to assess the differences between halves and between the three 15-minute sections of each half-time for all the physical and physiological variables collected. A significant effect of match half was found for the game time (p < 0.001) and the standing time (p = 0.005), both higher in the second half, and for the average speed (p = 0.017), which was lower in the second half. Total distance (p < 0.001), low-intensity distance (p = 0.004), and average speed (p = 0.007) all showed a reduction as a function of time. More than 7.800 high-speed intervals were detected. Accelerative actions within 3 seconds characterized most of the high-speed efforts of an FR during a match. Significant differences emerged in the way the match intensity is distributed across the match, analyzed both in halves (first vs. second) and 15-minute intervals within each half. It is important to emphasize the importance of high-speed training with a focus on a faster transition from low- to high-speed running to keep up with the play to get into an appropriate position and subsequently make the correct decisions. [ABSTRACT FROM AUTHOR]

Purpose: To examine the utility of differential ratings of perceived exertion (dRPE) for monitoring internal intensity and load in association football. Methods: Data were collected from 2 elite senior male football teams during 1 season (N = 55). External intensity and load data (duration × intensity) were collected during each training and match session using electronic performance and tracking systems. After each session, players rated their perceived breathlessness and leg-muscle exertion. Descriptive statistics were calculated to quantify how often players rated the 2 types of rating of perceived exertion differently (dRPEDIFF). In addition, the association between dRPEDIFF and external intensity and load was examined. First, the associations between single external variables and dRPEDIFF were analyzed using a mixed-effects logistic regression model. Second, the link between dRPEDIFF and session types with distinctive external profiles was examined using the Pearson chi-square test of independence. Results: On average, players rated their session perceived breathlessness and leg-muscle exertion differently in 22% of the sessions (range: 0%–64%). Confidence limits for the effect of single external variables on dRPEDIFF spanned across largely positive and negative values for all variables, indicating no conclusive findings. The analysis based on session type indicated that players differentiated more often in matches and intense training sessions, but there was no pattern in the direction of differentiation. Conclusions: The findings of this study provide no evidence supporting the utility of dRPE for monitoring internal intensity and load in football. [ABSTRACT FROM AUTHOR]

Purpose: To examine the utility of a standardized small-sided game (SSG) for monitoring within-player changes in mean exercise heart rate (HRex) when compared with a submaximal interval shuttle-run test (ISRT). Methods:Thirty-six elite youth football players (17 [1] y) took part in 6 test sessions across an in-season period (every 4 wk). Sessions consisted of the ISRT (20-m shuttles, 30″:15″ work:rest ratio, 70% maximal ISRT) followed by an SSG (7v7, 80 × 56 m, 6 min). HRex was collected during both protocols, with SSG external load measured as high-speed running distance (>19.8 km·h–1) and acceleration distance (>2 m·s−2). Data were analyzed using linear mixed-effect models. Results:Controlling for SSG external load improved the model fit describing the SSG–ISRT HRex relationship (χ2 = 12.6, P =.002). When SSG high-speed running distance and SSG acceleration distance were held constant, a 1% point change in SSG HRex was associated with a 0.5% point change in ISRT HRex (90% CI: 0.4 to 0.6). Inversely, when SSG HRex was held constant, the effects of a 100-m change in SSG high-speed running distance and a 21-m change in SSG acceleration distance on ISRT HRex were −1.0% (−1.5 to −0.4) and −0.6% points (−1.1 to 0.0), respectively. Conclusions:An SSG can be used to track within-player changes in HRex for monitoring physiological state. Given the uncertainty in estimates, we advise to only give meaning to changes in SSG HRex >2% points. Additionally, we highlight the importance of considering external load when monitoring SSG HRex. [ABSTRACT FROM AUTHOR]

The relative age effect (RAE) has been demonstrated in many youth and professional sports. In this study, we hypothesized that there would also be a RAE among youth chess players who are typically involved in a complex cognitive task without significant physical requirements. While typical RAEs have been observed in adult chess players, in this paper we wanted to focus primarily on youth chess players. In addition, we also examined RAEs in both participation rates and performance levels in a national chess championship. Therefore, the RAE was examined in a complex cognitive task that has no significant physical requirements, more specifically among youth chess players. Data were analyzed (1) for all registered Belgian youth chess players over a 5-year period (2009-2013) and (2) for participants of the Belgian youth championship 2013. Results indicated an overall RAE among all Belgian youth chess players over the last 5 years. The likelihood of participation was significantly greater for players born in the first birth-date quartile (?[superscript 2] = 10.21, p < 0.05; r = -0.77, p < 0.01; w = 0.07) and the likelihood of participation decreased when youth chess players were born in the last quartile of the year. These effects were most prominent in the under-8 and under-10 year olds. There also appeared to be a performance-related RAE. Kolmogorov-Smirnov tests (p < 0.05) showed that players born in the first months of the selection year were significantly more often in the top 10 players for each age level of the "Belgian" Youth Championship 2013.

Inequalities in relative age distribution have previously been demonstrated to influence participation and performance achievements in Masters athletes. The purpose of the present study was to examine the participation- and performance-related constituent year effect among Masters athletes (N = 2,474) from the European Masters Track and Field Championships across subdisciplines and age. The results indicated that a participation-related constituent year effect was observed. The likelihood of participation was significantly higher for athletes in their first year of any 5-year age category (χ2 = 149.8, p <.001) and decreased significantly when they were in the fourth or fifth year. The results also indicated a performance-related constituent year effect. Masters athletes in their first year won significantly more medals than expected based on observed participation rate (χ2 = 23.39, p <.001). We compare our results with the existing literature and discuss potential mechanisms for this constituent year effect. [ABSTRACT FROM AUTHOR]

This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Federation Internationale de Football Association (FIFA; n = 29) and Belgian elite (n = 28) assistant referees (ARs) assessed 64 computer-based offside situations. First, an expertise effect was found. The FIFA ARs assessed the trials more accurately than the Belgian ARs (76.4% vs. 67.5%). Second, regarding the type of error, all ARs clearly tended to raise their flag in doubtful situations. This observation could be explained by a perceptual bias associated with the flash-lag effect. Specifically, attackers were perceived ahead of their actual positions, and this tendency was stronger for the Belgian than for the FIFA ARs (11.0 vs. 8.4 pixels), in particular when the difficulty of the trials increased. Further experimentation is needed to examine whether video- and computer-based decision-making training is effective in improving the decision-making skills of ARs during the game. (Contains 1 table and 10 figures.)

Purpose: The influence of preceding load and future perceived wellness of professional soccer players is unexamined. This paper simultaneously evaluates the external load (EL) and internal load (IL) for different time frames in combination with presession wellness to predict future perceived wellness using machine learning techniques. Methods: Training and match data were collected from a professional soccer team. The EL was measured using global positioning system technology and accelerometry. The IL was obtained using the rating of perceived exertion multiplied by duration. Predictive models were constructed using gradient-boosted regression trees (GBRT) and one naive baseline method. The individual predictions of future wellness items (ie, fatigue, sleep quality, general muscle soreness, stress levels, and mood) were based on a set of EL and IL indicators in combination with presession wellness. The EL and IL were computed for acute and cumulative time frames. The GBRT model's performance on predicting the reported future wellness was compared with the naive baseline's performance by means of absolute prediction error and effect size. Results: The GBRT model outperformed the baseline for the wellness items such as fatigue, general muscle soreness, stress levels, and mood. In addition, only the combination of EL, IL, and presession perceived wellness resulted in nontrivial effects for predicting future wellness. Including the cumulative load did not improve the predictive performances. Conclusions: The findings may indicate the importance of including both acute load and presession perceived wellness in a broad monitoring approach in professional soccer. [ABSTRACT FROM AUTHOR]

In recent years, several publications examined the underlying mechanisms that might have an impact on decision-making processes under time pressure. This study investigated how individual differences in attentional capability relate to decision making in complex dynamic offside events. A total of 24 professional football assistant referees (ARs) performed an offside decision-making task and an attention-demanding task. ARs with higher attentional capability along the horizontal meridian of their attentional focus made fewer mistakes when judging offside situations in football than ARs with lower capability. This implies that being able to rely on high-attentional capabilities in situations requiring conscious perception of multiple processes is likely to be beneficial for the ultimate decision-making performance. [ABSTRACT FROM AUTHOR]

The purpose of this investigation was to (1) quantify the training load practices of a professional soccer goalkeeper and (2) investigate the relationship between the training load observed and the subsequent self-reported wellness response. One male goalkeeper playing for a team in the top league of the Netherlands participated in this case study. Training load data were collected across a full season using a global positioning system device and session-RPE (rating of perceived exertion). Data were assessed in relation to the number of days to a match (MD- and MD+). In addition, self-reported wellness response was assessed using a questionnaire. Duration, total distance, average speed, PlayerLoad™, and load (derived from session-RPE) were highest on MD. The lowest values for duration, total distance, and PlayerLoad™ were observed on MD-1 and MD+1. Total wellness scores were highest on MD and MD-3 and were lowest on MD+1 and MD-4. Small to moderate correlations between training load measures (duration, total distance covered, high deceleration efforts, and load) and the self-reported wellness response scores were found. This exploratory case study provides novel data about the physical load undertaken by a goalkeeper during 1 competitive season. The data suggest that there are small to moderate relationships between training load indicators and self-reported wellness response. This weak relation indicates that the association is not meaningful. This may be due to the lack of position-specific training load parameters that practitioners can currently measure in the applied context. [ABSTRACT FROM AUTHOR]

Purpose: Machine learning may contribute to understanding the relationship between the external load and internal load in professional soccer. Therefore, the relationship between external load indicators (ELIs) and the rating of perceived exertion (RPE) was examined using machine learning techniques on a group and individual level. Methods: Training data were collected from 38 professional soccer players over 2 seasons. The external load was measured using global positioning system technology and accelerometry. The internal load was obtained using the RPE. Predictive models were constructed using 2 machine learning techniques, artificial neural networks and least absolute shrinkage and selection operator (LASSO) models, and 1 naive baseline method. The predictions were based on a large set of ELIs. Using each technique, 1 group model involving all players and 1 individual model for each player were constructed. These models' performance on predicting the reported RPE values for future training sessions was compared with the naive baseline's performance. Results: Both the artificial neural network and LASSO models outperformed the baseline. In addition, the LASSO model made more accurate predictions for the RPE than did the artificial neural network model. Furthermore, decelerations were identified as important ELIs. Regardless of the applied machine learning technique, the group models resulted in equivalent or better predictions for the reported RPE values than the individual models. Conclusions: Machine learning techniques may have added value in predicting RPE for future sessions to optimize training design and evaluation. These techniques may also be used in conjunction with expert knowledge to select key ELIs for load monitoring. [ABSTRACT FROM AUTHOR]