Breaking barriers: Exploring female-specific health challenges affecting performance in an elite multisport training environment.

OBJECTIVES: Female-specific issues, such as breast injuries, pelvic floor dysfunctions, saddle sores, and menstrual symptoms, can significantly impact female athletes. This study examined the prevalence, perceived impact on performance, and role of the support staff in addressing and managing these issues in elite athletes based at a multisport training centre. DESIGN: Anonymous online questionnaire. METHODS: A total of 180 female athletes from various sport disciplines at the Dutch Olympic Training Centre were invited to participate in the study. An anonymous, 39-item questionnaire was developed and hosted on Qualtrics collecting data on respondents' characteristics, breast injuries, pelvic floor dysfunctions, saddle sores, menstrual symptoms, contraceptive use, and communication about these issues. RESULTS: A total of 105 valid responses were analysed. The findings revealed that athletes regularly experience breast injuries (15.2 %), urinary incontinence (29.5 %), other pelvic floor problems (21.0 %), saddle sores (65.7 %), and menstrual cycle-related symptoms, with negative performance effects. Communication with support staff remained limited, with only 23.8 % of athletes discussing any of these issues, often due to concerns about understanding, shame, or a lack of opportunity for easy communication. CONCLUSIONS: The findings underscore the crucial role of creating a supportive environment, promoting early intervention, and utilising multisport centres to comprehensively address these concerns, emphasising the need for open communication, education, and support to enhance female athletes' performance and well-being.

Effectiveness of Recovery Strategies After Training and Competition in Endurance Athletes: An Umbrella Review.

BACKGROUND: Recovery strategies are used to enhance performance and reduce injury risk in athletes. In previous systematic reviews, individual recovery strategies were investigated to clarify their effectiveness for mixed groups of athletes. However, the current evidence is ambiguous, and a clear overview of (training) recovery for endurance athletes is still lacking. METHODS: We conducted an umbrella review based on a literature search in PubMed, Cochrane Database of Systematic Reviews, and Web of Science. Reviews published in English and before December 2022 were included. Systematic reviews and meta-analyses were eligible if they investigated the effectiveness of one or more recovery strategies compared with a placebo or control group after a training session in endurance athletes. RESULTS: Twenty-two reviews (nine systematic reviews, three meta-analyses, and ten systematic reviews with meta-analyses included) met the inclusion criteria. In total, sixty-three studies with 1100 endurance athletes were included in our umbrella review. Out of the sixty-three studies, eight provided information on training recovery time frame for data synthesis. Among them, cryotherapy and compression garments showed positive effects, while applying massage showed no effect. In general, none of the included recovery strategies showed consistent benefits for endurance athletes. CONCLUSION: There is no particular recovery strategy that can be advised to enhance recovery between training sessions or competitions in endurance athletes. However, individual studies suggest that compression garments and cryotherapy are effective training recovery strategies. Further research should improve methodology and focus on the different time courses of the recovery process. REGISTRATION: The review protocol was registered with the International Prospective Register of Systematic Reviews with the number CRD42021260509.

Observe, Practice, and Improve? Enhancing Sidestep Cutting Execution in Talented Female Soccer Players: A Four-Week Intervention Program With Video Instruction.

ABSTRACT: Nijmeijer, EM, Kempe, M, Elferink-Gemser, MT, and Benjaminse A. Observe, practice and improve? Enhancing sidestep cutting (SSC) execution in talented female soccer players: A four-week intervention program with video instruction. J Strength Cond Res XX(X): 000-000, 2024-Implicit learning has the potential to improve movement execution and reduce injury risk. Previous research showed beneficial effects of short-term interventions with implicit learning in male athletes. However, research on long-term interventions in female athletes is lacking. The aim of this study was to examine the effects of a 4-week intervention with video instruction on movement execution of SSC, a task that is highly related with anterior cruciate ligament (ACL) injury risk, in female athletes. Twenty talented adolescent female soccer players were part of the control (CTRL, n = 10) or video instruction (VIDEO, n = 10) group. All subjects practiced 4 weeks and received general task instructions. In addition, the VIDEO group received expert video instruction during practice. Lower extremity kinematics and kinetics and vertical ground reaction force of SSC were examined during baseline, immediate post, and 1-week retention tests. After nonlinear registration, differences between each subject and the expert she had seen were determined. These differences were analyzed with SPM1D 2-way ANOVA. No interaction effects between time and group were found (p > 0.05). Main effects of time were found in the frontal plane. In particular, smaller deviations of subjects compared with the seen expert of the knee adduction (p = 0.005, 97.9-100% stance phase [SP]) and hip abduction (p = 0.005, 11.5-13.8% SP) and adduction (p < 0.001, 33.4-87.7% SP) moments were found in immediate post compared with baseline. These frontal plane short-term improvements, replicating earlier findings in both sexes, may lower ACL injury risk. The large observed interindividual differences over time may have concealed the long-term effects of video instruction at the group level.

The Success Factors of Rest Defense in Soccer - A Mixed-Methods Approach of Expert Interviews, Tracking Data, and Machine Learning.

While the tactical behavior of soccer players differs between specific phases of play (offense, defense, offensive transition, defensive transition), little is known about successful behavior of players during defensive transition (switching behavior from offense to defense). Therefore, this study aims to analyze the group tactic of rest defense (despite in ball possession, certain players safeguard quick counterattacks in case of ball loss) in defensive transition. A mixed-methods approach was used, involving both qualitative and quantitative analysis. Semi-structured expert interviews with seven professional soccer coaches were conducted to define rest defense. In the quantitative analysis, several KPIs were calculated, based on tracking and event data of 153 games of the 2020/21 German Bundesliga season, to predict the success of rest defense situations in a machine learning approach. The qualitative interviews indicated that rest defense can be defined as the positioning of the deepest defenders during ball possession to prevent an opposing counterattack after a ball loss. For instance, the rest defending players created a numerical superiority of 1.69 ± 1.00 and allowed a space control of the attacking team of 11.51 ± 9.82 [%] in the area of rest defense. The final machine learning model showed satisfactory prediction performance of the success of rest defense (Accuracy: 0.97, Precision: 0.73, f1-Score: 0.64, AUC: 0.60). Analysis of the individual KPIs revealed insights into successful behavior of players in rest defense, including controlling deep spaces and dangerous counterattackers. The study concludes regaining possession as fast as possible after a ball loss is the most important success factor in defensive transition.

The heat is on: Investigating the effect of psychological pressure on competitive performance in elite surfing.

Competitive sport often creates a high-stake and thus a high-pressure environment for its athletes. In the past, research has pointed to the negative effect that competitive pressure might have on skills and movement executions that have been perfected through prior practice. The Attentional Control Theory: Sport (ACTS) suggests that specifically high situational pressure and prior performance failures may negatively affect an athlete's subsequent performance. This study aimed to investigate the influence of situational pressure and previous performance errors on performance (i.e., wave score) in elite surfing while considering various contextual factors. A total of 6497 actions, performed by 80 elite surfers (female n = 28; male n = 52), were annotated based on video recordings of the 2019 World Championship Tour (WCT). A multi-level model was used to analyse the effect of pressure, previous errors and other contextual factors on the wave scores of individual surfers (i.e., events were nested within athletes). Partially confirming previous research, prior errors caused a significant decrease in surfing performance on the following ride. However, neither a significant effect of situational pressure on performance nor inter-individual differences in how prior-errors and situational pressure affected performance were found.

Capturing the Complex Relationship Between Internal and External Training Load: A Data-Driven Approach.

BACKGROUND: Training load is typically described in terms of internal and external load. Investigating the coupling of internal and external training load is relevant to many sports. Here, continuous kernel-density estimation (KDE) may be a valuable tool to capture and visualize this coupling. AIM: Using training load data in speed skating, we evaluated how well bivariate KDE plots describe the coupling of internal and external load and differentiate between specific training sessions, compared to training impulse scores or intensity distribution into training zones. METHODS: On-ice training sessions of 18 young (sub)elite speed skaters were monitored for velocity and heart rate during 2 consecutive seasons. Training session types were obtained from the coach's training scheme, including endurance, interval, tempo, and sprint sessions. Differences in training load between session types were assessed using Kruskal-Wallis or Kolmogorov-Smirnov tests for training impulse and KDE scores, respectively. RESULTS: Training impulse scores were not different between training session types, except for extensive endurance sessions. However, all training session types differed when comparing KDEs for heart rate and velocity (both P < .001). In addition, 2D KDE plots of heart rate and velocity provide detailed insights into the (subtle differences in) coupling of internal and external training load that could not be obtained by 2D plots using training zones. CONCLUSION: 2D KDE plots provide a valuable tool to visualize and inform coaches on the (subtle differences in) coupling of internal and external training load for training sessions. This will help coaches design better training schemes aiming at desired training adaptations.

The keys of pressing to gain the ball - Characteristics of defensive pressure in elite soccer using tracking data.

Recently, the availability of big amounts of data enables analysts to dive deeper into the constraints of performance in various team sports. While offensive analyses in football have been extensively conducted, the evaluation of defensive performance is underrepresented in this sport. Hence, the aim of this study was to analyze successful defensive playing phases by investigating the space and time characteristics of defensive pressure.Therefore, tracking and event data of 153 games of the German Bundesliga (second half of 2020/21 season) were assessed. Defensive pressure was measured in the last 10 seconds of a defensive playing sequence (time characteristic) and it was distinguished between pressure on the ball-carrier, pressure on the group (5 attackers closest to the ball), and pressure on the whole team (space characteristic). A linear mixed model was applied to evaluate the effect of success of a defensive play (ball gain), space characteristic, and time characteristic on defensive pressure.Defensive pressure is higher in successful defensive plays (14.47 ± 16.82[%]) compared to unsuccessful defensive plays (12.87 ± 15.31[%]). The characteristics show that defensive pressure is higher in areas closer to the ball (space characteristic) and the closer the measurement is to the end of a defensive play (time characteristic), which is especially true for successful defensive plays. Defensive pressure is a valuable key performance indicator for defensive play. Further, this study shows that there is an association between the pressing of the ball-carrier and areas close to the ball with the success of defensive play.

Shortcomings of applying data science to improve professional football performance: Takeaways from a pilot intervention study.

Positional tracking data allows football practitioners to derive features that describe patterns of player behavior and quantify performance. Existing research using tracking data has mostly focused on what occurred on the pitch, such as the determinants of effective passing. There have yet to be studies attempting to use findings from data science to improve performance. Therefore, 24 professional players (mean age = 21.6 years, SD = 5.7) were divided into a control team and an intervention team which competed against each other in a pre-test match. Metrics were gathered via notational analysis (number of passes, penalty box entries, shots on goal), and positional tracking data including pass length, pass velocity, defensive disruption (D-Def), and the number of outplayed opponents (NOO). D-Def and NOO were used to extract video clips from the pre-test that were shown to the intervention team as a teaching tool for 2 weeks prior to the post-test match. The results in the post-test showed no significant improvements from the pre-test between the Intervention Team and the Control Team for D-Def (F = 1.100, p = 0.308, η2 = 0.058) or NOO (F = 0.347, p = 0.563, η2 = 0.019). However, the Intervention Team made greater numerical increases for number of passes, penalty box entries, and shots on goal in the post-test match. Despite a positive tendency from the intervention, results indicate the transfer of knowledge from data science to performance was lacking. Future studies should aim to include coaches' input and use the metrics to design training exercises that encourage the desired behavior.

The "Hockey" Assist Makes the Difference-Validation of a Defensive Disruptiveness Model to Evaluate Passing Sequences in Elite Soccer.

With the growing availability of position data in sports, spatiotemporal analysis in soccer is a topic of rising interest. The aim of this study is to validate a performance indicator, namely D-Def, measuring passing effectiveness. D-Def calculates the change of the teams' centroid, centroids of formation lines (e.g., defensive line), teams' surface area, and teams' spread in the following three seconds after a pass and therefore results in a measure of disruption of the opponents' defense following a pass. While this measure was introduced earlier, in this study we aim to prove the usefulness to evaluate attacking sequences. In this study, 258 games of Dutch Eredivisie season 2018/19 were included, resulting in 13,094 attacks. D-Def, pass length, pass velocity, and pass angle of the last four passes of each attack were calculated and compared between successful and unsuccessful attacks. D-Def showed higher values for passes of successful compared to unsuccessful attacks (0.001 < p ≤ 0.029, 0.06 ≤ d ≤ 0.23). This difference showed the highest effects sizes in the penultimate pass (d = 0.23) and the maximal D-Def value of an attack (d = 0.23). Passing length (0.001 < p ≤ 0.236, 0.08 ≤ d ≤ 0.17) and passing velocity (0.001 < p ≤ 0.690, -0.09 ≤ d ≤ 0.12) showed inconsistent results in discriminating between successful and unsuccessful attacks. The results indicate that D-Def is a useful indicator for the measurement of pass effectiveness in attacking sequences, highlighting that successful attacks are connected to disruptive passing. Within successful attacks, at least one high disruptive action (pass with D-Def > 28) needs to be present. In addition, the penultimate pass ("hockey assist") of an attack seems crucial in characterizing successful attacks.

Early Prediction of Physical Performance in Elite Soccer Matches-A Machine Learning Approach to Support Substitutions.

Substitution is an essential tool for a coach to influence the match. Factors like the injury of a player, required tactical changes, or underperformance of a player initiates substitutions. This study aims to predict the physical performance of individual players in an early phase of the match to provide additional information to the coach for his decision on substitutions. Tracking data of individual players, except for goalkeepers, from 302 elite soccer matches of the Dutch 'Eredivisie' 2018-2019 season were used to enable the prediction of the individual physical performance. The players' physical performance is expressed in the variables distance covered, distance in speed category, and energy expenditure in power category. The individualized normalized variables were used to build machine learning models that predict whether players will achieve 100%, 95%, or 90% of their average physical performance in a match. The tree-based algorithms Random Forest and Decision Tree were applied to build the models. A simple Naïve Bayes algorithm was used as the baseline model to support the superiority of the tree-based algorithms. The machine learning technique Random Forest combined with the variable energy expenditure in the power category was the most precise. The combination of Random Forest and energy expenditure in the power category resulted in precision in predicting performance and underperformance after 15 min in a match, and the values were 0.91, 0.88, and 0.92 for the thresholds 100%, 95%, and 90%, respectively. To conclude, it is possible to predict the physical performance of individual players in an early phase of the match. These findings offer opportunities to support coaches in making more informed decisions on player substitutions in elite soccer.

Attacking Key Performance Indicators in Soccer: Current Practice and Perceptions from the Elite to Youth Academy Level.

Key Performance Indicators (KPIs) are used to evaluate the offensive success of a soccer team (e.g. penalty box entries) or player (e.g. pass completion rate). However, knowledge transfer from research to applied practice is understudied. The current study queried practitioners (n = 145, mean ± SD age: 36 ± 9 years) from 42 countries across different roles and levels of competition (National Team Federation to Youth Academy levels) on various forms of data collection, including an explicit assessment of twelve attacking KPIs. 64.3% of practitioners use data tools and applications weekly (predominately) to gather KPIs during matches. 83% of practitioners use event data compared to only 52% of practitioners using positional data, with a preference for shooting related KPIs. Differences in the use and value of metrics derived from positional tracking data (including Ball Possession Metrics) were evident between job role and level of competition. These findings demonstrate that practitioners implement KPIs and gather tactical information in a variety of ways with a preference for simpler metrics related to shots. The low perceived value of newer KPIs afforded by positional data could be explained by low buy-in, a lack of education across practitioners, or insufficient translation of findings by experts towards practice.

The tactics of successful attacks in professional association football: large-scale spatiotemporal analysis of dynamic subgroups using position tracking data.

Association football teams can be considered complex dynamical systems of individuals grouped in subgroups (defenders, midfielders and attackers), coordinating their behaviour to achieve a shared goal. As research often focusses on collective behaviour, or on static subgroups, the current study aims to analyse spatiotemporal behaviour of dynamic subgroups in relation to successful attacks. We collected position tracking data of 118 Dutch Eredivisie matches, containing 12424 attacks. Attacks were classified as successful (N = 1237) or non-successful (N = 11187) based on the potential of creating a scoring opportunity. Using unsupervised machine learning, we automatically identified dynamic formations based on position tracking data, and identified dynamic subgroups for every timeframe in a match. We then compared the subgroup centroids to assess the intra- and inter-team spatiotemporal synchronisation during successful and non-successful attacks, using circular statistics. Our results indicated subgroup-level variables provided more information, and were more sensitive to disruption, in comparison to team-level variables. When comparing successful and non-successful attacks, we found decreases (p < .01) in longitudinal inter- and intra-team synchrony of interactions involving the defenders of the attacking team during successful attacks. This study provides the first large-scale dynamic subgroup analysis and reveals additional insights to team-level analyses.

Not Every Pass Can Be an Assist: A Data-Driven Model to Measure Pass Effectiveness in Professional Soccer Matches.

In professional soccer, nowadays almost every team employs tracking technology to monitor performance during trainings and matches. Over the recent years, there has been a rapid increase in both the quality and quantity of data collected in soccer resulting in large amounts of data collected by teams every single day. The sheer amount of available data provides opportunities as well as challenges to both science and practice. Traditional experimental and statistical methods used in sport science do not seem fully capable to exploit the possibilities of the large amounts of data in modern soccer. As a result, tracking data are mainly used to monitor player loading and physical performance. However, an interesting opportunity exists at the intersection of data science and sport science. By means of tracking data, we could gain valuable insights in the how and why of tactical performance during a soccer match. One of the most interesting and most frequently occurring elements of tactical performance is the pass. Every team has around 500 passing interactions during a single game. Yet, we mainly judge the quality and effectiveness of a pass by means of observational analysis, and whether the pass reaches a teammate. In this article, we present a new approach to quantify pass effectiveness by means of tracking data. We introduce two new measures that quantify the effectiveness of a pass by means of how well a pass disrupts the opposing defense. We demonstrate that our measures are sensitive and valid in the differentiation between effective and less effective passes, as well as between the effective and less effective players. Furthermore, we use this method to study the characteristics of the most effective passes in our data set. The presented approach is the first quantitative model to measure pass effectiveness based on tracking data that are not linked directly to goal-scoring opportunities. As a result, this is the first model that does not overvalue forward passes. Therefore, our model can be used to study the complex dynamics of build-up and space creation in soccer.

"Good, better, creative": the influence of creativity on goal scoring in elite soccer.

This study investigated the level of creativity of goals scored in football. Therefore, all goals in the Football FIFA World Cup 2010 and 2014, as well as the Football UEFA Euro 2016 were qualitatively examined. Three Football experts evaluated the last eight actions before each goal using a creativity scale ranging from 0 to 10 (0 = not creative, 10 = highly creative) of all goals scored via open play (311 goals in 153 matches). Level of creativity was revealed using an Analysis of Variance and the frquency of high highly creative goals using a Kruskall- Wallis Test. The results showed that the closer the actions to a goal, the more creative they were evaluated. Teams that advanced to the later rounds of the tournament demonstrated greater creativity than teams that failed to do so. High creativity in the last two actions before the actual shot on goal proved to be the best predictor for game success. In conclusion, this study is the first one to show that creativity seems to be a factor for success in high level football. Thereby it provides an empirical basis for the ongoing debate on the importance of creativity training in football.

Naturalistic Assessment of Everyday Memory Performance Among Older Adults.

UNLABELLED: BACKGROUND/STUDY CONTEXT: Memory performance in everyday life (EDL) and its change through aging is still unclear because laboratory results are often not transferable to real-life situations. Therefore, a naturalistic memory task was designed to investigate memory performance in older adults in a representative task design. METHODS: The memory performance of 23 older (70.28 ± 4.65 years) and 20 younger adults (24.89 ± 3.16 years) was assessed by using four established tasks of short-term and working memory (Digit Simple Span, Digit Complex Span, Grid Simple Span, and Grid Complex Span) that differed in difficulty and domain (verbal vs. visual-spatial). To simulate an EDL context, a "Supermarket" was constructed within the laboratory. RESULTS: The results showed that memory performance presents alterations in older adults. This was especially true for the "Supermarket" task, in which the younger adults showed benefits in the common environment as opposed to older adults. A factor analysis showed that the four memory laboratory tasks measured different memory processes as compared with the EDL task. CONCLUSION: These findings suggest that memory performance in EDL is a different construct than when it is measured in the laboratory and that memory alterations in older adults are especially pronounced in EDL tasks. Following these findings, the authors recommend an EDL approach to measure memory performance further to the well-established laboratory approaches.

Motor imagery: effects of age, task complexity, and task setting.

UNLABELLED: BACKGROUND/STUDY CONTEXT: Mental training may potentially enhance motor performance and self-efficacy in older adults. However, several studies revealed an age-related decay of motor imagery (MI), which suggests that mental training might be too challenging for older adults. Recognizing that laboratory results are often not transferable to real-life situations, the purpose of the present study was to evaluate imagery performance in the elderly with a more real-life-like approach. METHODS: MI performance of 21 older (70.28 ± 4.65 years) and 19 younger adults (24.89 ± 3.16 years) was estimated by mental chronometry from the first-person perspective. Subjects were asked to walk in a supermarket scenario straight ahead (A), or with two changes of direction (B), or with two changes of direction while retrieving products (C). The three tasks were completed first in the subjects' imagination and then in reality, with time required as the dependent measure. MI ability was also assessed by the Controllability of Motor Imagery (CMI) test, in which subjects are required to mentally assume a sequence of body postures. RESULTS: Age-related alterations of MI were observed for walking only in Tasks B and C, and only in terms of intersubject variability, not in terms of across-subject means. This is in contrast to earlier studies that used a less realistic walking scenario and found an age-related decay even for MI means. Age-related alterations of CMI were observed as well, but they correlated little with those of walking. CONCLUSION: These findings suggest that MI is not a global phenomenon, as it decays in old age independently in the temporal and in the spatial domain, decays less with simple than with complex tasks, and less in an everyday-like than in a typical laboratory setting. These characteristics of MI should be taken into account when assessing its decay in old age, and when designing mental training for the elderly.

Detecting tactical patterns in basketball: comparison of merge self-organising maps and dynamic controlled neural networks.

The soaring amount of data, especially spatial-temporal data, recorded in recent years demands for advanced analysis methods. Neural networks derived from self-organizing maps established themselves as a useful tool to analyse static and temporal data. In this study, we applied the merge self-organising map (MSOM) to spatio-temporal data. To do so, we investigated the ability of MSOM's to analyse spatio-temporal data and compared its performance to the common dynamical controlled network (DyCoN) approach to analyse team sport position data. The position data of 10 players were recorded via the Ubisense tracking system during a basketball game. Furthermore, three different pre-selected plays were recorded for classification. Following data preparation, the different nets were trained with the data of the first half. The training success of both networks was evaluated by achieved entropy. The second half of the basketball game was presented to both nets for automatic classification. Both approaches were able to present the trained data extremely well and to detect the pre-selected plays correctly. In conclusion, MSOMs are a useful tool to analyse spatial-temporal data, especially in team sports. By their direct inclusion of different time length of tactical patterns, they open up new opportunities within team sports.