Blood-borne fatigue markers during major international football tournaments – a retrospective analysis of data from the FIFA World Championships and UEFA European Championships 2006 – 2016

Football Movement Profile-Based Creatine-Kinase Prediction Performs Similarly to Global Positioning System-Derived Machine Learning Models in National-Team Soccer Players

PURPOSE

The relationship between external load and creatine-kinase (CK) response at the team/position or individual level using Global Positioning Systems (GPS) has been studied. This study aimed to compare GPS-derived and Football Movement Profile (FMP) -derived CK-prediction models for national-team soccer players. The second aim was to compare the performance of general and individualized CK prediction models.

METHODS

Four hundred forty-four national-team soccer players (under 15 [U15] to senior) were monitored during training sessions and matches using GPS. CK was measured every morning from whole blood. The players had 19.3 (18.1) individual GPS-CK pairs, resulting in a total of 8570 data points. Machine learning models were built using (1) GPS-derived or (2) FMP-based parameters or (3) the combination of the 2 to predict the following days' CK value. The performance of general and individual-specific prediction models was compared. The performance of the models was described by R2 and the root-mean-square error (RMSE, in units per liter for CK values).

RESULTS

The FMP model (R2 = .60, RMSE = 144.6 U/L) performed similarly to the GPS-based model (R2 = .62, RMSE = 141.2 U/L) and the combination of the 2 (R2 = .62, RMSE = 140.3 U/L). The prediction power of the general model was better on average (R2 = .57 vs R2 = .37) and for 73% of the players than the individualized model.

CONCLUSIONS

The results suggest that FMP-based CK-prediction models perform similarly to those based on GPS-derived metrics. General machine learning models' prediction power was higher than those of the individual-specific models. These findings can be used to monitor postmatch recovery strategies and to optimize weekly training periodization.

Individual-Specific Relationship Between External Training and Match Load and Creatine-Kinase Response in Youth National Team Soccer Players

BACKGROUND

Previous studies have examined the relationship between external load and creatine-kinase (CK) response at the team level. This study aimed to build individualized CK prediction models for elite youth national team soccer players.

HYPOTHESIS

The CK response of youth soccer players can be categorized as being sensitive to micromovements (MM), high-velocity (HV) parameters, or the combination of both, measured during training sessions and matches.

STUDY DESIGN

Prospective cohort study.

LEVEL OF EVIDENCE

Level 4.

METHODS

A total of 25 U16-U17 youth national team soccer players were monitored during training sessions and matches using global positioning system (GPS) units. Individual CK values were measured every morning from whole blood. The data set consisted of 57 ± 17 individual datapoints per player. Individual prediction models were used to examine the relationship between external load and consecutive CK changes. Numerous models were built for each player using MM, HV parameters, or the combination of both. The performance of the models was described by the R2 and the root mean square error (RMSE, U/l for CK values).

RESULTS

The MM models were superior for 8 players (R2 = 0.68; RMSE = 113 U/l), followed by HV (8 players; R2 = 0.69; RMSE = 88 U/l) and the combined models (2 players; R2 = 0.64; RMSE = 141 U/l). For the remaining 7 players, the R2 of the models was <0.5. The recovery time between efforts was more important in the HV model.

CONCLUSION

Players could be categorized on sensitivity to MM, HV movements, or the combination of both.

CLINICAL RELEVANCE

These findings can be used to individualize postmatch recovery strategies and to optimize weekly training periodization to maximize match performance.

Individualised reference ranges for markers of muscle recovery assessment in soccer

Recently an individualisation algorithm has been developed and shown to significantly improve the diagnostic accuracy of creatine kinase (CK) and urea in endurance sports and Badminton. In this study, the applicability and benefit of this algorithm was evaluated using repeated measures data from 161 professional German soccer players monitored during the 2015-2017 seasons. Venous blood samples were collected after a day off (recovered state) and after a minimum of two strenuous training sessions within 48 h (non-recovered state) and analysed for CK and urea. Group-based reference ranges were derived from that same dataset to ensure the best possible reference for comparison. A z-test was conducted to analyse differences in error rates between individualised and group-based classifications. CK values for the individualised approach showed significantly lower error rates in the assessment of muscle recovery compared to both a population-based (p < .001; z-value: -17.01; test-pass error rate: 21 vs. 67%; test-fail: 19 vs. 64%) and a group-based cut-off (p < .001; z-value: -15.29; test-pass error rate: 65%; test-fail: 67%). It could be concluded that the assessment of muscle recovery in soccer using individualised interpretations of blood-borne markers may offer higher diagnostic accuracy than a population-based and a sample-specific group-based approach.HighlightsAssessing muscle recovery via CK using individualised ranges seems to offer a higher diagnostic accuracy than a sample-specific group-based analysis.Using an individualised algorithm seems to be a promising approach to overcome diagnostic problems arising from large inter- and intraindividual variability in blood parameters as it significantly improved the diagnostic accuracy of CK as a recovery marker.As recovery assessment in elite soccer ultimately aims at the accurate detection of differences in the individual player this algorithm seems to offer coaches and sport scientists a more sensitive approach compared to group-specific evaluations.

Blood-Based Biomarkers for Managing Workload in Athletes: Considerations and Recommendations for Evidence-Based Use of Established Biomarkers

Blood-based biomarkers can provide an objective individualized measure of training load, recovery, and health status in order to reduce injury risk and maximize performance. Despite enormous potentials, especially owing to currently evolving technology, such as point-of-care testing, and advantages, in terms of objectivity and non-interference with the training process, there are several pitfalls in the use and interpretation of biomarkers. Confounding variables such as preanalytical conditions, inter-individual differences, or an individual chronic workload can lead to variance in resting levels. In addition, statistical considerations such as the detection of meaningful minimal changes are often neglected. The lack of generally applicable and individual reference levels further complicates the interpretation of level changes and thus load management via biomarkers. Here, the potentials and pitfalls of blood-based biomarkers are described, followed by an overview of established biomarkers currently used to support workload management. Creatine kinase is discussed in terms of its evidence for workload management to illustrate the limited applicability of established markers for workload management to date. We conclude with recommendations for best practices in the use and interpretation of biomarkers in a sport-specific context.

Where do you go when your periods go?: A case-study examining secondary amenorrhea in a professional internationally-capped female soccer player through the lens of the sport nutritionist

This case study follows a professional internationally capped female soccer player's two-year journey from eumenorrhea, through injury, to amenorrhea, and the challenges faced by the player and nutritionist. The two years are split into three sections: (Areta et al. 2013) longitudinal profiling of the player, (Baker et al. 2020) nutrition to support her return from injury, and (Beato et al. 2018) investigation into the observed secondary amenorrhea. The cause of amenorrhea was investigated through the assessment of energy availability via doubly labelled water, remote food photography, blood biomarkers and resting metabolic rate. Despite having secondary amenorrhea and anovulatory cycles, the player did not have low energy availability. This study shows the importance for practitioner's, particularly nutritionists, to not assume that all menstrual irregularities are caused by low energy availability and could be caused by a combination of factors (e.g., clinical, physiological, and psychological), which requires a multi-disciplinary investigation and intervention team. This study also showed that education needs to be provided about menstrual health to elite female soccer players as the player (i) believed that not having a period was beneficial for performance and unsure of possible health implications; (ii) was convinced that a one-day bleed indicated a regular menstrual cycle; and (iii) was reluctant to waste the practitioners time discussing menstrual issues and was nervous of finding out if she had an actual health issue. It is therefore crucial that players feel comfortable in discussing their menstrual status with practitioners to support their performance and long-term health.

Running Performance of High-Level Soccer Player Positions Induces Significant Muscle Damage and Fatigue Up to 24 h Postgame

This study aimed to determine the impact of a soccer game on the creatine kinase (Ck) response and recovery and the specific Global Positioning System (GPS)-accelerometry-derived performance analysis during matches and comparing playing positions. A sample composed of 118 observations of 24 professional soccer teams of the Brazil League Serie A was recruited and classified according to playing positions, i.e., Left/Right Defenders (D = 30, age: 25.2 ± 5.8 years, height: 187 ± 5.5 cm, weight: 80 ± 5.8 kg), Offensive Midfielders (OM = 44, age: 25.1 ± 0.2 years, height: 177 ± 0.3 cm, weight: 73 ± 1.2 kg), Forwards (F = 9, age: 25.1 ± 0.2 years, height: 176.9 ± 4.3 cm, weight: 74.5 ± 2.1 kg), Left/Right Wingers (M = 23, age: 24.5 ± 0.5 years, height: 175 ± 1.1 cm, weight: 74 ± 4.4 kg), and Strikers (S = 12, age: 28 ± 0.2 years, height: 184 ± 1.0 cm, weight: 80 ± 1.4 kg). Blood Ck concentration was measured pre-, immediately post-, and 24 h postgame, and the GPS-accelerometry parameters were assessed during games. Findings demonstrated that Ck concentrations were higher at all postgame moments when compared with pregame, with incomplete recovery markers being identified up to 24 h after the game (range: 402–835 U/L). Moreover, Midfielders (108.6 ± 5.6 m/min) and Forwards (109.1 ± 8.3 m/min) had a higher relative distance vs. other positions (100.9 ± 10.1 m/min). Strikers [8.2 (8.1, 9.05) load/min] and Defenders [8.45 (8, 8.8) load/min] demonstrated lower load/min than Wingers [9.5 (9.2, 9.8) load/min], Midfielders [10.6 (9.9, 11.67) load/min], and Forwards [11 (10.65, 11, 15) load/min]. These results could be used to adopt specific training programs and recovery strategies after match according to the playing positions.

Factors Influencing Creatine Kinase Response in Youth National Team Soccer Players

BACKGROUND

Previous studies have examined the relationship between external training load and creatine kinase (CK) response after soccer matches in adults. This study aimed to build training- and match-specific CK prediction models for elite youth national team soccer players.

HYPOTHESIS

Training and match load will have different effects on the CK response of elite youth soccer players, and there will be position-specific differences in the most influential external and internal load parameters on the CK response.

STUDY DESIGN

Prospective cohort study.

LEVEL OF EVIDENCE

Level 4.

METHODS

Forty-one U16-U17 youth national team soccer players were measured over an 18-month period. Training and match load were monitored with global positioning system devices. Individual CK values were measured from whole blood every morning in training camps. The dataset consisted of 1563 data points. Clustered prediction models were used to examine the relationship between external/internal load and consecutive CK changes. Clusters were built based on the playing position and activity type. The performance of the linear regression models was described by the R² and the root-mean-square error (RMSE, U/L for CK values).

RESULTS

The prediction models fitted similarly during games and training sessions (R² = 0.38-0.88 vs 0.6-0.77), but there were large differences based on playing positions. In contrast, the accuracy of the models was better during training sessions (RMSE = 81-135 vs 79-209 U/L). Position-specific differences were also found in the external and internal load parameters, which best explained the CK changes.

CONCLUSION

The relationship between external/internal load parameters and CK changes are position specific and might depend on the type of session (training or match). Morning CK values also contributed to the next day's CK values.

CLINICAL RELEVANCE

The relationship between position-specific external/internal load and CK changes can be used to individualize postmatch recovery strategies and weekly training periodization with a view to optimize match performance.