Monitoring Training Load to Understand Fatigue in Athletes

Abstract

Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.

Post-Match Changes in Muscle Damage Markers among U-21 Soccer Players

“…Our data show much higher values compared to the upper reference value (270 UI/L), for the general population (Mougios, 2007). Furthermore, the high variability of the measure of CK activity must also be taken into account (Halson, 2014), which was the case in this study. Research conducted on elite soccer players has also reported large variability in CK levels (Meister, Faude, Ammann, Schnittker, & Meyer, 2013).…”

Match Running Performance During Fixture Congestion in Elite Soccer: Research Issues and Future Directions

“…Any holistic approach must also take into consideration the aforementioned performance-related and contextual factors recognised as affecting match-play performance. In addition, while no definitive marker exists for monitoring biochemical, hormonal and immunological responses to exercise [31], there is still potential for research merging this information with external workload information derived from time-motion analyses. First-hand accounts from the players themselves providing subjective ratings of perceived exertion, muscle soreness, wellness and sleep quality could also aid interpretation of variations in match performance.…”

Validity and reliability of 6-a-side small-sided game locomotor performance in assessing physical fitness in football players

“…the Yo-Yo tests (Krustrup et al, 2006). However, during the competitive season in professional settings maximal fitness tests are usually not employed (Halson, 2014). Besides fitness tests, time-motion analysis of both matches and SSGs in training could perhaps provide additional information about football-specific fitness.…”

“…Indeed, many studies found positive correlations between aerobic fitness tests and match locomotor performance assessed as (high intensity) distance covered (Buchheit, Mendez-Villanueva, Simpson, & Bourdon, 2010;Castagna, Impellizzeri, Cecchini, Rampinini, & Alvarez, 2009;Castagna, Manzi, Impellizzeri, Weston, & Barbero Alvarez, 2010;Krustrup et al, 2003;Rampinini et al, 2007a;Rebelo, Brito, Seabra, Oliveira, & Krustrup, 2014) or estimated metabolic power (Manzi et al, 2014). However, in team sports, maximal (physical) performance is difficult to define during an actual match (Halson, 2014), as it is influenced by many factors such as player position, score line, opposition and tactics (Carling, 2013). Unlike matches, SSGs can be better standardised, locomotor performance is less position dependent and there is more continuous play.…”