The Integration of Internal and External Training Load Metrics in Hurling

Abstract

The current study aimed to assess the relationship between the hurling player’s fitness profile and integrated training load (TL) metrics. Twenty-five hurling players performed treadmill testing for VO2max, the speed at blood lactate concentrations of 2 mmol•L-1 (vLT) and 4 mmol•L-1 (vOBLA) and the heart rate-blood lactate profile for calculation of individual training impulse (iTRIMP). The total distance (TD; m), high speed distance (HSD; m) and sprint distance (SD; m) covered were measured using GPS technology (4-Hz, VX Sport, Lower Hutt, New Zealand) which allowed for the measurement of the external TL. The external TL was divided by the internal TL to form integration ratios. Pearson correlation analyses allowed for the assessment of the relationships between fitness measures and the ratios to performance during simulated match play. External measures of the TL alone showed limited correlations with fitness measures. Integrated TL ratios showed significant relationships with fitness measures in players. TD:iTRIMP was correlated with aerobic fitness measures VO2max (r = 0.524; p = 0.006; 95% CI: 0.224 to 0.754; large) and vOBLA (r = 0.559; p = 0.003; 95% CI: 0.254 to 0.854; large). HSD:iTRIMP also correlated with aerobic markers for fitness vLT (r = 0.502; p = 0.009; 95% CI: 0.204 to 0.801; large); vOBLA (r = 0.407; p = 0.039; 95% CI: 0.024 to 0.644; moderate). Interestingly SD:iTRIMP also showed significant correlations with vLT (r = 0.611; p = 0.001; 95% CI: 0.324 to 0.754; large). The current study showed that TL ratios can provide practitioners with a measure of fitness as external performance alone showed limited relationships with aerobic fitness measures.

The Use of Small-Sided Games as an Aerobic Fitness Assessment Supplement within Elite Level Professional Soccer

“…the integration of the individualised heart rate (internal load) with distance measure (external load) during SSGs. In line with recent literature in this area, an © Editorial Committee of Journal of Human Kinetics additional strength of this particular investigation is the fact that this protocol may aid the identification of fitness changes and possibly counteract the potential impact of player pacing on external load variables (Akubat et al, 2014;Malone et al, 2016;Taylor et al, 2018). Given that improved aerobic fitness has been shown to reduce the odd risk of lower limb non-contact injury within soccer cohorts, and the observed associations between 5 vs. 5 SSGs and the Yo-YoIR1, future research may aim to best ascertain the number of exposures to 5 vs. 5 SSGs that result in improved aerobic fitness and whether this improvement is associated with reduced likelihood of players sustaining lower limb noncontact injuries.…”

“…All devices were always activated 15 minutes before the data collection to allow acquisition of satellite signals in accordance with the manufacturer's instructions. In addition, to avoid inter-unit error, each player wore the same GPS device for each training session (Malone et al, 2016) After recording, the data were downloaded to a computer and analysed using the software package Viper version (STATSports, Viper, System). Based on GPS data, total, high-speed (>19.8 km•h -1 ) and sprint distance (>25.5 km•h -1 ), as well as average metabolic power (W•kg -1 ), high metabolic power distance (m; ≥ 20 W•kg -1 ), accelerations (n; ≥ 3.3 m•s -2 ), decelerations (n; ≥ -3.3 m•s -2 ) and the dynamic stress load (AU) were calculated during each training session.…”

“…The demands of soccer match-play have been reported (Casamichana et al, 2012;Malone et al, 2016;Taylor et al, 2018). During official games players complete between 9 and 14 km (Manzi et al, 2014;Osgnach et al, 2010), with a high proportion of distance covered jogging and walking (Manzi et al, 2014).…”

High-speed running and sprinting as an injury risk factor in soccer: Can well-developed physical qualities reduce the risk?

“…Unfortunately, it was not possible to describe the external and subjective training loads of specific session types within the current study. Additionally, there is a need to assess the utility of external:internal load ratios as a potential metric for injury risk assessment given the known relationship between these ratios and fitness in team sport athletes (29,30) . Finally, the model developed within the current investigation will be best suited to the population from which it is derived (16,19) .…”

The Relationships Between Internal and External Measures of Training Load and Intensity in Team Sports: A Meta-Analysis

“…Specifically, changes in internal load with respect to a standard external load may be used to infer on an athletes fitness or fatigue over time or in comparison to their peers [14]. The simplicity of using an external:internal load ratio to provide a normalised metric that may be indicative of fitness or fatigue is conceptually appealing [83,[96][97][98][99] [103,104] that is inherent to training and competition in team sports [33,51]. For the retrospective analyses of larger datasets, we again recommend that ratios are avoided and that practitioners seek to explore their data through more appropriate means.…”