Training load monitoring in soccer : the dose-response relationships with fitness, recovery and fatigue

The congested fixture schedules in elite soccer leagues around the world has bought the issue of recovery between games and subsequent performance to the fore in soccer related research. Studies have described the time-course of recovery for numerous biochemical and physiological measures of performance, fatigue and recovery from match-play. However, the research also suggests that there is individual variation in the external load both between players and between matches. The external load measured as distance in match-play has been shown to vary by ~30% between games. However it is the internal training load that will determine the magnitude of the physiological responses on an individual basis. Therefore the major aim of this thesis was to examine the dose-response relationships between measures of training load and the physiological and biochemical responses used as markers of recovery from match-play. The thesis also assessed the relationships between these proposed markers of recovery and soccer specific performance.In meeting the aims of the thesis a number of preliminary studies were conducted. The study in section 3 assesses the extent of fixture congestion in the English Premier League. The results showed over 30% of games for the most successful teams are played with 3 days recovery time, justifying the need for investigating recovery from soccer match-play. Given the variation in soccer match-play section 4 examines the reliability and validity of the modified BEAST90 soccer simulation. A measure of performance with less variance would allow changes in soccer specific performance to be identified with greater certainty in section 7. Section 5 assesses the influence of intermittent exercise on the blood lactate response. Given that the new iTRIMP method of measuring internal training load weights exertion with the blood lactate response it was important to assess the influence exercise mode may have on the calculation of internal training load. The results showed that at higher intensities intermittent exercise produced significantly higher blood lactate responses. Section 6 assesses the dose-response relationships between training and fitness using numerous measures of internal training load over a 6 week training period. The results showed only the iTRIMP method showed a significant relationship with changes in fitness. Section 7 assesses the dose-response relationships between exertion in soccer match-play and various physiological measures of fatigue and recovery. The relationships between these measures and changes in soccer specific performance were also assessed. Finally the internal and external load were integrated and the relationships of this ratio assessed with measures of fitness and performance. The results showed that changes in any of the physiological and biochemical measures used to assess recovery did not relate to changes in performance with the exception of testosterone which showed significant positive relationships with changes in distance covered from the 1st trial of the modified BEAST protocol to 2nd. Testosterone also was the only measure to show a significant relationship during the recovery period with any measure of training load (sRPE). Finally, the novel findings of this thesis is the relationships between the integrated ratio’s of internal and external training load with measures of aerobic fitness is also presented in section 7.The studies provided in this thesis have made a major contribution in demonstrating how data that is routinely collected at elite levels of soccer can be used more appropriately. It has also shown limitations of some the methods currently employed to measure training load. Furthermore changes in many of the markers used to assess recovery of soccer players do not seem to relate to changes in soccer specific performance. This may point to a change in paradigm which is required in both research and practice

The Integration of Internal and External Training Load Metrics in Hurling

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 Integration of Internal and External Training Load Metrics in Hurling

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

Training intensity distribution in road cyclists: objective versus subjective measures

Purpose: This study aims to evaluate training intensity distribution using different intensity measures based on session rating of perceived exertion (sRPE), heart rate (HR) and power output (PO) in well-trained cyclists. Methods: Fifteen road cyclists participated in the study. Training data was collected during a 10-week training period. Training intensity distribution was quantified using HR, PO and sRPE categorized in a 3-zone training intensity model. Three zones for HR and PO were based around a first and second lactate threshold. The three sRPE zones were defined using a 10-point scale: zone 1, sRPE scores 1-4; zone 2, sRPE scores 5-6; zone 3, sRPE scores 7-10. Results: Training intensity distribution as percentages of time spent in zone 1, zone 2 and zone 3 was moderate to very largely different for sRPE (44.9%, 29.9%, 25.2%) compared to HR (86.8%, 8.8%, 4.4%) and PO (79.5%, 9.0%, 11.5%). Time in zone 1 quantified using sRPE was large to very largely lower for sRPE compared to PO (P < 0.001) and HR (P < 0.001). Time in zone 2 and zone 3 was moderate to very largely higher when quantified using sRPE compared to intensity quantified using HR (P < 0.001) and PO (P < 0.001). Conclusions: Training intensity distribution quantified using sRPE demonstrates moderate to very large differences compared to intensity distributions quantified based on HR and PO. The choice of intensity measure impacts on the intensity distribution and has implications for training load quantification, training prescription and the evaluation of training characteristics

The dose-response relationship between training load and aerobic fitness in academy rugby union players

© 2018 Human Kinetics, Inc. Purpose: To identify the dose-response relationship between measures of training load (TL) and changes in aerobic fitness in academy rugby union players. Method: Training data from 10 academy rugby union players were collected during a 6-wk in-season period. Participants completed a lactate-threshold test that was used to assess VO 2 max, velocity at VO 2 max, velocity at 2 mmol/L (lactate threshold), and velocity at 4 mmol/L (onset of lactate accumulation; vOBLA) as measures of aerobic fitness. Internal-TL measures calculated were Banister training impulse (bTRIMP), Edwards TRIMP, Lucia TRIMP, individualized TRIMP (iTRIMP), and session RPE (sRPE). External-TL measures calculated were total distance, PlayerLoad™, high-speed distance > 15 km/h, very-high-speed distance > 18 km/h, and individualized high-speed distance based on each player’s vOBLA. Results: A second-order-regression (quadratic) analysis found that bTRIMP (R 2 = .78, P = .005) explained 78% of the variance and iTRIMP (R 2 = .55, P = .063) explained 55% of the variance in changes in VO 2 max. All other HR-based internal-TL measures and sRPE explained less than 40% of variance with fitness changes. External TL explained less than 42% of variance with fitness changes. Conclusions: In rugby players, bTRIMP and iTRIMP display a curvilinear dose-response relationship with changes in maximal aerobic fitness

The integration of internal and external training load metrics in hurling

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 validity of external: internal training load ratios in rested and fatigued soccer players

Purpose: To examine the relationship of external:internal training load ratios with fitness and assess the impact of fatigue. Method: Ten soccer players performed a lactate threshold test followed by two soccer simulations (BEAST90mod ) 48 h apart. Recovery (TQR) and muscle soreness (DOMS) was measured before each trial. Internal Training load (TL) (iTRIMP) and external load total distance (TD), high intensity distance (HID), PlayerLoad™ (PL) mean metabolic power (MMP) high metabolic power distance (HP) were collected for each trial and external:internal ratios produced. The relationships between ratios and velocity at lactate threshold (vLT) and velocity at Onset of Blood Lactate Accumulation (vOBLA) were examined in both trials along with changes in ratios. Results: Total Quality of Recovery and DOMS showed large changes. There were trivial to large decreases in TL from trial 1 to 2. Moderate increases in ratios for TD:iTRIMP, PL:iTRIMP and MMP:iTRIMP were seen but only small/trivial for HP:iTRIMP and HID:iTRIMP. In rested conditions all ratios show large relationships with vLT and vOBLA. However vLT vs. HID:iTRIMP; PL:iTRIMP; HP:iTRIMP and vOBLA vs. TD:iTRIMP; PL:iTRIMP; MMP:iTRIMP became weaker under fatigue. Conclusions: Acute changes in the ratios have implications forthe use of ratios as fitness measures but also as indicators of fatigue

A field-based cycling test to assess predictors of endurance performance and establishing training zones

This study evaluates the relationship between a field-based 8-min time trial (8MTT) and physiological endurance variables assessed with an incremental laboratory test. Secondly, lactate thresholds assessed in the laboratory were compared to estimated functional threshold power (FTP) from the 8MTT. Nineteen well-trained road cyclists (aged 22 +/- 2 yr, height 185.9 +/- 4.5 cm, weight 72.8 +/- 4.6 kg, VO2max 64 +/- 4 ml[middle dot]min-1[middle dot]kg-1) participated. Linear regression revealed that mean 8MTT power output (PO) was strongly to very strongly related to PO at 4 mmol[BULLET OPERATOR]L-1, PO at initial rise of 1.00 mmol[BULLET OPERATOR]L-1, PO at Dmax and modified (mDmax) (r = 0.61 - 0.82). Mean 8MTT PO was largely to very largely different compared to PO at fixed blood lactate concentration (FBLC) of 2 mmol[middle dot]L-1 (ES = 3.20) and 4 mmol[middle dot]L-1 (ES = 1.90), PO at initial rise 1.00 mmol[BULLET OPERATOR]L-1 (ES = 2.33), PO at Dmax (ES = 3.47) and mDmax (ES = 1.79) but only trivially different from maximal power output (Wmax) (ES = 0.09). The 8MTT based estimated FTP was moderate to very largely different compared to PO at initial rise of 1 mmol[BULLET OPERATOR]L-1 (ES = 1.37), PO at Dmax (ES = 2.42), PO at mDmax (ES = 0.77) and PO at 4 mmol[BULLET OPERATOR]L-1(ES = 0.83). Therefore, even though the 8MTT can be valuable as a performance test in cycling shown through its relationships with predictors of endurance performance, coaches should be cautious when using FTP and PO at laboratory-based thresholds interchangeably to inform training prescription

The Relationship between Training Load Measures and Next-Day Well-Being in Rugby Union Players

The aim of this study is to identify the relationship between different internal and external load measures and next day subjective wellbeing. With institutional ethics approval, ten academy rugby union players (Five forwards, and five backs) with a local National League One club agreed to participate in the study (aged; 18.4 ± 1.0 years, height; 181.3 ± 5.9 cm, body mass 85.9 ± 13.0 kg, VO2max 56.2 ± 6.8 mL·kg−1·min−1). Before the 6-week in-season data collection period, participants completed an incremental treadmill test to determine lactate thresholds at 2 mmol·L−1 (LT) and 4 mmol·L−1 and the heart rate blood lactate (HR-BLa) profile for individualized training impulse (iTRIMP) calculations. Internal training load was quantified using Banister’s TRIMP, Edward’s TRIMP, Lucia’s TRIMP, individualised TRIMP and session-RPE. External training load was reported using total distance, PlayerLoadTM, high-speed distances (HSD) > 18 km∙h−1 and >15 km∙h−1, and individualized high-speed distance (iHSD) based on each player’s velocity at OBLA. On arrival and prior to all training sessions players completed a well-being questionnaire (WB). Bayesian linear mixed model analysis identified that a range of internal and external load measures explained between 30% and 37% of next-day total wellbeing and between 65% and 67% of next-day perceived stress. All other internal and external load measures demonstrated very weak to moderate relationships (R2 = 0.08 to 0.39) with all other wellbeing components. Internal sRPE, iTRIMP and bTRIMP loads alongside external HSD loads provide coaches with the most practical measures to influence players’ perceived wellbeing