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Jill Borresen and Michael I. Lambert

Purpose:

To establish the relationship between a subjective (session rating of perceived exertion [RPE]) and 2 objective (training impulse [TRIMP]) and summated-heart-rate-zone (SHRZ) methods of quantifying training load and explain characteristics of the variance not accounted for in these relationships.

Methods:

Thirty-three participants trained ad libitum for 2 wk, and their heart rate (HR) and RPE were recorded to calculate training load. Subjects were divided into groups based on whether the regression equations over- (OVER), under- (UNDER), or accurately predicted (ACCURATE) the relationship between objective and subjective methods.

Results:

A correlation of r = .76 (95% CI: .56 to .88) occurred between TRIMP and session-RPE training load. OVER spent a greater percentage of training time in zone 4 of SHRZ (ie, 80% to 90% HRmax) than UNDER (46% ± 8% vs 25% ± 10% [mean ± SD], P = .008). UNDER spent a greater percentage of training time in zone 1 of SHRZ (ie, 50% to 60% HRmax) than OVER (15% ± 8% vs 3% ± 3%, P = .005) and ACCURATE (5% ± 3%, P = .020) and more time in zone 2 of SHRZ (ie, 60% to 70%HRmax) than OVER (17% ± 6% vs 7% ± 6%, P = .039). A correlation of r = .84 (.70 to .92) occurred between SHRZ and session-RPE training load. OVER spent proportionally more time in Zone 4 than UNDER (45% ± 8% vs 25% ± 10%, P = .018). UNDER had a lower training HR than ACCURATE (132 ± 10 vs 148 ± 12 beats/min, P = .048) and spent more time in zone 1 than OVER (15% ± 8% vs 4% ± 3%, P = .013) and ACCURATE (5% ± 3%, P = .015).

Conclusions:

The session-RPE method provides reasonably accurate assessments of training load compared with HR-based methods, but they deviate in accuracy when proportionally more time is spent training at low or high intensity.

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Anthony N. Turner, Conor Buttigieg, Geoff Marshall, Angelo Noto, James Phillips and Liam Kilduff

Session rating of perceived exertion (sRPE) is known to significantly relate to heart-rate (HR) -based methods of quantifying internal training load (TL) in a variety of sports. However, to date this has not been investigated in fencing and was therefore the aim of this study. TL was calculated by multiplying the sRPE with exercise duration and through HR-based methods calculated using Banister and Edwards TRIMP. Seven male elite foil fencers (mean ± SD age 22.3 ± 1.6 y, height 181.3 ± 6.5 cm, body mass 77.7 ± 7.6 kg) were monitored over the period of 1 competitive season. The sRPE and HR of 67 training sessions and 3 competitions (87 poule bouts and 12 knockout rounds) were recorded and analyzed. Correlation analysis was used to determine any relationships between sRPE- and HR-based methods, accounting for individual variation, mode of training (footwork drills vs sparring sessions), and stage of competition (poules vs knockouts). Across 2 footwork sessions, sRPE and Banister and Edwards TRIMP were found to be reliable, with coefficient of variation values of 6.0%, 5.2%, and 4.5%, respectively. Significant correlations with sRPE for individual fencers (r = .84–.98) and across mode of exercise (r = .73–.85) and competition stages (r = .82–.92) were found with HR-based measures. sRPE is a simple and valuable tool coaches can use to quantify TL in fencing.

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Trent Stellingwerff

Laboratory-based studies demonstrate that fueling (carbohydrate; CHO) and fluid strategies can enhance training adaptations and race-day performance in endurance athletes. Thus, the aim of this case study was to characterize several periodized training and nutrition approaches leading to individualized race-day fluid and fueling plans for 3 elite male marathoners. The athletes kept detailed training logs on training volume, pace, and subjective ratings of perceived exertion (RPE) for each training session over 16 wk before race day. Training impulse/load calculations (TRIMP; min × RPE = load [arbitrary units; AU]) and 2 central nutritional techniques were implemented: periodic low-CHO-availability training and individualized CHO- and fluidintake assessments. Athletes averaged ~13 training sessions per week for a total average training volume of 182 km/wk and peak volume of 231 km/wk. Weekly TRIMP peaked at 4,437 AU (Wk 9), with a low of 1,887 AU (Wk 16) and an average of 3,082 ± 646 AU. Of the 606 total training sessions, ~74%, 11%, and 15% were completed at an intensity in Zone 1 (very easy to somewhat hard), Zone 2 (at lactate threshold) and Zone 3 (very hard to maximal), respectively. There were 2.5 ± 2.3 low-CHO-availability training bouts per week. On race day athletes consumed 61 ± 15 g CHO in 604 ± 156 ml/hr (10.1% ± 0.3% CHO solution) in the following format: ~15 g CHO in ~150 ml every ~15 min of racing. Their resultant marathon times were 2:11:23, 2:12:39 (both personal bests), and 2:16:17 (a marathon debut). Taken together, these periodized training and nutrition approaches were successfully applied to elite marathoners in training and competition.

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Miguel Angel Campos-Vazquez, Alberto Mendez-Villanueva, Jose Antonio Gonzalez-Jurado, Juan Antonio León-Prados, Alfredo Santalla and Luis Suarez-Arrones

Purpose:

To describe the internal training load (ITL) of common training sessions performed during a typical week and to determine the relationships between different indicators of ITL commonly employed in professional football (soccer).

Methods:

Session-rating-of-perceived-exertion TL (sRPE-TL) and heart-rate- (HR) derived measurements of ITL as Edwards TL and Stagno training impulses (TRIMPMOD) were used in 9 players during 3 periods of the season. The relationships between them were analyzed in different training sessions during a typical week: skill drills/circuit training + small-sided games (SCT+SSGs), ball-possession games + technical-tactical exercises (BPG+TTE), tactical training (TT), and prematch activation (PMa).

Results:

HR values obtained during SCT+SSGs and BPG+TTE were substantially greater than those in the other 2 sessions, all the ITL markers and session duration were substantially greater in SCT+SSGs than in any other session, and all ITL measures in BPG+TTE were substantially greater than in TT and PMa sessions. Large relationships were found between HR >80% HRmax and HR >90% HRmax vs sRPE-TL during BPG+TTE and TT sessions (r = .61−.68). Very large relationships were found between Edwards TL and sRPE-TL and between TRIMPMOD and sRPE-TL in sessions with BPG+TTE and TT (r = .73−.87). Correlations between the different HR-based methods were always extremely large (r = .92−.98), and unclear correlations were observed for other relationships between variables.

Conclusion:

sRPE-TL provided variable-magnitude within-individual correlations with HR-derived measures of training intensity and load during different types of training sessions typically performed during a week in professional soccer. Caution should be applied when using RPE- or HR-derived measures of exercise intensity/load in soccer training interchangeably.

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Jose A. Rodríguez-Marroyo and Carlos Antoñan

Purpose:

The purpose of this study was to examine the concurrent and construct validity of the Borg (0–10) and children’s OMNI scales for quantifying the exercise intensity and training load (TL) in youth soccer players.

Methods:

Twelve children (mean ± SD age 11.4 ± 0.5 y, height 154.3 ± 6.5 cm, body mass 39.5 ± 5.4 kg) took part in this study. Exercise intensity and TL were calculated on the basis of the session rating of perceived exertion (sRPE) and heart rate (HR; Edwards method) during 20 technical-tactical training sessions. Players’ sRPEs were obtained from the Borg and OMNI scales.

Results:

Low correlations between HR-based TL and sRPE TL based on the Borg (r = .17, P = .335) and OMNI (r = .34, P = .007) scales were obtained. Significant (P < .001) relationships in sRPE (r = .76) and TL (r = .79) between RPE scales were found.

Conclusion:

The current data do not support the relationship between the sRPE and HR methods for quantifying TL in youth soccer players. However, the sRPE method could be considered a better indicator of global internal TL, since sRPE is a measure of both physical and psychological stress. In addition, the authors demonstrated the construct validity for the OMNI scale to control exercise demands.

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Ben T. Stephenson, Eleanor Hynes, Christof A. Leicht, Keith Tolfrey and Victoria L. Goosey-Tolfrey

Purpose: To gain an exploratory insight into the relation between training load (TL), salivary secretory immunoglobulin A (sIgA), and upper respiratory tract illness (URI) in elite paratriathletes. Methods: Seven paratriathletes were recruited. Athletes provided weekly saliva samples for the measurement of sIgA over 23 consecutive weeks (February to July) and a further 11 consecutive weeks (November to January). sIgA was compared to individuals’ weekly training duration, external TL, and internal TL, using time spent in predetermined heart-rate zones. Correlations were assessed via regression analyses. URI was quantified via weekly self-report symptom questionnaire. Results: There was a significant negative relation between athletes’ individual weekly training duration and sIgA secretion rate (P = .028), with changes in training duration accounting for 12.7% of the variance (quartiles: 0.2%, 19.2%). There was, however, no significant relation between external or internal TL and sIgA parameters (P ≥ .104). There was no significant difference in sIgA when URI was present or not (101% vs 118% healthy median concentration; P ≥ .225); likewise, there was no difference in sIgA when URI occurred within 2 wk of sampling or not (83% vs 125% healthy median concentration; P ≥ .120). Conclusions: Paratriathletes’ weekly training duration significantly affects sIgA secretion rate, yet the authors did not find a relation between external or internal TL and sIgA parameters. Furthermore, it was not possible to detect any link between sIgA and URI occurrence, which throws into question the potential of using sIgA as a monitoring tool for early detection of illness.

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Aitor Iturricastillo, Javier Yanci, Cristina Granados and Victoria Goosey-Tolfrey

Purpose:

To describe the objective and subjective match load (ML) of wheelchair basketball (WB) and determine the relationship between session heart-rate (HR) -based ML and rating-of-perceived-exertion (RPE) -based ML methods.

Methods:

HR-based measurements of ML included Edwards ML and Stagno training impulses (TRIMPMOD), while RPE-based ML measurements included respiratory (sRPEres) and muscular (sRPEmus). Data were collected from 10 WB players during a whole competitive season.

Results:

Edwards ML and TRIMPMOD averaged across 16 matches were 255.3 ± 66.3 and 167.9 ± 67.1 AU, respectively. In contrast, sRPEres ML and sRPEmus ML were found to be higher (521.9 ± 188.7 and 536.9 ± 185.8 AU, respectively). Moderate correlations (r = .629–.648, P < .001) between Edwards ML and RPE-based ML methods were found. Moreover, similar significant correlations were also shown between the TRIMPMOD and RPE-based ML methods (r = .627–.668, P < .001). That said, only ≥40% of variance in HR-based ML was explained by RPE-based ML, which could be explained by the heterogeneity of physical-impairment type.

Conclusion:

RPE-based ML methods could be used as an indicator of global internal ML in highly trained WB players.

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Ibrahim Akubat, Steve Barrett and Grant Abt

Purpose:

This study aimed to assess the relationships of fitness in soccer players with a novel integration of internal and external training load (TL).

Design:

Ten amateur soccer players performed a lactate threshold (LT) test followed by a soccer simulation (Ball-Sport Endurance and Sprint Test [BEAST90mod]).

Methods:

The results from the LT test were used to determine velocity at lactate threshold (vLT), velocity at onset of blood lactate accumulation (vOBLA), maximal oxygen uptake (VO2max), and the heart rate–blood lactate profile for calculation of internal TL (individualized training impulse, or iTRIMP). The total distance (TD) and high intensity distance (HID) covered during the BEAST90mod were measured using GPS technology that allowed measurement of performance and external TL. The internal TL was divided by the external TL to form TD:iTRIMP and HID:iTRIMP ratios. Correlation analyses assessed the relationships between fitness measures and the ratios to performance in the BEAST90mod.

Results:

vLT, vOBLA, and VO2max showed no significant relationship to TD or HID. HID:iTRIMP significantly correlated with vOBLA (r = .65, P = .04; large), and TD:iTRIMP showed a significant correlation with vLT (r = .69, P = .03; large).

Conclusions:

The results suggest that the integrated use of ratios may help in the assessment of fitness, as performance alone showed no significant relationships with fitness.

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Alireza Rabbani, Mehdi Kargarfard, Carlo Castagna, Filipe Manuel Clemente and Craig Twist

-season phase. Figure 1 —NBL and Edwards TRIMP distribution during selected in-season phase. 30-15 IFT indicates 30-15 Intermittent Fitness Test; AU, arbitrary units; NBL, new body load; TRIMP, training impulse. Error bars represent the SD. Methodology 30-15 Intermittent Fitness Test After habituation, each

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Lilian Roos, Wolfgang Taube, Carolin Tuch, Klaus Michael Frei and Thomas Wyss

HR data of each individual training session were used to calculate the training impulse according to Edwards’ (training impulse [TRIMP]) 5 HR zones, with minutes spent in each zone multiplied by the corresponding factors from 1 to 5 and summed for the total. 3 Statistical Analysis Statistical