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Dajo Sanders, Tony Myers and Ibrahim Akubat

Purpose:

To evaluate training-intensity distribution using different intensity measures based on rating of perceived exertion (RPE), heart rate (HR), and power output (PO) in well-trained cyclists.

Methods:

Fifteen road cyclists participated in the study. Training data were collected during a 10-wk training period. Training-intensity distribution was quantified using RPE, HR, and PO categorized in a 3-zone training-intensity model. Three zones for HR and PO were based around a 1st and 2nd lactate threshold. The 3 RPE zones were defined using a 10-point scale: zone 1, RPE scores 1–4; zone 2, RPE scores 5–6; zone 3, RPE scores 7–10.

Results:

Training-intensity distributions as percentages of time spent in zones 1, 2, and 3 were moderate to very largely different for RPE (44.9%, 29.9%, 25.2%) compared with HR (86.8%, 8.8%, 4.4%) and PO (79.5%, 9.0%, 11.5%). Time in zone 1 quantified using RPE was largely to very largely lower for RPE than PO (P < .001) and HR (P < .001). Time in zones 2 and 3 was moderately to very largely higher when quantified using RPE compared with intensity quantified using HR (P < .001) and PO (P < .001).

Conclusions:

Training-intensity distribution quantified using RPE demonstrates moderate to very large differences compared with intensity distributions quantified based on HR and PO. The choice of intensity measure affects intensity distribution and has implications for training-load quantification, training prescription, and the evaluation of training characteristics.

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Matthew Ellis, Mark Noon, Tony Myers and Neil Clarke

Context: High doses of ∼6 mg·kg−1 body mass have improved performance during intermittent running, jumping, and agility protocols. However, there are sparse data on low doses of caffeine, especially in elite adolescent soccer players. Methods: A total of 15 elite youth soccer players (177.3 [4.8] cm, 66.9 [7.9] kg, and 16 [1] y) participated in the study, consuming 1, 2, or 3 mg·kg−1 caffeine in a gelatin capsule or a 2-mg·kg−1 placebo in a single-blind, randomized, crossover study design. Testing consisted of a 20-m sprint, arrowhead agility (change of direction [CoD] right or left), countermovement jump (CMJ), and Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1). Postexercise CMJ performance was assessed as participants exited the Yo-Yo IR1. Data were analyzed using a Bayesian multilevel regression model to provide explained variance and probabilities of improvement (P = %). Results: Compared with placebo, 3 mg·kg−1 caffeine presented the highest probabilities of change across a range of tests (mean [SD], P = %). Times for 20-m sprint were 3.15 (0.10) s vs 3.18 (0.09) s (P = 73%), CoD-right times were 8.43 (0.24) s vs 8.55 (0.25) s (P = 99%), CoD-left times were 8.44 (0.22) s vs 8.52 (0.18) s (P = 85%), Yo-Yo IR1 distance was 2440 (531) m vs 2308 (540) m (P = 15%), and preexercise CMJ height was 41.6 (7.2) cm vs 38 (8.5) cm (P = 96%). Postexercise CMJ was higher with 3 mg·kg−1 than with placebo (42.3 [8] cm vs 36.6 [8] cm; P = 100%). Doses of 1 or 2 mg·kg−1 caffeine also demonstrated the ability to enhance performance but were task dependent. Conclusion: Low doses of caffeine improve performance but are dose and task dependent. A dose of 3 mg·kg−1 caffeine improved performance across the majority of tests with potential to further improve postexercise CMJ height.

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Dajo Sanders, Grant Abt, Matthijs K.C. Hesselink, Tony Myers and Ibrahim Akubat

Purpose:

To assess the dose-response relationships between different training-load methods and aerobic fitness and performance in competitive road cyclists.

Methods:

Training data from 15 well-trained competitive cyclists were collected during a 10-wk (December–March) preseason training period. Before and after the training period, participants underwent a laboratory incremental exercise test with gas-exchange and lactate measures and a performance assessment using an 8-min time trial (8MT). Internal training load was calculated using Banister TRIMP, Edwards TRIMP, individualized TRIMP (iTRIMP), Lucia TRIMP (luTRIMP), and session rating of perceived exertion (sRPE). External load was measured using Training Stress Score (TSS).

Results:

Large to very large relationships (r = .54–.81) between training load and changes in submaximal fitness variables (power at 2 and 4 mmol/L) were observed for all training-load calculation methods. The strongest relationships with changes in aerobic fitness variables were observed for iTRIMP (r = .81 [95% CI .51–.93, r = .77 [95% CI .43–.92]) and TSS (r = .75 [95% CI .31–.93], r = .79 [95% CI .40–.94]). The strongest dose-response relationships with changes in the 8MT test were observed for iTRIMP (r = .63 [95% CI .17–.86]) and luTRIMP (r = .70 [95% CI .29–.89).

Conclusions:

Training-load quantification methods that integrate individual physiological characteristics have the strongest dose-response relationships, suggesting this to be an essential factor in the quantification of training load in cycling.

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Richard J. Taylor, Dajo Sanders, Tony Myers, Grant Abt, Celia A. Taylor and Ibrahim Akubat

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 VO2max, velocity at VO2max, 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 VO2max. 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.