Methods of Monitoring Training Load and Their Relationships to Changes in Fitness and Performance in Competitive Road Cyclists

Click name to view affiliation

Dajo Sanders
Search for other papers by Dajo Sanders in
Current site
Google Scholar
PubMed
Close
,
Grant Abt
Search for other papers by Grant Abt in
Current site
Google Scholar
PubMed
Close
,
Matthijs K.C. Hesselink
Search for other papers by Matthijs K.C. Hesselink in
Current site
Google Scholar
PubMed
Close
,
Tony Myers
Search for other papers by Tony Myers in
Current site
Google Scholar
PubMed
Close
, and
Ibrahim Akubat
Search for other papers by Ibrahim Akubat in
Current site
Google Scholar
PubMed
Close
Restricted access

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.

Sanders, Myers, and Akubat are with the Sport, Exercise and Health Research Centre, Newman University, Birmingham, UK. Abt is with the Dept of Sport, Health and Exercise Science, University of Hull, Hull, UK. Hesselink is with the Dept of Human Movement Science, MUMC+, Maastricht, the Netherlands.

Address author correspondence to Dajo Sanders at dajosanders@gmail.com.
  • Collapse
  • Expand