Introduction Highly-trained runners need to endure workouts at intensities very close or above their Personal Best (PB) to induce adaptive changes and improve their performance. Unfortunately, these high-intensity trainings could also trigger undesirable negative stress effects, what increases the importance of thoroughly quantifying their training load (TL). Previous research have suggested that post-exercise Heart Rate (HR) dynamics may offer objetive information on TL (1, 2). Therefore, our purpose was to investigate the effect of a high-intensity speed-endurance workout for 800-m runners (i.e. the ”Broken 800’s”) on HR complexity, comparing senior to junior athletes. Methods 19 male 800m runners, belonging to either Senior (n=10; PB800-m: 112.61±3.87 s) or Junior category (n=9; PB800-m: 120.92±3.33 s) participated in the study. Subjects performed 2x4x200-m, with a recovery period of 30 s between bouts and 15 min between the sets. Intensity was established for every subject at the 102% of his 800-m running velocity (i.e., according to his previous season best performance). Total time required to complete each 4×200-m was retained as a measure of performance. Heart interbeat intervals were recorded during 5 min using a Polar RS800 in a seated position before the warm-up (PRE) and 5 min following the first (POST1) and the second set (POST2) of the interval training. HR complexity was quantified by means of Sample Entropy algorithm (SampEn), utilizing Kubios HRV software. A repeated measures ANOVA followed by a Bonferroni post-hoc, with one within factor (‘fatigue’: PRE, POST1, POST2) and one between factor (‘category’: SENIOR vs JUNIOR), was employed to elucidate the effect of ”Broken 800’s” on SampEn. The same statistical approach was used to analyze possible differences in performance. Results A significant effect was found for ’fatigue’ factor and the interaction ’category x fatigue’ on SampEn. Regarding fatigue factor, further Bonferroni pairwise comparisons showed that SampEn was higher at PRE compared to Post1 and Post2 (1.30±0.35; 0.90±0.32 & 0.96 ± 0.30; p<0.05); however, post-hoc analysis of the interaction between category and fatigue revealed that these differences remained significant only for junior athletes (p<0.05). Similarly, whereas junior’s performance was significantly worse in the second 4×200 (119.7±3.1 s vs. 122.6±3.3 s; p<0.05), there were no differences for senior athletes. Conclusions Our results showed that ”Broken 800’s” have a greater disturbing effect on HR complexity of junior athletes (i.e., compared to senior athletes), despite individualizing running velocity. This is consistent with a significant performance decay in juniors during the second set of repetitions, unlike senior athletes. Therefore, this type of maximal speed-endurance workout should be used with caution on junior runners.