Dear Editor-in-Chief, We thank Boullosa et al. (1) for their interest in our study (2), and we appreciate their support in further stimulating discussion in this research area. We are aware that the nonfunctional overreaching “sword of Damocles” is often mentioned with sudden increases in workload. Therefore, all participants in our study completed the short form of the Acute Recovery and Stress Scale (3), and heart rate variability was measured frequently, although neither of these data sets were presented (2). However, we did monitor both data sets and found no impaired, long-lasting recovery–stress state indicating adverse health effects. Our data do not allow us to comment on the assumption by Boullosa et al. (1) that reduced total workload might have induced a better performance outcome in our recreational runners. However, we agree that in order to judge the responses to exercise, an all-day integrative view is required (4), including habitual exercise, which should be addressed in future studies. In rebuttal to the remark that the 3-wk training intensity distribution (TID) of our polarized training group (POL) is not an adequate reproduction of previously described typical polarized TID in recreational and subelite runners as presented by Muñoz et al. (5) and Esteve-Lanao et al. (6), our reply is as follows: We are aware of the different methodological issues surrounding TID quantification, especially comparability between different studies. One solution may be to calculate a “polarization index” (7), which in POL (2) was 1.94 a.u. and slightly higher than the studies quoted by Boullosa et al. (1.87 a.u. [5] and 1.75 a.u. [6]) (1). The difference between the TID of Muñoz et al. (5) (72.9/13.5/13.6%) and our TID (2) (69.7/13.4/16.9%) is that our mean time spent in zone 1 was slightly lower (−3.2%) and higher in zone 3 (+3.3%), but we consider these differences to be minor. Thus, our POL–TID appears somewhat more “polarized” in comparison with the quoted TID (5). The referred TID of Esteve-Lanao et al. (6) presents a rather “pyramidal” TID (80.5/11.8/8.3%), whereas a recalculation (mentioned within the discussion of [6]) revealed a more “polarized” TID (74/11/15%, polarization index = 2.0 a.u.). Therefore, depending on the TID quantification, shifts in the proportion of zones may occur. Nevertheless, both TID calculations by Esteve-Lanao et al. (6) showed more time spent in zone 1 and slightly less time in zone 2 (compared with our recreational runners), which is likely attributable to the substantially greater amount of overall training time of subelite runners. Subelite runners performing >80 km·wk−1 will not or cannot invest too much time in zones 2 and 3 because recovery between frequent demanding training sessions becomes challenging/impossible. We therefore discourage the comparison of TID between (sub)elite and recreational runners. We agree that training time in zone 1 constitutes the greatest proportion within a polarized model in (sub)elite runners. However, optimal TID, especially the proportion of zones 1 and 3, has yet to be identified in both recreational and (sub)elite runners (8). In fact, the individual responses within our three groups are quite heterogenous without conclusive identification of a best practice TID in recreational runners. Future studies with well-designed crossover designs are warranted to address this matter in detail. Christoph Zinner University of Applied Sciences for Police and Administration of Hesse Wiesbaden, GERMANY Integrative & Experimental Exercise Science & Training Institute for Sport Sciences University of Würzburg, GERMANY Daniela Schäfer Olstad Polar Electro Oy Kempele, FINLAND Billy Sperlich Integrative & Experimental Exercise Science & Training Institute for Sport Sciences University of Würzburg, GERMANY