The  objective of this study was to examine the practicability and accuracy of the RLT to determine the MLSS in a field test setting and to investigate whether the average running speed (v5000) in a 5000-meter all-out trial would be appropriate to determine the highest intensity during the RLT priming segment. In addition, heart rate (HR) and rating of perceived exertion (RPE) were measured as potential non-invasive steady-state identification methods and stride pattern changes with altered load were observed.
Our primary finding is that the RLT can be easily implemented in a field test setting exhibiting a high accuracy determined by a strong correlation with the MLSS gold standard test. As a strong link between the v5000 and the MLSS speed in the RLT could be observed, the results clearly indicate that the v5000 presents a suitable benchmark to determine the single RLT stage intensities. In addition, non-invasive parameters, like HR, RPE, and foot strike pattern changes are considered easily obtainable as well as correlated with the MLSS.
Previous research recommended to use the physiologically founded RLT to determine the MLSS  because of its higher accuracy compared to graded exercise tests that are based on arbitrary or empirically derived criteria (Dotan, 2012; Wahl, 2017; Messias, 2018). Even if they included athletes from different endurance-based sports (rowing, cycling, running) as well as non-athletes, this is the first investigation to implement the RLT in a field test setting. Since in accordance with the cited authors we found a strong correlation between the MLSS determined by the RLT and that determined by means of the gold standard (r = .95), we clearly propose the RLT as a practicable and precise method to estimate the MLSS even in a field test setting with a number of athletes. 
Furthermore, we recommend a new way to handle the main weakness of the RLT, i. e. the definition of the single stage intensities (Dotan, 2012; Wahl, 2017). The difficulty is inherent in the test design because the intensity has to be increased above MLSS intensity during the priming segment in order to equally raise lactate concentrations above MLSS conditions. However, the intensity above MLSS has to be chosen carefully otherwise athletes probably will not be able to finish the test.  Since the MLSS defined as the highest constant workload that still leads to a lactate production and elimination equilibrium can be sustained for more than 30 minutes (Billat, 2003), it seems obvious that athletes would generally absolve a 5000-meter all-out trial at least with the MLSS speed or rather, depending on training status, even with a higher intensity. Likewise, our results show a strong link between the v5000 and the MLSS speed determined by both the RLT (r = .93) and by the gold standard (r = .95). As our group of subjects (sport students) was extremely heterogeneous (inter alia teamsport, endurance, and strenght athletes) and therefore some participants potentially were not used to absolve a 5000-meter all-out trial with maximal speed, we used v5000 + 5% as the highest running speed in the last stage of the RLT priming segment to avoid an underestimation of the MLSS speed. As evident from the high accordance between the MLSS speed determined by the RLT and that determined by the gold standard, our pacing seems to be suitable for a broad spectrum of athletes.
Since Messias and co-workers (2018) recently showed that the HR course during the RLT can constitute a valid, non-invasive alternative to the more expensive parameter lactate, we also observed HR during the RLT. In accordance with the previous research we found a strong correlation between MLSS determination via HR course and MLSS determination by means of the gold standard (via blood lactate concentration) (r = .92). Similarly, Madrid et al. (2016) demonstrated that RPE as an indicator of individual’s subjective tolerance of exercise at a given intensity could be useful for estimating MLSS. Likewise, we found a strong correlation between MLSS speed determined by RPE during the RLT and that determined by means of the gold standard (r = .85). Thus, we believe that apart from being a useful tool to determine MLSS intensities via blood lactate concentration the RLT offers a cheap and simple possibility of non-invasive MLSS determination via HR and RPE as well.