A well-planned periodized approach endeavors to allow road cyclists to achieve peak performance when their most important competitions are held. Purpose: To identify the main characteristics of periodization models and physiological parameters of trained road cyclists as described by discernable training intensity distribution (TID), volume, and periodization models. Methods: The electronic databases Scopus, PubMed, and Web of Science were searched using a comprehensive list of relevant terms. Studies that investigated the effect of the periodization of training in cyclists and described training load (volume, TID) and periodization details were included in the systematic review. Results: Seven studies met the inclusion criteria. Block periodization (characterized by employment of highly concentrated training workload phases) ranged between 1- and 8-week blocks of high-, medium-, or low-intensity training. Training volume ranged from 8.75 to 11.68 h·wk^–1 and both pyramidal and polarized TID were used. Traditional periodization (characterized by a first period of high-volume/low-intensity training, before reducing volume and increasing the proportion of high-intensity training) was characterized by a cyclic progressive increase in training load, the training volume ranged from 7.5 to 10.76 h·wk^–1, and pyramidal TID was used. Block periodization improved maximum oxygen uptake (VO₂max), peak aerobic power, lactate, and ventilatory thresholds, while traditional periodization improved VO₂max, peak aerobic power, and lactate thresholds. In addition, a day-by-day programming approach improved VO₂max and ventilatory thresholds. Conclusions: No evidence is currently available favoring a specific periodization model during 8 to 12 weeks in trained road cyclists. However, few studies have examined seasonal impact of different periodization models in a systematic way.

Background : The role of high-volume low-intensity training for enhancing endurance performance has gained growing interest in recent years. Specifically, so-called “zone 2 training” is currently receiving much attention, and many propose that this is the target intensity at which a large proportion of total endurance training should be performed. However, despite the popularity of this concept, there is no clear consensus among coaches, athletes, and scientists regarding the definition of zone 2 training. Purpose : This commentary summarizes the perspectives, experience, and knowledge of an expert panel of 14 applied sport scientists and professional coaches with the aim of providing insight and a basis for definitional consensus on zone 2 training. Moreover, potential training strategies at this intensity are proposed, and the expected physiological adaptations when exercising at this intensity and related research gaps are also discussed. Results : Experts reached consensus that zone 2 training should preferably be performed at intensities located immediately below the first lactate or ventilatory threshold through continuous, variable, or interval-type sessions. Furthermore, experts expected a broad range of central and peripheral adaptations from zone 2 training. These expected adaptations might not be unique to zone 2 and could also be induced with sessions performed at slightly higher and lower intensities. Conclusions : This commentary provides practical insight and unified criteria regarding the preferred intensity, duration, and session type for the optimization of zone 2 training based on the perspectives of acknowledged sport scientists and professional coaches.

The aim of this study was to determine the influence of body weight or lean body mass-based load on Wingate Anaerobic Test performance in male and female endurance trained individuals. Thirty-one participants (22 male cyclists and triathletes and 9 female triathletes) completed two randomized Wingate Anaerobic Test (body weight and lean body mass loads) in stationary start. There were no significant differences in power outputs variables between loads in any group. However, when comparing specific groups within the sample (e. g. cyclists vs cyclists) medium to large effect sizes were observed for Relative Mean Power Output (ES=0.53), Relative Lowest Power (ES=0.99) and Relative Power Muscle Mass (ES=0.54). Regarding gender differences, male cyclists and triathletes displayed higher relative and absolute power outputs (p<0.001) compared to female triathletes regardless of the protocol used. FI was lower in female triathletes compared to male triathletes and cyclists in body weight (p<0.001) and lean body mass (p<0.01) protocols. Body composition and anthropometric characteristics were similar in male cyclists and triathletes, but there were differences between genders. These results suggest that using either body weight-based or lean body mass-based load can be used interchangeably. However, there may be some practically relevant differences when evaluating this on an individual level.

Critical speed represents the highest exercise intensity at which the oxidative phosphorylation is sufficient to satisfy the energy demand. Since the release of the advanced footwear technology in May 2017, every road record from the 5-km event to the marathon has been broken. The question arises whether this type of footwear improves critical speed and, thus, performance. The aims of this study were (i) to assess the impact of advanced footwear technology on critical speed and D′ (curvature constant of speed-time relationship) in male elite distance runners, and (ii) to analyse the interference of the weather conditions and orography on such influence. Critical speed and D′ were calculated using the linear distance-time model analysis in eleven runners through their season best performances in two distance running events (10-km and half-marathon) during the same season. Six runners were wearing advanced footwear technology during the advanced footwear technology era and not wearing this footwear during the pre-advanced footwear technology era (experimental group), and five runners were not wearing advanced footwear technology during any of both eras (control group). Critical speed improved by 3.31% in the experimental group when runners were wearing advanced footwear technology (p = 0.034; ES = 0.623), while in the control group did not change (p = 0.311; ES = 0.251). D′ remained unchanged in both groups. Weather conditions and orography remained unchanged. The use of advanced footwear technology resulted into an improved critical speed which could explain the improvement in performance with this type of footwear in recent years in elite runners.

The present study aims to determine the utility of integrating balance model (W´_BAL-INT) in designing interval training programs as assessed by improvements in power output, critical power (CP), and W prime (W´) defined as the finite work capacity above CP. Fourteen male cyclists (age = 42 ± 7 yr, body mass = 69.6 ± 6.5 kg, height = 175 ± 5 cm, CP = 302 ± 32 W, relative CP = 4.35 ± 0.66 W·kg^-1) were randomized into two training groups: Short-Medium-Long intervals (SML-INT; n = 7) or Long intervals (L-INT, n = 7) [training sessions separated by 72 h], along with 3-4 sessions of moderate intensity training per week, for 4 weeks. All sessions were designed to result in the complete depletion of the W´ as gauged by the W´_BAL-INT. CP and W´ were assessed using the specified efforts (i.e., 12, 7 and 3 min) and calculated with the 2-parameter CP linear model. Training loads between the groups were compared using different metrics. CP improved in both the SML-INT and L-INT groups by 5 ± 4% and 6 ± 5% (p < 0.001) respectively, without significant changes in W´. Mean maximal power over 3, 7 and 12 min increased significantly in the SML-INT group by 5%, 4% and 9%, (p < 0.05) without significant changes in the L-INT group. There were no differences between groups in training zone distribution or training load using BikeScore and relative intensity, but there was significantly (p < 0.05) higher TRIMPS for the Long-INT group. Therefore, W´_BAL model may prove to be a useful tool for coaches to construct SML-INT training programs.