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Objective: The sports-science literature lacks data on training and performance characteristics of international elite athletes over multiple seasons. The present case study provided general training characteristics and performance data of two male short-distance triathletes in the Junior, U23, and international Elite categories., Methods: General training and performance data of two male elite triathletes were described in swimming, cycling, and running segments from the 2015 to 2022 season. The training load was presented using the ECO model while the training intensity distribution (TID) was a triphasic model., Results: Both triathletes increased their performance throughout the seasons. Triathlete A increased his VO 2max in cycling by 20.6%, in running by 16.7%. His power at VO 2max and his speed at VO 2max by 18.9% and 11.0%, respectively. Triathlete B improved his VO 2max by 17.8% in cycling, by 16.1% in running and his power at VO 2max by 24%, and his speed at VO 2max by 14.3%. The triathletes trained on average 14-17 h a week. The TID model was polarized., Conclusions: To achieve the top international level, it is necessary to consider the following measures: training load progression; improvements in physiological variables; and participation in international events starting from youth categories., (© 2023 The Authors. Scandinavian Journal of Medicine & Science In Sports published by John Wiley & Sons Ltd.)

The purpose of the present study was to relate the training intensity distribution with performance in a Half-Ironman distance triathlon competition. A total of 18 recreational-level triathletes were divided into two training groups according to their training intensity distribution: Polarized (POL) and Pyramidal (PYR). Prior to the specific training period of the study, subjects performed a ramp-protocol test, running and cycling to determine ventilatory thresholds (VT) through gas-exchange analysis. For swimming, subjects performed an 800-metre test to establish their training zones. Training was quantified based on the cumulative time spent in 3 intensity zones: zone 1 (low intensity, VT2). POL competed 84.5%/4.2%/11.3% and PYR 77.9%/18.8%/3.3% of total training time for zones 1,2 and 3 respectively. The goal of the training period was a half Ironman distance triathlon. Training time in zone 2 inversely correlated with swimming and cycling race time in POL and with running and total race time in PYR. Power at VT2 on bike and speed at VT2 as well as maximum aerobic power and speed in the physiological post test inversely correlated with bike and run segment respectively and with total race time. These results suggest that training time in zone 2 was related with better performance on a Half-Ironman race in amateur triathletes. Future experimental research is needed to clarify the importance of training intensity distribution regarding performance., (© Journal of Sports Science and Medicine.)

Purpose: To describe training loads during an Ironman training program based on intensity zones and observe Training-performance relationships., Methods: Nine triathletes completed a program with the same periodization model aiming at participation in the same Ironman event. Before and during the study, subjects performed ramp-protocol tests, running, and cycling to determine aerobic (AeT) and anaerobic thresholds (AnT) through gas-exchange analysis. For swimming, subjects performed a graded lactate test to determine AeT and AnT. Training was subsequently controlled by heart rate (HR) during each training session over 18 wk. Training and the competition were both quantified based on the cumulative time spent in 3 intensity zones: zone 1 (low intensity; AnT)., Results: Most of training time was spent in zone 1 (68% ± 14%), whereas the Ironman competition was primarily performed in zone 2 (59% ± 22%). Significant inverse correlations were found between both total training time and training time in zone 1 vs performance time in competition (r = -.69 and -.92, respectively). In contrast, there was a moderate positive correlation between total training time in zone 2 and performance time in competition (r = .53) and a strong positive correlation between percentage of total training time in zone 2 and performance time in competition (r = .94)., Conclusions: While athletes perform with HR mainly in zone 2, better performances are associated with more training time spent in zone 1. A high amount of cycling training in zone 2 may contribute to poorer overall performance.