Although swimmers with the lowest swimming class experienced the highest passive drag and vice versa, the inconsistent difference in mean passive drag between adjacent classes indicates that the current classification system does not always differentiate clearly between swimming groups.

In this study, we used recently developed technology to determine the force-time profile of elite swimmers, which enabled coaches to make informed decisions on technique modifications. Eight elite male swimmers with a FINA (Federation Internationale de Natation) rank of 900+ completed five passive (streamline tow) and five net force (arms and leg swimming) trials. Three 50-Hz cameras were used to video each trial and were synchronized to the kinetic data output from a force-platform, upon which a motorized towing device was mounted. Passive and net force trials were completed at the participant's maximal front crawl swimming velocity. For the constant tow velocity, the net force profile was presented as a force-time graph, and the limitation of a constant velocity assumption was acknowledged. This allowed minimum and maximum net forces and arm symmetry to be identified. At a mean velocity of 1.92+0.06 m s⁻¹, the mean passive drag for the swimmers was 80.3+4.0 N, and the mean net force was 262.4+33.4 N. The mean location in the stroke cycle for minimum and maximum net force production was at 45% (insweep phase) and 75% (upsweep phase) of the stroke, respectively. This force-time profile also identified any stroke asymmetry.

The measurement of active drag in swimming is a biomechanical challenge. This research compared two systems: (i) measuring active drag (MAD) and (ii) assisted towing method (ATM). Nine intermediate-level swimmers (19.7 ± 4.4 years) completed front crawl trials with both systems during one session. The mean (95% confidence interval) active drag for the two systems, at the same maximum speed of 1.68 m/s (1.40-1.87 m/s), was significantly different (p = .002) with a 55% variation in magnitude. The mean active drag was 82.3 N (74.0-90.6 N) for the MAD system and 148.3 N (127.5-169.1 N) for the ATM system. These differences were attributed to variations in swimming style within each measurement system. The inability to measure the early catch phase and kick, along with the fixed length and depth hand place requirement within the MAD system generated a different swimming technique, when compared with the more natural free swimming ATM protocol. A benefit of the MAD system was the measurement of active drag at various speeds. Conversely, the fixed towing speed of the ATM system allowed a natural self-selected arm stroke (plus kick) and the generation of an instantaneous force-time profile.

This study compared stroke-coordination and symmetry using traditional timing methods and net drag force profiles. Twenty elite front-crawl swimmers Federation Internationale de Natation (FINA ranking 908 ± 59) were tested to identify the influence of both gender and breathing. A total of six randomised free-swimming trials were conducted: (i) three breathing, (ii) three non-breathing. Net drag forces were measured using an assisted towing device and the magnitude and location of minimum and maximum was determined to create a stroke symmetry index. Within the breathing condition, there were significant differences between the two symmetry index methods. Using the timing index, all 10 female participants, and seven males, illustrated symmetrical timing. For the net drag force profile, only three females and zero males exhibited a symmetrical minimum net drag force; and only four females and two males demonstrated a symmetrical maximum net drag force index. No differences existed within the non-breathing condition. There was a small (5.2%) difference in the location of maximum net drag force, when stratifying by gender. During the breathing condition, gender also influenced the percentage of overlap for the breathing stroke by 25.2%, and 14.6 % for the non-breathing stroke. A combination of the traditional timing based and net drag force based profile can guide future swimming technique intervention strategies.