Researchers have quantified swimming races for several decades to provide objective information on race strategy and characteristics. The purpose of the present review was to summarize knowledge established in the literature and current issues in swimming race analysis. A systematic search of the literature for the current narrative review was conducted in September 2020 using Web of Science, SPORTDiscus (via EBSCO), and PubMed. After examining 321 studies, 22 articles were included in the current review. Most studies divided the race into the start, clean swimming, turn, and/or finish segments; however, the definition of each segment varied, especially for the turn. Ideal definitions for the start and turn-out seemed to differ depending on the stroke styles and swimmers’ level. Many studies have focused on either 100 m or 200 m events with the four strokes (butterfly, backstroke, breaststroke, and freestyle). Contrastingly, there were few or no studies for 50 m, long-distance, individual medley, and relay events. The number of studies examining races for short course, junior and Paralympic swimmers were also very limited. Future studies should focus on those with limited evidence as well as race analysis outside competitions in which detailed kinematic and physiological analyses are possible.

The aim of this study was to review the literature on front crawl swimming biomechanics, focusing on propulsive and resistive forces at different swimming velocities. Recent studies show that the resistive force increases in proportion to the cube of the velocity, which implies that a proficient technique to miminise the resistive (and maximise the propulsive) force is particularly important in sprinters. To increase the velocity in races, swimmers increase their stroke frequency. However, experimental and simulation studies have revealed that there is a maximum frequency beyond which swimmers cannot further increase swimming velocity due to a change in the angle of attack of the hand that reduces its propulsive force. While the results of experimental and simulation studies are consistent regarding the effect of the arm actions on propulsion, the findings of investigations into the effect of the kicking motion are conflicting. Some studies have indicated a positive effect of kicking on propulsion at high swimming velocities while the others have yielded the opposite result. Therefore, this review contributes to knowledge of how the upper-limb propulsion can be optimised and indicates a need for further investigation to understand how the kicking action can be optimised in front crawl swimming. Abbreviations: C: Energy cost [kJ/m]; Ė: Metabolic power [W, kJ/s]; F_hand: Fluid resultant force exerted by the hand [N]; F_total: Total resultant force [N] (See Appendix A); F_normal: The sum of the fluid forces acting on body segments toward directions perpendicular to the segmental long axis, which is proportional to the square of the segmental velocity. [N] (See Appendix A); F_tangent: The sum of the fluid forces acting on body segments along the direction parallel to the segmental long axis, which is proportional to the square of the segmental velocity. [N] (See Appendix A); F_addmass: The sum of the inertial force acting on the body segments due to the acceleration of a mass of water [N] (See Appendix A); F_buoyant: The sum of the buoyant forces acting on the body segments [N] (See Appendix A); D: Fluid resistive force acting on a swimmer’s body (active drag) [N]; T: Thrust (propulsive) force acting in the swimming direction in reaction to the swimmer’s actions [N]; T_hand: Thrust force produced in reaction to the actions of the hand [N]; T_{upper_limb}: Thrust force produced in reaction to the actions of the upper limbs [N]; T_{lower_limb}: Thrust force produced in reaction to the actions of the lower limbs [N]; M_body: Whole-body mass of the swimmer [kg]; SF: Stroke frequency (stroke number per second) [Hz]; SL: Stroke length (distance travelled per stroke) [m]; v: Instantaneous centre of mass velocity of the swimmer [m/s]; $\bar{V}$: Mean of the instantaneous centre of mass velocities in the swimming direction over the period of the stroke cycle [m/s]; a: Centre of mass acceleration of the swimmer [m/s2]; $\bar{V}$_hand: Mean of the instantaneous magnitudes of hand velocity over a period of time [m/s]; Ẇ_tot: Total mechanical power [W]; Ẇ_ext: External mechanical power [W]; Ẇ_d: Drag power (mechanical power needed to overcome drag) [W, Nm/s]; α: Angle of attack of the palm plane with respect to the velocity vector of the hand [deg]; η_o: Overall efficiency [%]; η_p: Propelling efficiency [%]; MAD-system: Measuring Active Drag system; MRT method: Measuring Residual Thrust method.

Background and aim: To identify kinematic variables related to short course 100 m breaststroke performance. Methods: An automatic race analysis system was utilized to obtain start (0–15 m), turn (5 m before the wall until 10 m out), finish (95–100 m), and clean swimming (the rest of the race) segment times as well as cycle rate and cycle length during each swimming cycle from 15 male swimmers during a 100 m breaststroke race. A bivariate correlation and a partial correlation were employed to assess the relationship between each variable and swimming time. Results: Turns were the largest time contributor to the finishing time (44.30 ± 0.58%), followed by clean swimming (38.93 ± 0.50%), start (11.39 ± 0.22%), and finish (5.36 ± 0.18%). The finishing time was correlated (p < 0.001) with start segment time (r = 0.979), clean swimming time (r = 0.940), and 10 m turn-out time (r = 0.829). The clean swimming time was associated with the finishing time, but cycle rate and cycle length were not. In both start and turns, the peak velocity (i.e., take-off and push-off velocity) and the transition velocity were related to the segment time (r ≤ −0.673, p ≤ 0.006). Conclusions: Breaststroke training should focus on: (I) 15 m start with generating high take-off velocity, (II) improving clean swimming velocity by finding an optimal balance between cycle length and rate, (III) 10 m turn-out with maintaining a strong wall push-off, and (IV) establishing a high transition velocity from underwater to surface swimming.

This study aimed to assess kinematic and kinetic changes in front crawl with various stroke frequency (SF) conditions to investigate why swimming velocity (SV) does not increase above a certain SF (SF_max). Eight male swimmers performed 20 m front crawl four times. The first trial involved maximal effort, whereas SF was controlled during the next three trials. The instructed SFs were 100 (T100%), 110 (T110%), and 120% (T120%) of the SF_max. Through pressure measurement and underwater motion analysis, hand propulsive force (calculated by the difference between the palm and dorsal pressure value and the hand area) and the angle of attack of the hand were quantified, and differences between trials were assessed by a repeated-measures ANOVA. There was no difference in SV between the conditions, while the angle of attack during the latter half of the underwater stroke at T120% was smaller by 25.7% compared with T100% (p = 0.007). The lower angle of attack induced a lower pressure value on the palm that consequently caused a smaller hand propulsive force at T120% than T100% (p = 0.026). Therefore, the decrease in the angle of attack must be minimised to maintain the hand propulsive force.

The purpose of this study was to establish the relationships between 50 m sprint swimming performance and variables acquired from a swimming load-velocity profile established by semi-tethered butterfly swimming. Twelve male elite swimmers participated in the present study and performed 50 m sprint and semi-tethered butterfly swimming with different loads. The mean velocity among all upper-limb cycles was obtained from the 50 m swimming (race velocity), and maximum load and velocity were predicted from the load-velocity profile established by the semi-tethered swimming test. There was a very large correlation (r=0.885, p<0.01) and a high intra-class correlation (0.844, p<0.001) between the race velocity and the predicted maximum velocity. Significant correlations were also observed between the predicted maximum load and the 50 m time as well as the race velocity (r=− 0.624 and 0.556, respectively, both p<0.05), which imply that an ability to achieve a large tethered swimming force is associated with 50 m butterfly performance. These results indicate that the load-velocity profile is a useful tool for predicting and assessing sprint butterfly swimming performance.