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Participant characteristics
Participant characteristics and JBI scores across the 43 eligible studies are summarised in Table 1. A total of 1837 participants are included in this review, where mean ages ranged between 10.3 ± 1.0 and 17.5 ± 3.5. The competition level of participants was reported in all but 13 studies who either stated [9, 16, 21, 50, 70,71,72] or did not state the participants were competitive [29, 35, 42, 43, 52, 60]. For studies who stated competitive level, one included only county level participants [41], one included only regional level participants [62], thirteen included only national level participants [1, 2, 5, 12, 15, 17, 44, 53, 61, 74, 76, 81, 86] and one included only international participants [23]. Twelve studies recruited a combination of participants who were competing at either national or regional level [13, 25, 26, 36, 38, 39, 51, 55, 56, 78, 82, 83], one recruited international and national level participants [58] and one included regional, national and international participants [31].
Study design and JBI Scores
Over the 43 studies, swimming velocity, swimming trials, personal best times, LEN Ligue (Européenne de Natation)/FINA points were used as the swimming performance parameters. LEN/FINA points are calculated by relating personal best times to current world records via mathematical equation [22].
Across the 43 studies, a total of 18 measured strength and power variables, with three studies measuring only strength [2, 26, 58], five measuring only power [41, 53, 55, 56, 70] and ten measuring at least one variable of each [23, 25, 38, 39, 44, 50, 62, 67, 76, 80]. One study directly measured the propulsion force of the arms during swimming as the strength and power test [15]. Three of the 18 studies investigated the influence of strength and power variables in relation to swimming start and/or turn performance [23, 38, 39], the remainder of studies researched strength and power variables with swimming performance alone.
Energetic measures were explored relative to swimming performance in 29 papers in this review. Studies reported BL values [12, 36, 51, 52, 58], measures of V̇O2 [9, 41, 62, 81, 82] or BL and V̇O2 [1, 17, 21, 31, 35, 38, 39, 61, 67, 71, 72, 74, 86], with one study measuring V̇O2 and anaerobic power [16] and one measuring anaerobic power alone [29]. Investigations also operated test measurements representing energetic capacities including critical speed [13, 52, 53], lung capacity [50] and a shuttle run endurance stage test [76].
A measurement of body composition in relation to swimming performance was incorporated into the design of 18 studies included in this review. Ten studies reported only a measure of body fat [5, 13, 15, 16, 25, 41, 51, 53, 71, 76], three only LBM or fat free mass [38, 82, 83] and four reported both [39, 52, 62, 78]. Methods of obtaining these measures included bioelectrical impedance [62], densitometry [38, 39, 41], absorptiometry [52, 78] and skin folds [5, 13, 15, 16, 25, 51, 53, 76, 82, 83].
A total of 14 studies stratified their sample, two by grade of performance [5, 55], two by age [78, 83], one by age and performance [41], eight by gender [9, 12, 25, 29, 51, 52, 62] and two by gender and performance [53, 76]. The remaining studies did not stratify their samples. Seventeen studies conducted a maturity assessment amongst their participants [13, 15, 16, 21, 25, 35, 38, 39, 51,52,53, 55, 56, 62, 70, 76, 86].
Of the studies included in this review, 95.35% (41) were cross-sectional and 4.65% (2) were randomised-controlled trials. All cross-sectional studies scored 4, 5, 6, 7 or 8 and randomised-controlled trials scored 8 or 9 on their respective JBI checklists. 81.4% of cross-sectional studies had points deducted for failing to describe inclusion criteria. Differences in JBI scores were due to investigations not describing participants in detail, failing to identify confounding factors, not providing strategies to deal with confounding factors and not using appropriate statistical analysis. For randomised controlled trials, each study had points deducted for items relating to blinding of participants, treatment and assessors. These factors are challenging to control in training intervention studies.
Maximal strength and explosive power measures
Evidence for greater strength and/or power being a contributing factor for better swim performance was found in 18 studies, whether via simple correlation or multiple regression analysis (Table 2). A mixture of isokinetic and multi joint actions were used to measure strength and power across the included studies.
Multi-joint exercises were used in five studies, where 1-repetition maximum tests (1RM) were used by Amara et al. [2], Keiner et al. [38] and Keiner et al. [39]. Significant relationships between 1RM, swimming [2, 28, 39] and start performance [38, 39] were reported, where greater 1RM scores were associated with superior performance. 1RM push-up was associated with faster times in the 25 and 50 m front crawl and front crawl arms only [2]. Keiner et al. [38] reported moderate correlations between 15 m, 50 m and 100 m freestyle with bench press and squat 1RM when combined in a multiple regression analysis, where higher 1RM scores were conducive to swim performance. Strong correlations were found with 5 m and 15 m start performance with 1RM squat scores alone, where stronger squatters had faster start times. Similarly, Keiner et al. [39] demonstrated higher 1RM scores were associated with faster swim times over multiple sprint distances (15-100 m) across freestyle, breaststroke and backstroke, where weak to very strong correlations with 1RM squat, bench press, bent over row, deadlift and sit-up. A sit-up test was used in another study, but was maximal repetition rather than 1RM, where a weak correlation was found between abdominal power and swim performance [76]. Loturco et al. [44] used isometric quarter-squat and bench press as their strength tests, but no significant correlations were found with 50 m and 100 m freestyle performance.
In the eight studies that used isokinetic dynamometer devices to evaluate muscle strength and power, all but one found significant relationships with swim performance [23]. This study investigated swimming start performance with isometric flexion and extension measures of the knee, where no significant correlations were found. Similar isometric measures of the knee were conducted in three other studies but were compared to freestyle swimming velocity [82], 50 m freestyle time [62] and 100 m and 400 m freestyle performance [78]. Weak to strong correlations were found between knee flexion and extension with freestyle velocity over 50 m [82], isometric knee extension force and 50 m freestyle time [62] and knee flexion and extension torque and power with 100 m and 400 m freestyle performance [78]. Two studies investigated relationships between isometric force of the shoulder and freestyle performance over various distances. Isometric shoulder flexion measures had weak correlations with 50 m freestyle time [62] and shoulder internal and external rotation presented moderate to strong correlations with 100 m and 400 m times [78]. Upper limb strength and power was also measured by Girold et al. [26] where flexion and extension measures of the elbow showed moderate to strong correlations with 100 m freestyle performance under isometric and concentric conditions. One study measured the propulsion force of the arms during 30 s maximal freestyle efforts using a dynamometer. This measurement was considered a key predictor of 50 m freestyle performance in this study when used in an allometric approach alongside other variables [15]. Handgrip strength displayed moderate to strong correlations with swimming performance or velocity in three studies for males [25, 62, 78] and one in both males and females [77].
Jump performance was assessed in 14 studies, where tests including countermovement jumps (CMJ), squat jumps (SJ) and broad/horizontal jumps (HJ) were used. Weak to very strong correlations were found between CMJ, SJ and HJ measures with start performance [23, 38, 39] and swim performance [25, 39, 44, 50, 53, 62, 70, 76, 78, 83]. One study found no relationship between vertical jump and swim performance, but the type of jump was not stated [41]. Morais et al. [55] conducted a cluster analysis between their participants, finding SJ (0.34 m ± 0.06 vs 0.24 m ± 0.03, F = 11.18, p < 0.001) and CMJ (0.36 m ± 0.05 vs 0.26 m ± 0.03, F = 11.16, p < 0.001) score discriminated the talented, faster swimmers from the non-proficient swimmers, respectively. Turn performance was analysed in one study, revealing SJ and CMJ had strong correlations with turn performance to 5 m [38]. Potdevin et al. [70] conducted a maximal glide test, where scores improved after 6 weeks of plyometric training (2.28 ms ± 0.19 vs. 2.41 ms ± 0.27, p < 0.05, ES = 0.26). Alongside jump measures, Morais et al. [56] found a moderate correlation between medicine ball throwing velocity and 100 m freestyle performance and Morias et al. [55] characterised faster, talented swimmers as having higher medicine ball throwing velocity compared non-proficient swimmers (7.58 ± 0.28 vs. 6.07 ± 0.81 ms, F = 8.18, p = 0.002).
Anaerobic and aerobic measures
Testing related to anaerobic and aerobic measures occurred in 30 studies, all of which found at least one relationship between an anaerobic and/or aerobic variable and swim performance (Table 3). Assessment of anaerobic and aerobic profiles of participants was commonly through BL, V̇O2 measures, force, power and velocity profiles.
Tests relating to anaerobic determinants of swimming performance were used in eight studies. Tethered swimming performance over 30 s [12, 58, 61] and 22.9 m [41] showed moderate to very strong correlations with swimming performance. Papoti et al. [60], also found moderate to strong correlations between 100 m, 200 m and 400 m freestyle performance with anaerobic impulse capacity and critical force over four short, tethered swimming bouts. Tests using ergometers to assess anaerobic measures were conducted for the upper [29] and lower body [16, 29], where measures of force, power and fatigue were associated with swim performance. Anaerobic power was also measured using average velocity in an 8 × 25 m all out swimming test which showed moderate correlations with 100 m freestyle performance [13]. In one study, speed endurance during a specific swimming test was reported to have a moderate correlation with LEN scores [76]. Pardos-Mainer et al. [62] presented a moderate correlation between 30 m sprint running velocity and 50 m freestyle time.
BL profiles were measured across 13 studies, which used tethered [12, 36, 60, 61] and free-swimming tests [17, 21, 42, 43, 51, 61, 71, 72, 74] to assess these parameters. Net change in BL concentration was analysed in relation to swim performance in two investigations, one found a moderate correlation with 100 m freestyle performance [43] and one did not report it was a successful predictor of performance [42]. Three studies measured BL concentration after a single maximal effort bout of swimming, one found no relationship [72], the other two found weak to strong correlations with performance improvements over time [21] and mean swimming speed [74]. Ribeiro et al. [72] found a strong correlation between velocity at BL 4 mmol and maximal swimming velocity. One study identified relationships between infra and supra intensities of maximal lactate steady state with 800 m freestyle and 400 m freestyle performance at infra intensities only [17]. Lactate threshold was measured by Papoti et al. [60], who found strong correlations with swim performance across multiple distances. Lactate minimum tests and its related parameters were associated with swim performance in four studies [12, 36, 51, 52].
Measurements of V̇O2 were observed in 17 studies [1, 9, 16, 17, 31, 35, 41,42,43, 60,61,62, 71, 72, 81, 82, 86]. V̇O2peak was measured in seven studies, four of which showed weak to strong relationships with swimming performance [1, 35, 42, 82]. One analysis showed V̇O2peak was a contributor to swim performance when entered into a multi-discriminant function with leg kick force, stroke efficiency and muscularity [41]. Two studies found no relationships between V̇O2peak and swimming performance [43, 86]. Measures of V̇O2max showed moderate to very strong relationships with swimming performance in seven studies [9, 16, 17, 60, 62, 72, 81]. One investigation measured aerobic capacity via a staged shuttle run and 30-min swim test, where weak and strong correlations were found between tests and LEN scores [76]. Another study measuring aerobic capacity through swimming tests found that 400 m freestyle velocity and maximal lactate steady state (MLSS) were correlated to this measure [61]. One study found that measures of V̇O2 and aerobic power were associated with faster 100 m freestyle performance [31]. Three studies investigated critical speed, a measure of aerobic threshold, finding weak and moderate correlations with swimming performance [10, 46, 52]. One study measured lung capacity which was found to be a predictive factor of 50 m freestyle performance when used in regression models [50]. Breaststroke performance for the 100 m and 200 m events was successfully predicted by combinations of BL and V̇O2 in a study evaluating breaststroke performance measures [71].
The energy cost of swimming, which considers anaerobic and aerobic components of swimming performance, was measured in four studies. Relationships were reported in two investigations that found links between energy cost, 100 m freestyle performance [43] and national ranking over multiple distances [86]. The other studies did not report performance links but did show relationships between energy cost and maturation stage [35, 42].
Body composition measures
Out of the 18 studies that investigated body composition, seven found some relationship with swimming performance (Table 4). Six studies found weak to very strong relationships between BF% [5, 15, 62, 71, 76, 78] and swim performance, however, each did not identify BF% as a predictive factor. Saavedra et al. [76], identified a weak correlation between swimming performance and lower BF% in males, but no association in females. Seffrin et al. [78], found higher BF% was very strongly associated with faster swim times in females, but had no association in males. Klika and Thorland [41], identified greater fat mass was associated with faster sprint swimming times. Mitchell et al. [53], found 100 m freestyle and 200 m freestyle swimmers had significantly different BF% (62.9 vs. 68.9, p < 0.01). One study found that faster swimmers could be categorised by BF%, where faster swimmers had overall lower sum of skinfolds than slower swimmers [5]. Six studies identified LBM [52, 78, 82, 83] and fat free mass [35, 42, 62] as having weak to very strong relationships, where higher levels were beneficial to performance. Pardos-Mainer et al. [62] did not report fat free mass was a predictive value, although it showed a moderate correlation with swimming performance. Other investigations found no significant relationships with body composition measures and swim performance, including BF% [13, 16, 25, 43, 51], LBM [41] and fat free mass [43].
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