This investigation was approved by the Faculty of Human Kinetics Institutional Review Board (approval number 37/2021) and conformed to all standards of human research set out in the declaration of Helsinki (34). The trial was registered at clinicaltrials.gov as NCT05228236 (https://clinicaltrials.gov/ct2/show/NCT05228236). Prior to engaging in any of the study procedures, the purpose and design of the study, the data collection methodologies, and all potential risks and benefits were explained to potential research participants. All participants gave their verbal and written informed consent before enrolling.

Fifty male futsal players, not engaged in RET, at the time of the investigation, volunteered to participate in this 8-week study. From the initial sample, forty completed the investigation. Participants were between the ages of 18 and 35 y and were recruited from national level futsal sports clubs. They were randomly assigned to one of two groups: novel plant-based protein (PB) or whey protein (WP). For details, please refer to the CONSORT flow diagram (Figure 1). Baseline measures were performed pre-season while wk 4 and 8 were assessed during the competitive season, in the first half of the regular phase of the championship.

The final sample was comprised of both professional and semi-professional players. The professional players (n = 16) participated in the Major Portuguese National Futsal League “LIGA PLACARD” and had a sport-specific training frequency of 5 times per week (5×/wk) and a weekend game frequency of 1×/wk. Each training session lasted ~1.5 h.

The semi-professional players (n = 34) participated in either the second (n = 17) or third (n = 17) Portuguese National Futsal League. Training sessions lasted ~1.5 h for both teams and athletes had a training frequency of 3×/wk and a weekend game frequency of 1×/wk.

Participants represented the top five teams of each division and included players from the current and former national team. Although the players were from different teams, they had similar training schemes, where sport-specific training regimen was normally comprised of mobility and injury prevention exercises for ~20 min, followed by technical and tactical components for ~30 min. The remainder of the training session was dedicated to open exercises, mimicking game conditions. RET was not part of the coaches' training prescription at the initial phase of the season, nevertheless, three players reported that they occasionally went to the gym on their own to perform RET.

Athletes' anthropometry, body composition, strength, power, aerobic performance, nutritional intake, health, and safety biochemical parameters were assessed at baseline and week 8. A partial evaluation was performed in week 4 that included anthropometry, body composition, strength, power, and nutritional intake assessment. All evaluations of the participants, including blood and saliva samples collection, were performed in our laboratory facilities, early in the morning (7 a.m.) after a 12-h fast and without consumption of alcohol, caffeine/stimulant beverages, and at least 12 h from the last exercise session. Biofluids and body composition assessments were performed fasting, while the performance evaluations were made in a fed state, with the consumption of a meal replacement bar (nutritional composition: 231 kcal, 14 g fat, 12 g carbohydrate, and 13 g protein).

IBM SPSS Statistics version 25.0, 2012 (IBM, Chicago, Illinois, USA) was used to analyze the data. Basic descriptive statistics were run to characterize the study participants. All variables were assessed for normality using the Kolmogorov–Smirnov test. Independent sample T-tests were used to compare means between groups at baseline. Post-hoc intention to treat (ITT) analysis was applied to investigate the effects of intervention over time within and between groups through generalized estimated equations (GEE) analyses. Time and time-by-group interactions were analyzed by analysis of covariance (ANCOVA), using baseline measurements as the covariate. The equality of the matrix of variance and sphericity were explored with the Levene F-test and Mauchly's test, respectively. Significance for α was set at p ≤ 0.05.

We found no differences between groups regarding all body composition variables when comparing PB and WP in professional and semi-professional futsal athletes. These findings are in line with previous populations (26–30, 35) but not with others (31, 32, 50, 51). Of note, a study by Babault et al. (28) that compared pea protein with whey used 25 g 2 times a day (50 g daily) on untrained subjects. Compared to the present study, this investigation (28) was of longer duration (12 wks), used only three exercises (involving elbow flexor and extensor muscles), and involved a higher daily protein supplementation in untrained men. Moreover, Babault et al. (28) did not control the dietary intake and the pea protein supplement offered a lower amount of leucine per serving than in our study (1.6 vs. 2.2 g). Another study compared pea protein with whey protein, in trained subjects (35), performed a combination of high-intensity functional training (HIFT) and no differences were found between groups after 8 wks of HIFT, with only a time effect being reported regarding 1-RM squat and deadlift. Limitations in that study included a small sample size (n = 15) and the use of a BIA model with questionable accuracy (52, 53).

Studies from Joy et al. (26) and Moon et al. (27) that compared rice protein with whey protein also presented several limitations. As acknowledged by the authors, sample sizes were relatively small (n = 24) and the Moon et al. (27) work lacked training supervision. Moreover, neither study employed a direct measure of hypertrophy, which may have limited the ability to detect subtle longitudinal changes in muscle mass (54). The sample in our study was comprised of professional and semi-professional futsal players without RET exposure, which explains the absence of a time effect pertaining MT and fat free mass (FFM) gains, even when consuming at least 1.6 g/kg BW.day⁻¹ of protein (16). Still, the FFM gains in both groups are in line with the values reported in some meta-analysis (16, 55) and with the works by Joy et al. (26) and Moon et al. (27) using rice protein. Our results pertaining to MT are also consistent with the work by Banazsek et al. (35), who found no differences between pea protein and whey protein after 8 wks of HIFT.

In contrast, Volek et al. (32) reported superior increases in FFM favoring WP vs. soy protein in untrained subjects. It should be noted that the supplements used by Volek et al. (32) also provided carbohydrates and the soy protein supplement provided a lower amount of leucine than the PB in our study (1.4 vs. 2.2 g). Furthermore, the amount of leucine provided from both supplements in Volek et al. (32) differed greatly (1.4 g of leucine in the soy protein group vs. 2.2 g in the WP), which is particularly important given the recommended leucine dosage for maximizing muscle protein synthesis (1.7–3.5 g per meal) (24, 25). Other studies that reported conflicting findings with ours did not compare isolated protein sources (50), and assessed dairy protein vs. soy protein in elderly participants (31).

In our study, a time effect was noted regarding FM loss, with no differences between groups. These results are in agreement with some studies (26, 27, 32) but not others (28, 35). This might be explained by the reduced energy availability in both arms of our study (PB: 35.8 ± 7.1; WP: 37.1 ± 6.4 kcal/kg FFM), which seems more appropriate for fat loss (56). Moreover, research indicates a higher protein intake might mitigate FFM loss during periods of energy restriction (57, 58), which might explain the FM reduction while maintaining FFM. Taken together, the absence of a RET protocol and the reduced energy availability in our trial might explain the lack of a time effect pertaining to FFM gains and the reduction of FM in both conditions. Furthermore, since the dietary intake did not change throughout the study, one might speculate that a natural increase pertaining to in-season training volume might have led to the reported FM reduction in both groups.

No differences were found between groups regarding both muscle strength markers, nor did we observe a time effect. These results are in contrast with protein supplement research performed in combination with RET (26–28, 32, 35). Since our sample was comprised of futsal players not engaged in RET, these results are not surprising. A meta-analysis by Morton et al. (16), found that protein supplementation has little effect on strength when compared to RET when individuals consume >1.6 g/kg BW.day⁻¹ of protein. Similar results have been reported regarding protein supplementation on muscle force production with both acute and chronic concurrent training (59). Still, when comparing our results with the study from Banazsek et al. (35), which used a sample closer to ours (HIFT), our results are in line with all findings except for 1-RM. It could be hypothesized that protein supplementation might improve performance via enhanced recovery. However, a recent study showed no differences between a high intake of pea protein or WP when compared with water intake on post-exercise delayed onset muscle soreness (60), casting doubt on the hypothesis.

No between-group differences or time effects were found regarding anaerobic or aerobic performance. Few studies have investigated the effects of protein supplementation on anaerobic (59) and aerobic performance (61–63). Regarding protein supplementation on muscle power Camera et al. (59) showed similar results to ours. Also, it seems that when adequate amounts of carbohydrates are consumed, protein supplementation does not further increase aerobic performance (24). Moreover, our results agree with a recent systematic review showing that protein supplementation increases myofibrillar but not mitochondrial protein synthesis (64), consequently failing to enhance whole-body aerobic power (i.e., VO_2max).

No effects of time or group were detected regarding all hematological and biochemical markers. Only one previous study by Nieman et al. (60) compared pea protein vs. WP after a 90-min eccentric exercise bout regarding proxy markers of muscle damage (CK) in non-athletic, non-obese males. Results showed that WP delayed the elevation of CK to a greater extent than pea protein or water. These results conflict with ours since we did not find any differences between groups. Discrepancies in findings can potentially be explained by the fact that we studied a different population (trained futsal players) and did not include a specific muscle damage-inducing protocol. Moreover, we used a novel protein/BCAA matrix that combined not only pea protein but also yeast protein and BCAA as well, yielding an equal amino acid profile to whey protein.

Regarding ALT and AST (proxy markers of liver health) our null findings align with those of Nieman et al. (60). The lack of changes in eGFR and creatinine in our study is consistent with a plethora of research showing that relatively high protein diets do not have negative effects on renal health in healthy individuals (65–67) or even in overweight/obese individuals with mild kidney function impairment (68). In brief, both proteins displayed a good safety profile after 8 wks of supplementation, with no changes in inflammatory markers (CRP), red blood cell profile (Hct), liver (ALT/AST), glucose or kidney function (creatinine, eGFR), being observed between groups.

This is the first study to compare a plant-based protein vs. whey in professional and semi-professional team sports athletes (i.e., futsal). Few (or no) studies have compared the effects of a protein source when provided as supplemental protein outside RET or strength/power sports (61–63), with only one comparative study being performed in collegiate female basketball players (whey vs. casein) (69). Furthermore, we supplemented with an iso-energetic, iso-nitrogenous, iso-EAA novel plant-based protein/BCAA mixture that matched whey protein, using yeast protein for the first time. Moreover, we assessed not only body composition using multiple gold standard methods but also anaerobic and aerobic performance, as well as several hematological and biochemical markers, thus providing a complete longitudinal view of the effects of both proteins. While this study provides novel insights, it nevertheless presents some limitations. For one, the inclusion of a placebo/control group would have added important information to the findings. In addition, we did not assess the effectiveness of the blinding and thus cannot be completely sure that there was not a residual placebo effect. Additionally, the participants spontaneously reduced their protein intake from other sources, when supplementing with either protein. Albeit not interfering with their usual diet adds ecological validity to our study, it precludes any conclusions from an increase in dietary protein. Moreover, extending the study length to 12 wks or more and employing a RET protocol in both groups would have provided additional insights into the effects of the proteins on measures of strength and body composition. It is also important to bear in mind that DXA, as well as BIA-derived parameters, have different instrumental sensitivities thus not allowing for direct comparisons between studies that measure R, Xc, and/or water compartments with different technologies or sampling frequencies (70, 71). As previously discussed, although not changing the diet of the participants adds ecological validity to this study, this might have influenced some performance outcomes (i.e., aerobic capacity) due to reduced energy and carbohydrate intake.