Physical conditioning plays a vital role in training strategies designed to improve the fitness levels of basketball players (Balčiūnas et al., 2006). Conditioning programs are designed with specific interventions tailored to the characteristics of the discipline in which the athlete competes (Laursen and Buchheit, 2019; Sheykhlouvand et al., 2018a; Balčiūnas et al., 2006). Basketball is a high-intensity intermittent team sport requiring activities with maximal or near-maximal efforts (García et al., 2020). The game is characterized by high anaerobic glycolytic and aerobic oxidative demands, repeated change of direction (COD) challenging neuromuscular system, accelerations, decelerations, short distance sprints, jumps, physical contacts, and sport-specific skills (García et al., 2020; Heishman et al., 2020; Sekine et al., 2019; Hernández et al., 2018; Ben Abdelkrim et al., 2007). According to the literature, basketball players perform an average of 105 high-intensity runs with short duration (2-6 seconds) with 21 seconds rest intervals (Figueira et al., 2022). To achieve high-performance levels in repetitive high-intensity actions throughout basketball games, the energy demands rely on both anaerobic and aerobic energy metabolism while during low-intensity activities such as jogging, walking, and standing, aerobic energy metabolism is dominant (Arslan et al., 2022). Hence, improving both anaerobic and aerobic metabolic system is crucial for enhancing basketball performance.

Various sport-specific interventions have been introduced to improve these qualities in basketball players. High-intensity interval training (HIIT) is proven effective for enhancing metabolic capacities. Like the nature of HIIT, a basketball match involves periods of intensive sprinting, followed by short periods of moderate-to-low-intensity running (Garcia et al., 2020). Hence, HIIT could be considered a sport-specific conditioning approach for basketball players (Engel et al., 2018).

Many studies have developed sport-specific interval interventions, such as small-sided games, which are tailored to the unique requirements of basketball game dynamics and have compared them with traditional running-based HIIT (Arslan et al., 2022; Klusemann et al., 2012). Researchers believe that when exercise mimics movement patterns specific to the game, it brings about the simultaneous enhancement of technical skills under demanding physical conditions. Such approach motivates athletes to engaging in basketball-specific conditioning than conventional training methods, leading to the better transmission of physiological adaptations (Klusemann et al., 2012; Delextrat and Martinez, 2014). However, there are limitations to such interventions in question.

While these methods imitate basketball-specific movement patterns, they primarily aim to enhance athletes' skills under high-intensity exercise rather than directly focusing on athlete's conditioning. Although game-based interval interventions enhance aerobic and anaerobic training, their adaptive responses cannot be compared with traditional HIIT, given that the running distance and total work are rate different, making matching exercise loads difficult. More importantly, different numbers of high-intensity activities performed during the game-based interventions result in an inter-individual difference in the adaptations and prevent uniform adaptive response to the training (Castagna et al., 2011; Matthew and Delextrat, 2009; Ben Abdelkrim et al., 2007). Accordingly, in this study, we aimed to examine the effects of sprint interval training (SIT) program, known as one of the practical models of HIIT capable to induce positive improvement in performance capacity and skeletal muscle energy metabolism (Bayati et al., 2011; Sheykhlouvand et al., 2018b), using basketball-specific drills with a ball (SSIT). We directly compare it with a traditional running-based SIT program without ball using a research design that matched groups concerning total time commitment and repetitions, training frequency (2 sessions a week), and training duration (6 weeks) but differed in modality (running vs. running + ball drills). The effects on aerobic and anaerobic performance and hormonal changes were examined. Identifying a sport-specific SIT mimicking the game while imposing the same training load as traditional SIT to improve basketball-specific performance would be of value. Given the combination of ball drills with SIT and greater motivation of athlete’s during sport-specific movement causing to enhance and maintain intensity and increase the athlete’s physiological response (Aguiar et al., 2012), we hypothesized SSIT may result in more sport-specific adaptations than traditional SIT.

No pre-training difference (p ≥ 0.05) was observed for the measured variables, and the CON group showed no statistically significant changes over time.

There was a significant main effect of time (p = 0.001) and a group × time (p = 0.001) interaction for the VJ (Table 2). The SIT group demonstrated a medium increase in the VJ (%Δ = 7.5, p = 0.001, d = 0.58, 95% CI = -0.31 to 1.48) performance, but the SSIT group demonstrated a significantly large increase in the VJ performance (%Δ = 12.5, p = 0.001, d = 0.95, 95% CI = -0.03 to 1.87) (Figure 4, A). No significant pre- to post-training change was observed for SLJ in SIT and SSIT groups (Figure 4, B).

A significant time × regimen interaction (p = 0.001) was found in 20-m sprint time. As shown in Table 2, the change in 20-m sprint time in SIT and SSIT groups was significantly greater than that of the CON group (p = 0.001, d = -0.34, and p = 0.0001 d = -0.45, respectively). The SIT group demonstrated a significantly small decrease in the 20-m sprint time (%Δ = -2.9, d = -0.32, 95% CI = -1.21 to 0.56), but the SSIT group demonstrated significant medium decreases in the 20-m sprint time (%Δ = -4.3, d = -0.69, 95% CI = -1.59 to 0.21) (Figure 4, C).

A significant group × time interaction (p = 0.001) was observed for TT and IAT performance. The change in IAT performance in SIT and SSIT groups was significantly greater than that of the CON group (p = 0.0032, d = -2.11, and p = 0.0001 d = -2.25, respectively). Also, the change in IAT in response to SSIT was significantly greater compared to SIT (p = 0.01, d = -0.49, 95% CI = -1.39 to 0.4) (Table 2). The SIT group demonstrated a significantly small decrease in the TT time (%Δ = -1.8, p = 0.0311, d = -0.46, 95% CI = -1.35 to 0.43) and a very large decrease in IAT time (%Δ = -4.5, p = 0.0011, d = -2.01, 95% CI = -3.09 to 0.94) pre- to post-training. Also, the SSIT group demonstrated a significantly large decrease in the TT time (%Δ = -2.7, p = 0.002, d = -1.14, 95% CI = -2.09 to 0.20) and a very large decrease in IAT time (%Δ = -5.4, p = 0.0001, d = -1.93, 95% CI = -3.0 to 0.87), over the training period (Figure 3, E and F).

There was a significant time × regimen interaction (p = 0.001) for the Yo-Yo IR1 performance test. The change in this variable in response to SIT (%Δ = 18.5, p = 0.002, d = 2.19) and SSIT (%Δ = 23.7, p = 0.001, d = 2.56) groups was significantly greater (p = 0.0001, d = 2.3, and p = 0.0001, d = 2.81, respectively) than that of CON group.

Although both SIT (p = 0.001, d = 2.19, 95% CI = -1.08 to 3.30) and SSIT (p = 0.001, d = 2.56, 95% CI = -1.37 to 3.74) groups demonstrated significant very large increases in Yo-Yo IR1 performance (Figure 3, G). SSIT indicated greater improvement in this test than to SIT over time (p = 0.001, d = 0.44, 95% CI = -0.44 to 1.33) (Table 2). However, both the SIT (%Δ = 4.9, p = 0.001, d = 2.22, 95% CI = 1.11 to 3.33) and SSIT (%Δ = 6, p = 0.001, d = 2.57, 95% CI = 1.39 to 3.76) groups demonstrated a significantly very large increase in V̇O_2max (Figure 3, H). Also, the change in V̇O_2max in SIT and SSIT groups was significantly (p = 0.0001, d = 2.33, and p = 0.0001, d = 2.82, respectively) greater than the CON group.

After the 6-week training program, both the SIT and SSIT groups displayed a significantly (time, p = 0.001; group × time, p = 0.001) higher TEST levels (p = 0.0021, d = 1.52, and p = 0.0011, d = 1.59, respectively) and lower CORT levels (p = 0.038, d = -0.37, and p = 0.031, d = -0.64, respectively) than the CON group (Table 2). The SIT group demonstrated a significant very large increase in the TEST (p = 0.001, d = 1.52, 95% CI = 0.52 to 2.51) and a small decrease in the CORT (p = 0.001, d = -0.37, 95% CI = -1.52 to 0.52) pre- to post-training. Also, the SSIT group indicated a significantly very large increase in the TEST (p = 0.006, d = 1.59, 95% CI = -0.58 to 2.59) and a medium decrease in CORT (p = 0.001, d = -0.64, 95% CI = -1.54 to 0.26) over time (Figure 3, I and J).

SIT, SSIT, and CON didn’t alter 1RM_LP across time (Table 2).

The present study aimed to compare the effects of traditional SIT and sport-specific SIT (SSIT) on physiological and biochemical adaptations and bio-motor abilities in male basketball players. The most striking finding of the present study was that both traditional SIT and SSIT significantly improved the abovementioned parameters. However, effect size values indicate greater effects of SSIT on aerobic and anaerobic performance than SIT.

Research has shown a positive relationship between aerobic fitness and power recovery between repeated bouts of intensive interval exercise (Laursen and Buchheit, 2019). This observation implies that aerobic fitness plays a pivotal role in a crucial aspect of basketball performance, i.e., the capacity to execute repeated sprints (Aschendorf et al., 2018). The increased running distance completed during the Yo-Yo IR1 test in both SIT and SSIT groups could also verify this improvement. In the present study, both SIT and SSIT imposed an effective stimulus for improving V̇O_2max and significantly enhanced this indicator. Our findings corroborate previous studies reporting enhanced aerobic fitness following game-based (Arslan et al., 2022; Aschendorf et al., 2018) and traditional (Bayati et al., 2011) interval interventions. The enhancement of V̇O_2max can be attributed to increases in two fundamental aspects of aerobic fitness: the central component, involving the improved delivery of oxygen, and the peripheral component, which signifies the enhanced utilization of oxygen by the active muscles (Sheykhlouvand et al., 2016a; Fereshtian et al., 2017; Rasouli Mojez et al., 2021; Sayevand et al., 2022; Sheykhlouvand et al., 2022).

Anaerobic energy metabolism is the primary determinant of high-intensity movement performance, such as jumping, sprinting, and change of direction (Arslan et al., 2022). Both SIT and SSIT significantly enhanced these sport-specific bio-motor abilities, indicating their positive effects on anaerobic power. The increase in VJ observed in this study (SIT: 7.5%; SSIT: 12%) was in conjunction with previous studies employing different SIT regimens (Arslan et al., 2022; García-Pinillos et al., 2017). However, some researchers failed to show the positive effects of SIT on VJ (Aschendorf et al., 2018). The observed disparities in the outcomes might stem from variations in the duration of the training, gender, fitness levels of the participants, and the specific mode of training employed. Enhanced explosiveness in VJ could be attributed to parameters such as reactive strength and muscular power (Panoutsakopoulos and Bassa, 2023). However, neither SIT nor SSIT enhanced 1RM_LP, indicating that enhanced neuromuscular adaptations such as increasing rate of force development and firing rate of muscles (Buchheit and Laursen, 2013) and anaerobic power production of plantar flexors and knee extensors (Maffiuletti et al., 2002) could be a possible explanation for improved VJ. We can speculate implementing SSIT, involving sport-specific drills such as dribbling, passing, and shooting exercises, resulted in more significant neuromuscular adaptations than regular SIT, leading to greater training effects with an effect size of 0.95 vs. 0.58. Nonetheless, further investigations are necessary to elucidate the specific adaptations achieved through this approach.

Regarding the sprint performance, both SIT and SSIT groups enhanced this locomotor ability after six weeks. An increase in sprint acceleration and velocity due to interval intervention involves fast-twitch muscle fiber and also improvements in stride length resulting in sprint gains (Lee et al., 2020). Our finding is in accordance with previous studies reporting a positive transfer of SIT to sprint performance (Clemente et al., 2022). SSIT indicated greater changes in the 20-m sprint than SIT (medium vs. small ES). The possible mechanism explaining such a difference could be the enhanced acceleration component of the maximal sprint test due to sport-specific movements during SSIT (Arslan et al., 2022). Both SIT and SSIT significantly diminished TT and IAT time. In addition, the changes in IAT were significantly greater in the SSIT than in the SIT. Likewise, Arslan and colleagues (2022) have shown small vs. moderate training effects of HIIT and small-sided games on these parameters. COD presents a key attribute in basketball. A quick COD requires rapid force development and high power generation by the lower extremities (Miller et al., 2006). In COD ability tasks, the leg extensor muscles undergo swift transitions between eccentric and concentric muscle actions, accompanied by minimal ground contact time (Miller et al., 2006; Clemente et al., 2022). Effect size results indicate a greater impact of SSIT on COD, which could be attributed to the sport-specific drill during SSIT (i.e., forward, dribbling, and CODs). By challenging the neuromuscular system and decision-making ability through basketball-specific drills, such movements may indirectly benefit the ultimate COD better than linear running (Arslan et al., 2022).

Both SIT interventions were associated with an increase in TEST levels and a decrease in serum CORT concentrations. Our results corroborate previous findings (Sheykhlouvand et al., 2016b; Ambroży et al., 2021), indicating anabolic-type effects of intensive interval training. Typically, elevations in resting TEST with reductions in CORT show an anabolic environment and increase performance capacity in athletes. Enhanced resting TEST levels represent a favorable hormonal environment when attempting to maximize performance adaptations.

This study possesses certain limitations that warrant consideration when interpreting its findings. Firstly, the study exclusively involved male subjects, which restricts the generalizability of our results to the broader population. Gender-based differences in physiology and responses to interventions may exist, and further research with diverse participant groups is necessary to ascertain the applicability of our findings to women.

Secondly, the study acknowledges the potential influence of external factors outside of the intervention, such as dietary habits, sleep patterns, and overall training load. While we tried to control these variables and maintain consistency among participants, we cannot entirely exclude the impact of these factors on the observed outcomes. Future research could employ more rigorous control measures or investigate these external factors as variables of interest to understand their effects on the studied intervention better.

In conclusion, the results in the present study support the hypothesis that incorporating SIT and SSIT into typical basketball training of male basketball players during the off-season phase of the athletes’ annual training program can induce more significant improvements in aerobic fitness, anaerobic performance, and hormonal adaptations. Specifically, the post-training analysis indicated that both interventions were linked with enhanced aerobic fitness, VJ, COD, linear speed, and anabolic hormonal status. The effect size values indicated more significant effects of SSIT than SIT in most physiological and sport-specific adaptations. Such a superior effect could be attributed to the more basketball-specific movement pattern of the SSIT. We speculate technical drills and tactical exercises related to a team’s success influence the players’ motivation to enhance and maintain intensity and increase the athlete’s physiological response. Moreover, sport-specific practices may impose more challenging movements mimicking the game and cause more significant gains than SIT performed on a direct track.