Effects of Small-Sided Games and High-Intensity Interval Training on Aerobic and Repeated Sprint Performance and Peripheral Muscle Oxygenation Changes in Elite Junior Basketball Players : The Journal of Strength & Conditioning Research

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Original Research

Effects of Small-Sided Games and High-Intensity Interval Training on Aerobic and Repeated Sprint Performance and Peripheral Muscle Oxygenation Changes in Elite Junior Basketball Players

Delextrat, Anne1; Gruet, Mathieu2; Bieuzen, Francois3

Author Information
Journal of Strength and Conditioning Research 32(7):p 1882-1891, July 2018. | DOI: 10.1519/JSC.0000000000002570
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During a basketball match, players are on the court for about 75 minutes and cover a total distance (TD) ranging from 6.4 to 7.6 km, including 1.7, 1.6, and 2.5 km of high-, moderate-, and low-intensity activities, respectively (1,41). It is a highly intermittent sport characterized by the repetition of short (about 2 seconds) high-intensity movements, such as sprints, lateral shuffles, and jumps, with a work:rest ratio of 1:3.6 in elite male junior players (1). This limited recovery time between high-intensity actions and the necessity to maintain a high quality of these actions to win matches highlight the need for a well-developed aerobic pathway, as it forms the basis of players' ability to recover between intense bouts (12). Indeed, it has been shown that a high level of aerobic fitness allows for quicker resynthesis of phosphocreatine during intermittent high-intensity actions (43). This latter has also been associated with a better repeated sprint ability (RSA) (3), which is a crucial determinant of basketball performance (10).

A number of longitudinal studies have highlighted the success of various types of aerobic training, including high-intensity interval training (HIIT) or moderate-intensity continuous training on aerobic and RSA performance (4,6,15). Small-sided games (SSGs) are currently viewed as the best physical conditioning method (both aerobic and anaerobic) for basketball players because they simultaneously develop physical abilities and technical and tactical skills (12,29). In addition, studies among various team sports consistently reported that training interventions relying on SSG or HIIT resulted in similar improvements in aerobic fitness assessed by continuous (13,32) or intermittent protocols (4,12,13,21), and other aspects of endurance performance, such as running economy and the velocity at the lactate threshold (24). However, contrasting results are observed in the literature regarding anaerobic performance, RSA, and perceived exertion. Indeed, the benefits attributed to SSG-based training on RSA performance (34,39) were found to be similar to those obtained after HIIT-based training (4), whereas one study did not find any improvement in RSA performance after either type of training (12). Finally, it has been shown that, compared with HIIT training, SSG training was associated with greater enjoyment and lower perceived exertion (21,32), and led to significantly greater improvements in anaerobic performance, such as 10- and 20-m sprint, agility, upper-body strength, and vertical jump height (12,23). Although these results are essential for strength and conditioning coaches, only one of the above-mentioned studies focused on basketball (12) and it did not investigate the peripheral mechanisms underlying the positive aerobic adaptations brought about by these 2 types of training.

To the best of our knowledge, only one study has investigated the peripheral adaptations after SSG training. Buchheit and Ufland (6) measured tissue saturation index (TSI) and postsprint muscle reoxygenation rate during an RS sequence using near-infrared spectroscopy (NIRS) before and after an 8-week HIIT period in various team sport players (including basketball, handball, and football players). Their main results showed that the training intervention led to a significant improvement in postsprint reoxygenation that was correlated with the improvement in RSA performance. The study provided some insights into the peripheral adaptations linked to aerobic training in team sports. However, to the best of our knowledge, there is no similar study specific to basketball players. It is therefore essential to add some knowledge in this area because the characteristics of basketball, such as its highly intermittent nature or the greater use of the vertical dimension compared with other team sports, lead to specific adaptations and a unique metabolic players' profile, such as lower aerobic fitness compared with handball and football players (1,33).

Therefore, the objective of this study was to compare the effects of 6 weeks of SSG and HIIT on aerobic fitness and muscle oxygenation changes during an RS sequence in elite male junior basketball players. We hypothesized that SSG and HIIT will result in similar improvements in aerobic and RSA performance as well as muscle oxygenation.


Experimental Approach to the Problem

The current study used a randomized parallel matched-group design with repeated measures, including a pre-testing session, intervention period, and post-testing session. Players in each team were matched according to their playing position (guard, forward, and center). Random allocation within each pair to either a small-sided training group (SSG, n = 10) or a HIIT group (HIIT, n = 10) was then performed by tossing a coin. Because the aim of the study was to investigate in-season training adaptations, testing sessions and training interventions took place during the first phase of the competitive season (mid-October to early December), after pre-season conditioning had taken place to avoid variations in players physical fitness. Tests were performed in a controlled indoor environment (temperature: 18.1 ± 2.6°, humidity: 59.9 ± 6.3%) at the same time of the day to minimize the influence of circadian variations on performance. During the entire duration of the study, players had the same type and volume of basketball training and HIIT or SSG were added to the training sessions to ensure that the differences observed could only be due to this additional training. Our intervention took place over 6 weeks, which is the duration recommended for aerobic performance modifications to occur (21,26). We measured aerobic performance using a well-established test (5). The RS sequence of 2 bouts of 15-second all-out sprint, separated by 15-second recovery (6) is not a typical basketball RSA test but it was chosen for its better reliability, less possibility for pacing, and its ability to induce important muscle deoxygenation levels (14). Although the test for aerobic performance included a warm-up, the RS was preceded by a 15-minute warm-up including jogs, sprints, jumps and changes in direction, followed by some dynamic stretching. Players were requested to start the testing sessions at least 2 hours after consuming a meal, and could drink water ad libitum during the tests (the amount was recorded as replicated in the post-tests). Finally, the originality of the study was to include muscle oxygenation measurements, which has never been undertaken on basketball players.


Twenty junior male basketball players (mean ± SD 14.3 ± 0.6 year old, age range 13-14 years old; 176.9 ± 13.0 cm; 74.9 ± 9.7 kg) were recruited from 2 teams competing in the French U15 national league during 2 different seasons (2012–2013 and 2013–2014). Both teams were trained by the same coach. They had an average of 5.2 ± 3.6 years of basketball playing experience. Subjects were excluded if they had had any lower limb injury in the past 6 months. Before testing, subjects and their legal guardians were informed of the study protocol and provided written informed consent. The study was approved by the local ethics committee. (Oxford Brookes University). Three players dropped off during the course of the study because of injuries occurring during competition and thus, the final sample included 17 players (SSG, n = 8; 14.1 ± 0.6 years old; 175.9 ± 13.5 cm; 73.5 ± 10.0 kg; HIIT, n = 9, 14.4 ± 0.5 years old; 177.6 ± 10.5 cm; 76.1 ± 9.5 kg).


Pre- and Post-testing Sessions

Testing consisted of 2 types of tests performed 24 hours apart. The first one was a test for aerobic capacity, which was estimated by the 30–15 intermittent fitness test (30–15 IFT) characterized by very good test-retest reliability (5). The speed and heart rate (HR) attained in the last fully completed stage were recorded as maximal aerobic performance (VIFT, km·h−1) and HRpeak (b·min−1).

The second type of test included 1 (pre-test) or 2 (post-test) RS sequences. The first RS test, completed in pre- and post-testing sessions, consisted in two 15-second all-out shuttle runs (S1 and S2) over a distance of 20-m, interspersed by 15 seconds of passive recovery. It is characterized by very good reliability (typical error of 1.2–2.2%) among measured variables (6). The main variables measured were distances (in meter) covered in S1 and S2, TD covered during the 2 sprints (in meter), and performance decrement (%Dec) calculated according to the following equation:

Where ideal time was defined as the greatest distance covered (either in sprint 1 or 2) multiplied by 2, and total time as the sum of the distances covered in both sprints (19). The second RS test was an adjusted RS (RSadj), completed in the post-test only. It was similar in structure to the first RS and consisted in a first sprint where the performance achieved during S1 of the pre-test RS was replicated (S1adjpost) and a second sprint performed at maximal speed (S2adjpost). To allow for the best possible replication of the distance covered during S1, verbal feedback was given to subjects throughout their run. The 2 RS sequences in the post-test were undertaken on 2 different days to allow for enough recovery, and their order was randomized.

During RSadj, variations in oxyhemoglobin ([HbO2], μM), deoxyhemoglobin ([HHb], μM), and total hemoglobin ([tHb], μM) were continuously measured at 10 Hz using a portable NIRS device (Portamon; Artinis Medical System, Zetten, the Netherlands), using the differences in light absorption at 750 and 850 mm. An arbitrary value for the differential path length of 3.83 was chosen (6) and changes in [HbO2], [HHb], and [tHb] are reported as a change from baseline (−30 seconds to the start of the test). The TSI (%) was calculated according to the following equation:

The NIRS probes were placed on the vastus lateralis muscle (about 10 cm from the superior border of the patella) of the leg used to change direction (always the same leg used to change direction), parallel to the vertical axis of the thigh. The probes were secured on the leg with elastic tape, and then covered by players' basketball knee-length shorts to minimize the intrusion of daily light. Skinfold thickness of the relevant part of the thigh was measured by a skinfold caliper (Holtain Ltd., Crymmych, United Kingdom) and was found to be below the threshold of 50% of the distance between emitter and receptor, which allowed the light to penetrate into the muscle probes (36).

Training Interventions

High-intensity interval training and SSG training interventions were performed during the season and added twice a week to basketball practice sessions for a total duration of 6 weeks. They were always performed at the start of the session, after a standardized warm-up, and matched for exercise duration. Both training programs followed a periodization plan based on progression, prevented overreaching, and used a short tapering period to optimize final performance. The HIIT training sessions consisted of intermittent running at 95% of players' VIFT for 15 seconds, followed by 15 seconds of active recovery (jogging), as described in Table 1. The type of SSG used was 2v2 on full length (28 m), and half width (7.5 m) court. Although this space is frequently used by coaches for its ability to allow 2 simultaneous full-court drills on one court, it has been investigated by only one study (12), and thus warrants further examination. Drills were played like a competition continuously for 3–4.15 minutes (separated by 2-minute recovery), with only man-to-man defense, and no free throws or time-outs. Scores were kept to encourage players' motivation and verbal encouragements were provided by the coach. Players were randomly allocated to pairs (guard and either a forward or a center), and new pairs were created for each training session. During training, HR (Suunto Pro Team Pack, Vantaa, Finland) was continuously monitored and perceived exertion (Borg CR-10, (18)) was recorded within 10 minutes of the completion of the SSG or HIIT part of one weekly session. Consequently, mean heart rate (HRmean) was calculated and expressed as a % of HRpeak. Apart from the SSG and HIIT training prescribed, both teams had comparable training loads throughout the study. A typical week consisted of three 2-hour basketball practice sessions (Monday, Wednesday, and Friday) and one match weekly (Saturday or Sunday), with no additional strength and conditioning. The focus of training sessions was technical and offensive tactical skills (Monday), individual offensive and defensive skills (Wednesday), and technical and tactical defensive skills (Friday).

Table 1.:
Description of the 6-week training programs and the associated perceived exertion (RPE) for the small-sided game (SSG) group and the high-intensity interval training (HIIT) group.*

Near-Infrared Spectroscopy Data Analysis

Data were averaged on 1-second basis, and a moving average (2 seconds) was applied to smooth the signal. Tissue saturation index values corresponding to 30 seconds before the start of the test, the start (0 second) and end (15 seconds) of S1, the start (30 seconds) and end (45 seconds) of S2, as well as at various points after S2 (corresponding to absolute time points of 60, 75, 90, 105, and 120 seconds) were extracted. The variation in TSI (delta TSI, Δ) between the start and the end of each sprint was calculated as TSI end − TSI start (26). Tissue saturation index values were also normalized as a percentage of the maximum change in TSI (ΔTSI) observed between rest and the end of S1 to take into account any difference in absolute end-sprint muscle deoxygenation level after training (9). A linear model was fitted to the linear part of the TSI curve in relation to time within the first 15 seconds of recovery after each sprint (from 15 to 30 seconds for S1 and from 45 to 60 seconds for S2) (27).The slope of the relationship was retained as an index of reoxygenation rate (%·s−1), allowing for the calculation of post-S1 reoxygenation, post-S1 reoxygenation normalized (post-S1 reoxygenation [n]), post-S2 reoxygenation, and post-S2 reoxygenation (n). Although this type of modelization was used in a similar previous study (6), other authors used an exponential function (40); however, the protocol of this study (15-second recovery periods) did not allow for an exponential modelization. Moreover, the use of an exponential function after S2 was also not possible in some of the subjects because the early part of the muscle reoxygenation curve was sometimes blunted, as illustrated in Figure 1).

Figure 1.:
Variations in oxyhemoglobin ([HbO2]), deoxyhemoglobin ([HHb]), total hemoglobin ([tHb]), and tissue saturation index (TSI) before, during, and after the two 15-second sprints (S1 and S2) separated by 15 seconds of passive recovery before the training interventions.

Statistical Analyses

Each dependent variable was presented as mean (mean ±SD), with 95% confidence interval limits for the differences tested. After checking for parametric assumptions (Shapiro-Wilk test), 2- and 3-way analyses of variance with repeated measures were used to assess the effects of group (SSG vs. HIIT), time (pre- vs. post-intervention), and measurement points (−30 seconds, start, 15, 30, 45, 60, 75, 90, 105, and 120 seconds, only for TSI) on all dependent variables. However, we did not consider [HbO2], [HHb], and [tHb] in the statistical analysis because TSI is known to provide a better indication of muscle oxygenation status during exercise, where blood flow is not constant (muscle pump effect, (44)). Effect sizes were calculated using partial eta-squared () and Cohen d, and interpreted as small (>0.1), medium (>0.3), and large (>0.5), (7). Finally, Pearson correlations were used on the combined data from both groups (SSG and HIIT) to assess the association between the variations (delta, Δ) in aerobic (ΔVIFT) and anaerobic (Δ% Dec during RS and RSadj) performance measures and the variation in post-S1 reoxygenation (Δ post-S1 reoxygenation and Δ post-S1 reoxygenation [n]). Partial correlations were used for this latter to adjust for the distance covered during S1 because % Dec is known to be largely determined by S1 performance (38). For all these analyses, a p value inferior to 0.05 was considered statistically significant.


The mean HR and ratings of perceived exertion (RPE) recorded during training sessions were 90.5 ± 2.2% of HRpeak and 7.8 ± 09 (AU), and 90.6 ± 2.2% of HRpeak and 7.6 ± 0.7 (AU), respectively, for the HIIT and SSG groups. No significant interaction between time and group were shown on any of these variables (p ranging from 0.163 to 0.996, ranging from 0.001 to 0.163). A significant effect of time was shown on VIFT (P = 0.028, : 0.395) with both groups improving their performance in the post- compared with pre-training period (+3.4%, d: 0.70 and +4.1%, d: 0.44, respectively, for HIIT and SSG, P = 0.028, Table 2). The distances covered during S1 and S2 of the RS sequence both improved after compared with before training (+2.7%, d: 0.28 and +3.6%, d: 0.62 for S1, and +5.9%, d: 0.69 and +7.2%, d: 0.98 for S2, respectively, for HIIT and SSG, P = 0.014, : 0.357). The distances covered during S1adj were 73.0 ± 4.2 m and 72.2 ± 3.4 m, respectively, in the HIIT and SSG groups, which tended to be greater than S1 (P = 0.267). The distances covered during S2adj were 75.3 ± 5.9 m and 74.5 ± 3.8 m, respectively, in the HIIT and SSG groups. A significant increase in TD (+4.3%, d: 0.53 and +5.3%, d: 1.14, respectively, for HIIT and SSG, P = 0.014, : 0.357) and a significant decrease in % Dec (−62.5%, d: 1.24 and −21.6%, d: 0.67, respectively, for HIIT and SSG, P = 0.010, : 0.364) were reported between pre- and post-training in both groups.

Table 2.:
Changes in aerobic performance and reoxygenation rate after the 2 training interventions.*

A significant decrease in TSI (%) was observed between pre- and post-training in both groups (P = 0.028, : 0.473, Figure 2), as well as significant differences between measurement points (P = 0.001, : 0.848, Figure 2). When TSI was expressed relative to ΔS1 (% of ΔS1), significant differences between measurement points were shown (P = 0.001, : 0.814, Figure 3); however, no significant change with time (i.e., pre- vs. post-intervention) was observed (P = 0.450, : 0.118, Figure 3).

Figure 2.:
Effects of 6 weeks of small-sided game (SSG, upper panel) and high-intensity interval training (HIIT, lower panel) on the variation in tissue saturation index (TSI, %) before, during, and after the two 15-second sprints (S1 and S2) separated by 15 seconds of passive recovery. *Significant differences between preintervention and postintervention, P < 0.05. All significant differences between time points are indicated as the time point(s) being significantly different from each measurement point, P < 0.05.
Figure 3.:
Effects of 6 weeks of small-sided game (SSG, upper panel) and high-intensity interval training (HIIT, lower panel) on the variation in tissue saturation index (TSI) normalized as a percentage of the maximum change in TSI observed during the first sprint (% of ΔS1) before, during, and after the two 15-second sprints (S1 and S2) separated by 15 seconds of passive recovery. All significant differences between time points are indicated as the time point(s) being significantly different from each measurement point, P < 0.05.

A significant effect of time (P = 0.028) was found on ΔTSI during S2, with both groups characterized by greater ΔTSI in post- compared with pre-training (+114%, d: 1.33 and +47.8%, d: 0.46, respectively, in the HIIT and SSG groups, P = 0.028, : 0.355, Table 2). Significant improvements in all postsprint reoxygenation rates were shown in the postintervention compared with preintervention, including post-S1 reoxygenation (+31.8%, d: 0.27 and +46.8%, d: 0.61, respectively, for HIIT and SSG, P = 0.013, : 0386), post-S2 reoxygenation (+58.3%, d: 0.35 and +23.0%, d: 0.44, respectively, for HIIT and SSG, P = 0.036, : 0.296), post-S1 reoxygenation (n) (+69.0%, d: 0.44 and +60.3%, d: 0.72, respectively, for HIIT and SSG, P = 0.008, : 0.458) and post-S2 reoxygenation (n) (+107.7%, d: 0.44 and +34.2%, d: 0.44, respectively, for HIIT and SSG, P = 0.021, : 0.369).

Significant correlations were observed between Δ post-S1 reoxygenation during RSadj and ΔVIFT (r = 0.61, P = 0.008), as well as between Δ post-S1 reoxygenation (n) during RSadj and ΔVIFT (r = 0.64, P = 0.005). In addition, Δ post-S1 reoxygenation and Δ post-S1 reoxygenation (n) were significantly associated with Δ% Dec during RS (r = −0.487, P = 0.028 and r = −0.493, P = 0.024, respectively) and to %Dec during RSadj (r = −0.524, P = 0.020, and r = −0.577, P = 0.014, respectively).


The aim of the current study was to compare the effects of 6 weeks of SSG and HIIT on aerobic fitness and muscle oxygenation changes during an RS sequence in elite male junior basketball players. Our hypothesis was that SSG and HIIT will result in similar improvements in aerobic and RSA performance as well as muscle oxygenation. The main findings confirmed our hypothesis. Indeed, the in-season intervention based on SSG was as effective as HIIT to improve aerobic performance (VIFT) as well as RSA. Both training interventions also resulted in similarly greater ΔTSI during S2 and significant improvements in postsprint reoxygenation. Finally, the extent of change in post-S1 reoxygenation was significantly associated with improvements in aerobic (ΔVIFT) and anaerobic (Δ%Dec during RS) performances.

The 6-week interventions of this study induced significant increases in VIFT in both groups, suggesting the effectiveness of both SSG and HIIT to improve maximal aerobic performance during the season in junior basketball players. Although several studies have shown that SSGs were equally successful as HIIT at improving aerobic capacity (4,12,21,24,42), the novelty of the present findings showed the benefits of these types of interventions on a more specific population (basketball players) when performed in-season. Indeed, most of the interventions previously referred to were conducted in pre-season, and hence, were more likely to find significant improvements in aerobic performance because subjects' fitness was lower at the start of the intervention (21,24). By contrast, our results highlighted that maximal aerobic performance can also be improved during the season. Our intervention was shorter than the one in the study of Seitz et al. (42), (6 vs. 8 weeks); however, we observed a greater improvement in VIFT (+4.1 vs. +1.29% after SSG training interventions), suggesting that even a short-duration intervention could improve aerobic fitness. However, our subjects were less fit than theirs (VIFT of 17.4 km·h−1 and 17.2 km·h−1 in our study vs. 19.35 km·h−1 in the study of Seitz et al. (42)), which is usually associated with a greater margin for improvement. Other aspects of endurance performance can be similarly be improved by SSG vs. HIIT training, as shown by Faude et al. (17). Indeed, these authors showed that the individual anaerobic threshold of soccer players was improved to the same extent after both training interventions, with greater benefits observed in players with lower anaerobic thresholds at baseline (+4.3% compared with +0.0% in players with greater anaerobic thresholds at baseline). These individual adaptations are interesting to pinpoint; however, the relatively low sample size in this study did not allow us to perform such an analysis.

The effectiveness of training interventions to improve aerobic fitness is linked to the time spent with high HR during training sessions, with recommended zones ranging from 90 to 95% of HRpeak in the literature to induce significant adaptations (16). Within this context, we recorded average HR of 90.5 ± 2.2% of HRpeak and 90.6 ± 2.2% of HRpeak, respectively, for the HIIT and SSG, which could partly explain our positive results. Interestingly, no difference in RPE was observed between the 2 training interventions, which is similar to a previous study (13), but in contrast with others that observed a lower RPE in SSG compared with HIIT (21,32). This could be explained by the fact that our SSG format (2v2) was more intense than formats including more players (3v3 or 4v4) and did not allow as much recovery for players during one bout.

Several characteristics of SSG training bouts can be manipulated to elicit greater exercise intensities, such as court size, number of players, and training regimen (20). We chose 2v2 played on the full length and half width of the court to reach a greater intensity (11). Indeed, it has been shown that SSG based on 2v2 led to higher HRmean, compared with 3v3 (90.0 vs. 85.8% of HRpeak (11)), or 4v4 (89.9 vs. 87.3% of HRpeak in 2v2 vs. 4v4 (8)). In addition, less differences in the physiological load experienced by the various basketball playing positions were shown in 2v2 than 3v3 (11). We used continuous drills for about 4 minutes because they have been shown to induce greater HR levels compared with shorter intermittent bouts (29,35). By contrast, shorter (2-minute) bouts are characterized by greater blood lactate values (30). Finally, the short recovery between games used in the current study (2 minutes) was shown to induce greater HR responses compared with longer recovery duration (3 or 4 minutes) (31). Consequently, these authors suggested that longer SSG bouts interspersed by shorter recovery periods represented greater cardiovascular demands and were more likely to induce improvements in aerobic fitness (29–31).

Our results showed that both training programs significantly improved RSA, with greater distances covered in S1, S2, and TD, as well as a smaller %Dec in the postintervention compared with the preintervention period. These results are in accordance with those obtained by Buchheit and Ufland (6) after 8 weeks of HIIT in team sport players where the same RS sequence was used. The better sprint performance in S1 could be explained by an improvement in anaerobic power after training. Indeed, it has been shown that training interventions based on SSG or HIIT improved performance aspects known to rely on power, such as agility, vertical jump height, and 10-m sprint time (12,22,42). Improvements in mechanical efficiency and running economy have also been reported after HIIT and SSG intervention (24,39). Conversely, an improved capacity to recover between sprints has been suggested as the main explanation of the improved S2 distance in the same RS sequence as the one performed in our study (6). It was investigated with the NIRS parameters in this study.

We did not find any significant differences in TSI expressed as a % of ΔS1 after both training interventions, which is in contrast with the results of Buchheit and Ufland (6). However, it must be noted that these authors did not report p values, but qualitative and quantitative inferences. It is also important to note that the lower or similar postsprint TSI values observed in this study after training could reflect a greater relative workload during sprints in the postintervention, or a greater capacity of subjects to push themselves. Finally, considering TSI over the entire RS sequence and recovery might not be the most relevant approach, and instead, several authors chose to isolate specific measurement periods, such as sprint time, or immediate postsprint periods (6,25).

Our analysis of the changes in muscle saturation index during sprints revealed a greater drop in ΔTSI post-training during S2 only. This is similar to the results reported by Jones and Cooper (25) during 10 repetitions of 10-s sprints separated by 40 seconds of recovery in elite male rugby players after 8 weeks of pre-season training (ΔTSI of −12.4 and −14.8% in pre- and post-training, respectively). The same authors also observed similar results during 5 repetitions of 30-second sprints interspersed by 4-minute recovery periods in elite female field hockey players after 6 weeks of sprint interval training (ΔTSI of −7.6 and −12.2% in pre- and post-training, respectively (26)). The main explanation for the greater ΔTSI after a training intervention is an increase in oxygen consumption by the muscle tissue due to a greater mitochondrial content, resulting in better extraction of oxygen from the capillaries (2,25). Jones and Cooper (25) confirmed this hypothesis by showing a significant increase in HHb.

Our results on muscle reoxygenation showed that both training interventions resulted in improvements in post-S1 and post-S2 reoxygenation. These results are in accordance with those of Buchheit and Ufland (6) after an 8-week HIIT training, showing improvements in post-S1 and post-S2 reoxygenation ranging from 50 to 229% (23–107% in our study). They are also in agreement with the findings of Jones et al. (26) after 6 weeks of sprint interval training in female field hockey players, showing that TSI in the recovery periods from RSs (5 × 30 seconds with 4-minute recovery) was largely improved post-training, although it was not formally quantified in their study. However, the same authors showed no significant variation in reoxygenation after 8 weeks of pre-season training in elite male rugby players, suggesting that the improvement in reoxygenation may be intervention- or population-specific. The greater improvements in the study of Buchheit and Ufland (6) compared with ours could be due to the longer intervention period (8 compared with 6 weeks in this study), or the fact that their subjects were less fit than ours. Faster muscle reoxygenation rates in the recovery from exercise could indicate better muscle aerobic function (9). The main factors suggested in the literature to account for such changes are an improvement in muscle oxidative capacity (40), and an increase in the blood flow to the muscles as well and increased capillarization (28); however, we did not measure these parameters in this study.

An interesting finding of this study is the significant moderate to large associations between the improvement in RS performance (as evidenced by a smaller %Dec) and the better post-S1 reoxygenation during RS (r = −0.487) and RSadj (r = −0.577). This could be explained by the similarity between the kinetics of reoxygenation and those of PCr recovery after a dynamic exercise observed by McCully et al. (37). However, it must be noted that this study focused on submaximal exercise, and thus, further studies should replicate this finding during supramaximal exercise. Nevertheless, we could hypothesize that both training interventions in this study might have accelerated the restoration of PCr stores, resulting in better RSA (3). In favor of this hypothesis, we also found significant large associations between post-S1 reoxygenation and post S1-reoxygenation (n) and aerobic performance, evaluated by VIFT (r = 0.61 and 0.64, respectively), suggesting a greater involvement of the aerobic energy system in the recovery between sprints (potentially leading to a larger replenishment of PCr). These associations between postsprint reoxygenation and maximal aerobic performance was also previously observed (6).

The main limitations of the current study included a small sample size, a relatively short training period, and the lack of control on training and match loads. However, our sample size is comparable with the one used in a study focusing on similar training interventions and measurement methods (6). It would have been interesting to have a longer training period and test performance and muscle oxygenation parameters at the start, halfway, and end of the intervention to characterize more precisely the kinetics of adaptation of our players. Finally, we did not have access to all training and match loads of the players in this study, which limits the interpretation of our findings, in particular as the study took place over 2 seasons.

Practical Applications

The main findings of this study showed that SSG based on 2v2 played on a full court and half width were as effective as HIIT at improving aerobic performance (VIFT) as well as RSA, even when performed in-season. This suggests that coaches can use SSG to improve players' tactics and technique, as previously suggested, but also physical fitness. In particular, it seems that muscle reoxygenation after sprints could be improved by both SSG and HIIT, which is particularly important to improve RSA; this type of training should therefore be included in the relevant microcycles aiming at RSA training. The fact that the extent of change in post-S1 reoxygenation was significantly associated with improvements in aerobic (ΔVIFT) and anaerobic (Δ%Dec during RS) performances showed that these parameters could be interchangeably used in players' selection process or for talent identification. Finally, this is the first study to investigate basketball SSG played on full court and half width. This space is particularly interesting as it allows for 2 simultaneous high-intensity games to be played, and coaches could manipulate players' number within this space (3v3 or 4v4) to work on physical and tactical aspects.


1. Ben Abdelkrim N, Castagna C, Jabri I, Battikh T, El Fazaa S, El Ati J. Activity profile and physiological requirements of junior elite basketball players in relation to aerobic-anaerobic fitness. J Strength Cond Res 24: 2330–2342, 2010.
2. Bailey SJ, Wilkerson DP, Dimenna FJ, Jones AM. Influence of repeated sprint training on pulmonary O2 uptake and muscle deoxygenation kinetics in humans. J Appl Physiol 106: 1875–1887, 2009.
3. Bogdanis GC, Nevill ME, Boobis LH, Lakomy HK. Contribution of phosphocreatine and aerobic metabolism to energy supply during repeated sprint exercise. J Appl Physiol 80: 876–884, 1996.
4. Buchheit M, Laursen PB, Kuhnle J, Ruch D, Renaud C, Ahmaidi S. Game-based training in young elite handball players. Int J Sports Med 30: 251–258, 2009.
5. Buchheit M, Lefebvre B, Laursen PB, Ahmaidi S. Reliability, usefulness, and validity of the 30-15 Intermittent Ice Test in young elite ice hockey players. J Strength Cond Res 25: 1457–1464, 2011.
6. Buchheit M, Ufland P. Effect of endurance training on performance and muscle reoxygenation rate during repeated-sprint running. Eur J Appl Physiol 111: 293–301, 2011.
7. Cohen J. Statistical Power Analysis for the Behavioral Sciences New York: Academic Press, 1977.
8. Conte D, Favero TG, Niederhausen M, Capranica L, Tessitore A. Effect of different number of players and training regimes on physiological and technical demands of ball-drills in basketball. J Sports Sci 34: 780–786, 2016.
9. Costes F, Prieur F, Feasson L, Geyssant A, Barthelemy JC, Denis C. Influence of training on NIRS muscle oxygen saturation during submaximal exercise. Med Sci Sports Exerc 33: 1484–1489, 2001.
10. Delextrat A, Baliqi F, Clarke N. Repeated sprint ability and stride kinematics are altered following an official match in national-level basketball players. J Sports Med Phys Fitness 53: 112–118, 2013.
11. Delextrat A, Kraiem S. Heart-rate responses by playing position during ball drills in basketball. Int J Sports Physiol Perform 8: 410–418, 2013.
12. Delextrat A, Martinez A. Small-sided game training improves aerobic capacity and technical skills in basketball players. Int J Sports Med 35: 385–391, 2014.
13. Dellal A, Varliette C, Owen A, Chirico EN, Pialoux V. Small-sided games versus interval training in amateur soccer Players: Effects on the aerobic capacity and the ability to perform intermittent exercises with changes of direction. J Strength Cond Res 26: 2712–2720, 2012.
14. Dupont G, Moalla W, Matran R, Berthoin S. Effect of short recovery intensities on the performance during two Wingate tests. Med Sci Sports Exerc 39: 1170–1176, 2007.
15. Edge J, Bishop D, Goodman C, Dawson B. Effects of high- and moderate-intensity training on metabolism and repeated sprints. Med Sci Sports Exerc 37: 1975–1982, 2005.
16. Esposito F, Impellizzeri FM, Margonato V, Vanni R, Pizzini G, Veicsteinas A. Validity of heart rate as an indicator of aerobic demand during soccer activities in amateur soccer players. Eur J Appl Physiol 93: 167–172, 2004.
17. Faude O, Steffen A, Kellmann M, Meyer T. The effect of short-term interval training during the competitive season on physical fitness and signs of fatigue: A crossover trial in high-level youth football players. Int J Sports Physiol Perform 9: 936–944, 2014.
18. Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, Doleshal P, Dodge C. A new approach to monitoring exercise training. J Strength Cond Res 15: 109–115, 2001.
19. Glaister M, Stone MH, Stewart AM, Hughes M, Moir GL. The reliability and validity of fatigue measures during short-duration maximal-intensity intermittent cycling. J Strength Cond Res 18: 459–462, 2004.
20. Halouani J, Chtourou H, Gabbett T, Chaouachi A, Chamari K. Small-sided games in team sports training: A brief review. J Strength Cond Res 28: 3594–3618, 2014.
21. Hill-Haas SV, Coutts AJ, Rowsell GJ, Dawson BT. Generic versus small-sided game training in soccer. Int J Sports Med 30: 636–642, 2009.
22. Iacono A, Ardigo LP, Meckel Y, Padulo J. Effect of small-sided games and repeated shuffle sprint training on physical performance in elite handball players. J Strength Cond Res 30: 830–840, 2016.
23. Iacono A, Eliakim A, Meckel Y. Improving fitness of elite handball players: Small-sided games vs. High-Intensity intermittent training. J Strength Cond Res 29: 835–843, 2015.
24. Impellizzeri FM, Marcora SM, Castagna C, Reilly T, Sassi A, Iaia FM, Rampinini E. Physiological and performance effects of generic versus specific aerobic training in soccer players. Int J Sports Med 27: 483–492, 2006.
25. Jones B, Cooper CE. Use of NIRS to assess effect of training on peripheral muscle oxygenation changes in elite rugby players performing repeated supramaximal cycling tests. Adv Exp Med Biol 812: 333–339, 2014.
26. Jones B, Hamilton DK, Cooper CE. Muscle oxygen changes following Sprint Interval Cycling training in elite field hockey players. PLoS One 10: e0120338, 2015.
27. Kime R, Hamaoka T, Sako T, Murakami M, Homma T, Katsumura T, Chance B. Delayed reoxygenation after maximal isometric handgrip exercise in high oxidative capacity muscle. Eur J Appl Physiol 89: 34–41, 2003.
28. Kime R, Karlsen T, Nioka S, Lech G, Madsen O, Saeterdal R, et al. Discrepancy between cardiorespiratory system and skeletal muscle in elite cyclists after hypoxic training. Dyn Med 2: 4, 2003.
29. Klusemann MJ, Pyne DB, Foster C, Drinkwater EJ. Optimising technical skills and physical loading in small-sided basketball games. J Sports Sci 30: 1463–1471, 2012.
30. Köklü Y, Alemdaroğlu U, Cihan H, Wong DP. Effects of bout duration on players' internal and external loads during small-sided games in young soccer players. Int J Sports Physiol Perform 12: 1370–1377, 2017.
31. Koklu Y, Alemdaroglu U, Dellal A, Wong DP. Effect of different recovery durations between bouts in 3-a-side games on youth soccer players' physiological responses and technical activities. J Sports Med Phys Fitness 55: 430–438, 2015.
32. Los Arcos A, Vázquez JS, Martín J, Lerga J, Sánchez F, Villagra F, Zulueta JJ. Effects of small-sided games vs. Interval training in aerobic fitness and physical enjoyment in young elite soccer players. PLoS One 10: e0137224, 2015.
33. Malacko J, Doder D, Djurdjevic S, Savic B, Doder R. Differences in the bioenergetic potential of athletes participating in team sports. Vojnosanit Pregl 70: 633–636, 2013.
34. Malone S, Hughes B, Collins KD. Are small-sided games an effective training methodology for improving fitness in hurling players? A comparative study of training methodologies. Int J Sports Sci Coach 12: 685–694, 2017.
35. Marcelino PR, Aoki MS, Arruda A, Freitas CG, Mendez-Villanueva A, Moreira A. Does small-sided-games' court area influence metabolic, perceptual, and physical performance parameters of young elite basketball players? Biol Sport 33: 37–42, 2016.
36. Matsushita K, Homma S, Okada E. Influence of adipose tissue on muscle oxygenation measurement with an NIRS instrument. Proc. SPIE 3194: 3194–3197, 1998.
37. McCully KK, Iotti S, Kendrick K, Wang Z, Posner JD, Leigh JJ, Chance B. Simultaneous in vivo measurements of HbO2 saturation and PCr kinetics after exercise in normal humans. J Appl Physiol (1985) 77: 5–10, 1994.
38. Mendez-Villanueva A, Hamer P, Bishop D. Physical fitness and performance. Fatigue responses during repeated sprints matched for initial mechanical output. Med Sci Sports Exerc 39: 2219–2225, 2007.
39. Owen AL, Wong DP, Paul D, Dellal A. Effects of a periodized small-sided game training intervention on physical performance in elite professional soccer. J Strength Cond Res 26: 2748–2754, 2012.
40. Puente-Maestu L, Tena T, Trascasa C, Perez-Parra J, Godoy R, Garcia MJ, Stringer WW. Training improves muscle oxidative capacity and oxygenation recovery kinetics in patients with chronic obstructive pulmonary disease. Eur J Appl Physiol 88: 580–587, 2003.
41. Scanlan A, Dascombe B, Reaburn P. A comparison of the activity demands of elite and sub-elite Australian men's basketball competition. J Sports Sci 29: 1153–1160, 2011.
42. Seitz LB, Riviere M, de Villarreal ES, Haff GG. The athletic performance of elite rugby league players is improved after an 8-week small-sided game training intervention. J Strength Cond Res 28: 971–975, 2014.
43. Tomlin DL, Wenger HA. The relationship between aerobic fitness and recovery from high intensity intermittent exercise. Sports Med 31: 1–11, 2001.
44. Wolf M, Ferrari M, Quaresima V. Progress of near-infrared spectroscopy and topography for brain and muscle clinical applications. J Biomed Opt 12: 62104, 2007.

NIRS; recovery; 2v2; aerobic performance; anaerobic performance

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