The purpose of this study was to examine physiological and physical determinants of ice-hockey performance in order to assess their impact on the result during a selection for ice hockey. A total of 42 ice hockey players took part in the selection camp. At the end of the camp 20 best players were selected by team of expert coaches to the ice hockey team and created group G1, while the second group (G2) consisted of not selected players (non-successful group Evaluation of goodness of fit of the model to the data was based on the Hosmer Lemeshow test. Ice hockey players selected to the team were taller 181.95±4.02 cm, had lower% body fat 13.17±3.17%, a shorter time to peak power 2.47±0.35 s, higher relative peak power 21.34±2.41 W·kg−1 and higher relative total work 305.18±28.41 J·kg−1. The results of the aerobic capacity test showed significant differences only in case of two variables. Ice hockey players in the G1 had higher VO2max 4.07±0.31 l·min−1 values than players in the G2 as well as ice hockey players in G1 showed a higher level of relative VO2max 51.75±2.99 ml·min−1·kg−1 than athletes in G2. Ice hockey players selected to the team (G1) performed better in the 30 m Forwards Sprint 4.28±0.31 s; 6x9 Turns 12.19±0.75 s; 6x9 stops 12.79±0.49 s and Endurance test (6x30 m stops) 32.01±0.80 s than players in G2. The logistic regression model showed that the best predictors of success in the recruitment process of top level ice hockey players were time to peak power, relative peak power, VO2max and 30 m sprint forwards on ice. On the basis of the constructed predictive logistic regression model it will be possible to determine the probability of success of the athletes during following the selection processes to the team.

The aim of the study was to determine the effect of the wide-grip bench press (WGBP) and the close-grip bench press (CGBP) on the number of performed repetitions (REPs) and time under tension (TUT) using a variable tempo of movement. Twenty (20) women experienced in resistance training were enrolled in the study (1RM-CGBP = 55.2 ± 9.5 kg; 1RM-WGBP = 52.7 ± 8.5 kg). Participants performed 5 sets of the BP with a maximal number of REPs at 70%1RM. Different tempos of movement, i.e., slow (6/0/X/0) and fast (2/0/X/0), and grip widths, i.e., the CGBP and the WGBP, were employed. The following variables were registered: maximal number of repetitions in every set (REPSet1-5), total number of repetitions performed in 5 sets (TREP), maximal time under tension in every set (TUTSet1-5) and total time under tension in 5 sets (TTUT). The two-way ANOVA revealed statistically significant differences between the WGBPFAST and the WGBPSLOW in TUTSet1-5 (p < 0.05) and TTUT (p < 0.01), as well as between the CGBPFAST and the CGBPSLOW in TUTSet1-5 (p < 0.01) and TTUT (p < 0.01). Significant differences between the WGBPFAST and the WGBPSLOW were also observed in REPSet1-5 (p < 0.01) and TREP (p < 0.01) as well as between the CGBPFAST and the CGBPSLOW in REPSet1-5 (p < 0.01) and TREP (p < 0.01). No significant differences between the WGBPSLOW and the CGBPSLOW nor the WGBPFAST and the CGBPFAST were found. The study demonstrates that the tempo of movement, regardless of the width grip, has a significant effect on the volume of effort in resistance training.

While tests of basic motor abilities such as speed, maximum strength or endurance are well recognized, testing of complex motor functions such as agility remains unresolved in current literature. Therefore, the aim of this review was to evaluate which main factor or factor structures quantitatively determine agility. In methodological detail, this review focused on research that explained or described the relationships between latent variables in a factorial model of agility using approaches such as principal component analysis, factor analysis and structural equation modeling. Four research studies met the defined inclusion criteria. No quantitative empirical research was found that tried to verify the quality of the whole suggested model of the main factors determining agility through the use of a structural equation modeling (SEM) approach or a confirmatory factor analysis. From the whole structure of agility, only change of direction speed (CODS) and some of its subtests were appropriately analyzed. The combination of common CODS tests is reliable and useful to estimate performance in sub-elite athletes; however, for elite athletes, CODS tests must be specific to the needs of a particular sport discipline. Sprinting and jumping tests are stronger factors for CODS than explosive strength and maximum strength tests. The authors suggest the need to verify the agility factorial model by a second generation data analysis technique such as SEM.

Background:The main goal of the presented study was to assess the effect of blood flow restriction (BFR) on the maximum number of repetitions in the bench press exercise (BP) with different movement tempos.Material and methods: Four female athletes volunteered for the study. The experiment was performed following a randomized crossover design, with four different testing protocols: 2/0/X/0 fast tempo with BFR (FAST BFR ); 2/0/X/0 fast tempo without BFR (FAST NO-BFR ); 6/0/X/0 slow tempo with BFR (SLOW BFR ) or 6/0/X/0 slow tempo without BFR (SLOW NO-BFR ). During the experimental session, participants performed 5 sets of the BP at 80%1RM. The following variables were recorded: the maximal number of repetitions in every set (REP Set1-5 ) and the total number of repetitions performed in 5 sets (TREP). Two-way ANOVA was used to show differences between variables.Results: There were significant differences between FAST NO-BFR and SLOW NO-BFR , between FAST BFR and SLOW BFR variables in REP Set1-5 (p < 0.05) and TREP (p < 0.01). Similarly, there were significant differences between FAST NO-BFR and FAST BFR variables in REP Set1,2,5 (p < 0.05) and TREP. Significant differences between SLOW NO-BFR and SLOW BFR variables were also found in REP Set1,5 (p < 0.05), as well as in TREP (p < 0.01). Conclusions:The use of BFR in resistance training improves the maximal number of REP during the BP.

The purpose of this study was to determine ice-hockey players' playing intensity based on their heart rates (HRs) recorded during a game and on the outcomes of an incremental maximum oxygen uptake test. Sixteen ice-hockey players, members of the Polish national team junior (U20), performed an incremental test to assess their maximal oxygen uptake (VO2max) in the 2 week's period preceding 4 games they played at the World Championships. Players' HRs at the first and second ventilatory thresholds obtained during the test were used to determine intensity zones (low, moderate, and high) that were subsequently used to classify HR values recorded during each of the games. For individual intensity zones, the following HRs expressed as mean values and as percentages of the maximal heart rate (HRmax) were obtained: forwards, 143-151 b · min(-1) (HRmax, 75.2-79.5%), 152-176 b · min(-1) (HRmax, 80.0-92.4%), 177-190 b · min(-1) (HRmax, 92.9-100.0%); defensemen, 127-139 b · min(-1) (HRmax, 69.4-75.8%), 140-163 b · min(-1) (HRmax, 76.4-89.0%), 164-184 b · min(-1) (HRmax, 89.5-100.0%). The amounts of time the forwards and defensemen spent in the 3 intensity zones expressed as percentages of the total time of the game were the following: 58.75% vs. 44.29% (low), 21.95% vs. 25.84% (moderate), and 19.30% vs. 29.87% (high). The forwards spent average more time in the low-intensity zone than did the defensemen, with the difference being statistically significant in periods 1 and 2 (61.44% vs. 44.21% at p ≤ 0.001 and 59.14% vs. 47.23% at p ≤ 0.01, respectively). The results of the study indicate that a method using aerobic and anaerobic metabolism parameters to determine intensity zones can significantly improve the reliability of evaluation of the physiological demands of the game and can be a useful tool for coaches in managing the training process.

No abstract

The enforced sedentary lifestyle and muscle paresis below the level of injury are associated with adipose tissue accumulation in the trunk. The value of anthropometric indicators of obesity in patients with spinal cord injuries has also been called into question. We hypothesized that the Body Mass Index recommended by the WHO to diagnose obesity in general population has too low sensitivity in case of wheelchair rugby players.The study group comprised 14 wheelchair rugby players, aged 32.6 ± 5.1 years, who had sustained CSCI (paralysis of lower limbs and upper extremities). The research tool was the Tanita Viscan visceral and trunk fat analyzer AB140 using the abdominal bioelectrical impedance analysis (BIA) to estimate the visceral fat level (Vfat) and trunk fat percentage (Tfat). The AB140 analyzer also allowed the measurement of body composition of those individuals who could not assume an upright position. Our analyses revealed high and very high correlation coefficients between Vfat and WC (r=0.9), WHtR (r=0.7) and Tfat (r=0.9) whereas the correlation between Vfat and the BMI was weak, especially in the subgroup with Vfat < 13.5% (r=0.2). The subgroup with Vfat>13.5 exhibited a moderate-level relationship between the BMI and visceral fat increase. It was concluded that the BMI had a low sensitivity for predicting obesity risk in wheelchair rugby players after CSCI. The sensitivity of WC measurement was higher and thus, it may be stated that it constitutes an objective tool for predicting obesity risk in post-CSCI wheelchair rugby players.

The purpose of the study was to evaluate the impact of (1) maximal muscular strength of the upper body and (2) fat mass on musculoskeletal pain and sagittal spinal curvature deviations in elite Polish sitting volleyball players. The study examined twelve players (age = 35.4 ± 6.9 years). The assessments were performed based on objective (anthropometric examinations, Medi Mouse, 1RM test) and subjective (NMQ = 7) measurements. All statistical analyses were performed using the SPSS. The lower back, the upper back and the neck were the most frequent painful areas. Statistical analyses showed a significant relationship between lumbar lordosis (LL) sagittal standing extension (r = 0.62; p = 0.03) and thoracic kyphosis (TK) sagittal standing flexion (r = -0.63; p = 0.28) with the 1RM. Furthermore, correlations between a body adiposity index and TK sagittal standing flexion and extension (r = -0.65; p = 0.05, r = - 0.58; p = 0.0.05) as well as LL sagittal standing flexion (r = 0.61; p = 0.05) were found. The body mass index correlated with wrist pain, whereas a very high relationship was found between pain in the wrists and knee joints. Neck pain positively correlated with TK and LL sagittal standing. Low back pain correlated with LL sagittal standing flexion and TK sagittal standing extension. Fat mass impacts the depth of anteroposterior spinal curvatures, what may cause pain in the neck and the lower back. The 1 RM bench press may influence the prevalence and location of musculoskeletal pain, whereas its values might be predicted by the depth of TK. A lower 1RM in the bench press may impact sagittal spinal curvature deviations. Deepen TK and LL significantly contribute to the prevalence of the neck pain.