Kris Berg

Physiological demands of competitive basketball

The aim of this study was to assess physiological demands of competitive basketball by measuring oxygen consumption (VO2) and other variables during practice games. Each of 12 players (20.4 ± 1.1 years) was monitored in a 20‐min practice game, which was conducted in the same way as actual games with the presence of referees and coaches. VO2 was measured by a portable system during the game and blood lactate concentration (LA) was measured in brief breaks. Subjects were also videotaped for time‐motion analysis. Female and male players demonstrated respective VO2 of 33.4 ± 4.0 and 36.9 ± 2.6 mL/kg/min and LA of 3.2 ± 0.9 and 4.2 ± 1.3 mmol/L in the practice games (P>0.05). They spent 34.1% of play time running and jumping, 56.8% walking, and 9.0% standing. Pre‐obtained VO2max was correlated to VO2 during play (r=0.673) and to percent of duration for running and jumping (r=0.935 and 0.962 for females and males, respectively). This study demonstrated a greater oxygen uptake for competitive basketball than that estimated based on a previous compendium. The correlation between aerobic capacity and activity level suggests the potential benefit of aerobic conditioning in basketball.

Physiological Determinants of 40-Meter Sprint Performance in Young Male Athletes

This study examined 20 male athletes on a number of physiological variables to determine which may account for the most variation in 40-m sprint performance. The athletes were tested on 40-m sprint, 10-m sprint, a 5-step jump, vertical jump, Wingate anaerobic cycle power, and isokinetic peak torque of the knee and hip at speeds of 1.05, 3.14, and 7.85 rad · sec−1 and ankle at speeds of 1.05, 3.14, and 5.24 rad · sec−1. With R = 0.897 (p ≤ 0.05) and SEE = 0.151 (sec), the 10-m sprint and ankle dorsiflexion peak torque at 5.24 rad · sec−1 were identified as predictors of 40-m sprint performance. With the 10-m sprint removed as an independent variable, stepwise multiple regression was performed again. With R = 0.909 and SEE = 0.146 sec, the 5-step jump, knee flexion peak torque at 7.85 rad · sec−1, and ankle plantar flexion peak torque at 1.05 rad · sec−1 were identified as predictors of 40-m sprint performance. The results indicate that both 10-m sprint and 5-step jump can be used to predict 40-m sprint performance.

The Effect of Resistive Exercise Rest Interval on Hormonal Response, Strength and Hypertrophy with Training

Buresh, R, Berg, K, and French, J. The effect of resistive exercise rest interval on hormonal response, strength, and hypertrophy with training. J Strength Cond Res 23(1): 62-71, 2009- The purpose of this study was to compare the effects of different between-set rest periods (1 and 2.5 minutes) on changes in hormone response, strength, arm cross-sectional area (CSA), thigh muscular cross-sectional area (MCSA), and body composition during a 10-week training period. Twelve untrained males (24.8 ± 5.9 years) engaged in resistance training using either 1 minute (short rest [SR], n = 6) or 2.5 minutes (long rest [LR], n = 6) of rest between sets, with a load that elicited failure on the third set of each exercise. Body composition, thigh MCSA, arm CSA, and five-repetition maximum (RM) squat and bench press were assessed before and after training. Blood samples were collected after exercise in weeks 1, 5, and 10. In week 1, postexercise plasma testosterone levels were greater in SR (0.41 ± 0.17 mmol·L−1) than in LR (0.24 ± 0.06 mmol·L−1, p < 0.05), and postexercise cortisol levels were greater in SR (963 ± 313 mmol·L−1) than in LR (629 ± 127 mmol·L−1, p < 0.05). Week 1 postexercise GH levels were not different (p = 0.28). The differences between hormone levels in weeks 5 and 10 were not significant. Arm CSA increased more with LR (12.3 ± 7.2%) than with SR (5.1 ± 2.9%, p < 0.05). There were no differences in strength increases. These results show that in healthy, recently untrained males, strength training with 1 minute of rest between sets elicits a greater hormonal response than 2.5-minute rest intervals in the first week of training, but these differences diminish by week 5 and disappear by week 10 of training. Furthermore, the hormonal response is highly variable and may not necessarily be predictive of strength and lean tissue gains in a 10-week training program.

Exercise training effects on serum lipids of prepubescent boys and adult men

The effects of 10 wk of exercise training at low (40% VO2max) or high (75% VO2max) intensity on serum lipids and lipoproteins were compared in prepubescent boys and adult men. The final sample size consisted of: 8 boys (mean +/- SE age = 8.5 +/- 1.96 yr) and 8 men (36.6 +/- 3.18 yr) in low; 12 boys (8.0 +/- 1.40 yr) and 12 men (36.6 +/- 4.09 yr) in high; and 10 boys (9.0 +/- 2.08 yr) and 10 men (36.7 +/- 4.82 yr) in control. Training involved walking/jogging/running 3 d X wk-1 at a distance which progressed from 2.4 km X d-1 in the first week to 4.8 km X d-1 from the fifth week. Fasting blood samples, collected on 2 d during both pre- and post-training, were assayed for triglycerides, total cholesterol (CHOL), and high density lipoprotein cholesterol (HDL-C). Maximum aerobic power (VO2max) was determined from a treadmill test. Additionally, dietary intake was assessed from a 3-d dietary record and body composition from the sum of 6 skinfolds. The only statistically significant (P less than 0.05) changes occurred in HDL-C and CHOL for the high groups. HDL-C decreased following training. CHOL was lower for high than the other groups for the first day post-training only. There were no differences in the changes in HDL-C/CHOL ratio among the groups. VO2max only increased in the high groups. Dietary intake and body weight did not change. Further statistical adjustment in lipids for changes in sum of 6 skinfolds did not alter the results.(ABSTRACT TRUNCATED AT 250 WORDS)

Physical and Performance Characteristics of NCAA Division I Male Basketball Players

Forty-five NCAA Division I male basketball teams totaling 437 players were surveyed about their height, weight, strength, speed, power, agility, body fatness, and aerobic capacity. Selected mean values ± SD were as follows: height, 195.3 ± 8.9 cm; weight, 91.3 ± 11.1 kg; % fat, 9.4 ± 15.2 %; vertical jump 71.4 ± 10.4 cm; 1-RM bench press, 102.7 ± 18.9 kg; 1-RM squat, 152.2 ± 36.5 kg; 40-yd dash, 4.81 ± 0.26 sec; agility 8.95 ± 0.53 sec; and 1 mile run, 5 min 40 sec ± 32 sec. Guards, forwards, and centers differed on all variables except bench press, 1.5-mile run, and agility. Guards were the smallest and leanest players and had the best vertical jump, speed, and strength relative to body weight, and the best mile run performance. Centers were the largest players, had the highest percent body fat and the poorest agility, 40-yd dash, and mile run times. Forwards and centers were similar in bench press and power clean, but forwards were stronger in both absolute and relative squat strength. Team mean scores were significantly different (p < 0.001) except for height, weight, 30-yd dash, and agility.

Endurance training and performance in runners: research limitations and unanswered questions.

AbstractThe purpose of this review is to discuss several limitations common to research concerning running and, secondly, to identify selected areas where additional research appears needed. Hopefully, this review will provide guidance for future research in terms of topics, as well as design and methodology. Limitations in the research include: lack of longitudinal studies, inadequate description of training status of individuals, lack of confirmation of state of rest, nourishment and hydration, infrequent use of allometric scaling to express oxygen uptake, relative neglect of anaerobic power and physical structure as determinants of performance, neglect of the central nervous system, and reliance on laboratory data. Further research in a number of areas is needed to enhance our knowledge of running performance. This includes: body mass as a performance determinant, evaluation of methods used to measure economy of running, assessing the link between strength and running performance, and further examination of training methods. While the amount of research on distance running is voluminous, the present state of knowledge is somewhat restricted by the limitations in research design and methodology identified here.

The effects of anabolic steroids on myocardial structure and cardiovascular fitness

To determine the effects of anabolic steroids on myocardial structure, VO2max, and body composition, experienced age-matched male weight trainers (M age 26.5 yr) who either used (U) (N = 11) or did not use (NU) (N = 13) anabolic steroids were evaluated. Steroid users were tested while off cycle (U-OFF) for at least 8 wk, again at the peak (U-ON) of their subsequent cycle, and to the nonuser group of weight trainers. Echocardiographic measurements revealed significant differences in left ventricular (LV) mass (182.8 +/- 26.9 g vs 210.6 +/- 42 g; P < 0.05) and interventricular septum thickness (IVS) (10.3 +/- 1.2 mm vs 11.1 +/- 1.2 mm; P < 0.05) between U-OFF and U-ON, respectively. NU measurements were also significantly different than U-ON for LV mass and IVS (186.5 +/- 36.2 g; P < 0.05 and 9.3 +/- 1.2 mm; P < 0.05, respectively). LV diameter in diastole was significantly greater in U-ON (59.1 mm) than in NU (55.7 mm; P < 0.05). In addition, LV posterior wall thickness in diastole was greater in U-ON compared with NU (11.2 mm vs 9.5 mm; P < 0.05). VO2max values for both user groups were significantly lower than those for NU (U-OFF = 41.0 +/- 4.5 ml.kg-1.min-1, U-ON = 41.0 +/- 5.7 ml.kg-1.min-1, and NU = 50.2 +/- 6.4 ml.kg-1.min-1; P < 0.05). Despite these morphological changes within the myocardium, there were no concomitant increases in shortening fraction.

Comparison of physical and performance characteristics of NCAA Division I football players: 1987 and 2000.

The purpose of this study was to compare normative data from present Division I National Collegiate Athletic Association football teams to those from 1987. Players were divided into 8 positions for comparisons: quarterbacks (QB), running backs (RB), receivers (WR), tight ends (TE), offensive linemen (OL), defensive linemen (DL), linebackers (LB), and defensive backs (DB). Comparisons included height, body mass, bench press and squat strength, vertical jump, vertical jump power, 40-yd-dash speed, and body composition. Independent t-tests were used to analyze the data with level of significance set at p < 0.01. Significant differences (p < 0.01) were found in 50 of 88 comparisons. From 1987 until 2000, Division I college football players in general have become bigger, stronger, faster, and more powerful. Further research is warranted to investigate if these trends will continue.

The accuracy of the ACSM cycle ergometry equation.

The purpose of this study was to determine the accuracy of the American College of Sports Medicines equation for estimating the oxygen cost of exercise performed on a cycle ergometer. Sixty healthy males, ages 19-39 yr old, performed a five stage (30, 60, 90, 120, and 150 W) submaximal cycle ergometer test while their oxygen uptake was measured. Results indicated the standard error of estimate for the predicted oxygen values ranged from 0.11 to 0.22 l.min-1, with correlations between the actual and predicted values ranging from r = 0.22 to r = 0.50. Total errors ranged from 0.23 to 0.31 l.min-1. The actual oxygen cost was underestimated from 0.16 to 0.29 l.min-1 (P less than 0.05) by the equation at each workload. A revised equation was developed based upon the actual VO2-power relationship. The resulting slope was lower and the intercept higher when compared with the current ACSM equation. The slope and intercept of the revised equation are more consistent with values published in the literature. This equation appears as: VO2 (ml.min-1) = kgm.min-1 x 1.9 ml.min-1) + ((3.5 ml.kg-1.min-1 x kg body weight) + 260 ml.min-1). Predicted values from the revised equation were more accurate as reflected by slightly higher correlations, lower total errors, and lower mean differences from actual VO2 measurements than those from the current equation.

Validation of a cycle ergometry equation for predicting steady-rate ??VO2

The purpose of this study was to validate an equation used for predicting the oxygen cost of leg cycle ergometry. This equation was previously shown to be more accurate than the one of the American College of Sports Medicine (ACSM) and appears as: VO2 (ml.min-1) = kgm.min-1 x 1.9 ml.min-1 + ((3.5 ml.kg-1.min-1 x kg body weight) + 260 ml.min-1). Fifty healthy males, ages 18-38 yr old, performed a six-stage (0, 180, 360, 540, 720, and 900 kgm.min-1) submaximal cycle ergometry test while their oxygen uptake was measured. Results indicated the standard error of estimate for the predicted oxygen consumption values ranged from 80-156 ml.min-1, with correlations between the actual and predicted values ranging from r = 0.35 to r = 0.67. Total errors ranged from 92-160 ml.min-1. All of the standard errors and total errors were lower and all of the correlations, except one, were higher at each power load in the validation sample than the original sample. These statistics support the generalizability and accuracy of the new equation. It would appear that the new equation may make accurate predictions in independent samples and is more precise than the ACSM equation.