Thomas A. Haugen, Felix Breitschädel and Stephen Seiler
Purpose: To quantify possible differences in sprint mechanical outputs in handball and basketball players according to playing standard and position. Methods: Sprint tests of 298 male players were analyzed. Theoretical maximal velocity (v 0), horizontal force (F 0), horizontal power (P max), force–velocity slope (S FV), ratio of force (RFmax), and index of force application technique (D RF) were calculated from anthropometric and spatiotemporal data using an inverse dynamic approach applied to the center-of-mass movement. Results: National-team handball players displayed clearly superior 10-m times (0.03, ±0.02 s), 40-m times (0.12, ±0.07 s), F 0 (0.1, ±0.2 N·kg−1), v 0 (0.3, ±0.2 m·s−1), and P max (0.9, ±0.5 W·kg−1) than corresponding top-division players. Wings differed from the other positions in terms of superior 10-m times (0.02, ±0.01 to 0.07, ±0.02 s), 40-m times (0.07, ±0.05 to 0.27, ±0.07 s), F 0 (0.2, ±0.1 to 0.4, ±0.2 N·kg−1), v 0 (0.1, ±0.1 to 0.5, ±0.1 m·s−1), P max (0.7, ±0.4 to 2.0, ±0.5 W·kg−1), and RFmax (0.6, ±0.4 to 1.3, ±0.4%). In basketball, guards differed from forwards in terms of superior 10-m times (0.03, ±0.02 s), 40-m times (0.10, ±0.08 s), v 0 (0.2, ±0.1 m·s−1), P max (0.6, ±0.6 W·kg−1), and RFmax (0.4, ±0.3%). The effect magnitudes of the substantial differences observed ranged from small to large. Conclusions: The present results provide an overall picture of the force–velocity profile continuum in sprinting handball and basketball players and serve as useful background information for practitioners when diagnosing individual players and prescribing training programs.
Thomas Haugen, Espen Tønnessen and Stephen Seiler
Human upper performance limits in the 100-m sprint remain the subject of much debate. The aim of this commentary is to highlight the vulnerabilities of prognoses from historical trends by shedding light on the mechanical and physiological limitations associated with human sprint performance. Several conditions work against the athlete with increasing sprint velocity; air resistance and braking impulse in each stride increase while ground-contact time typically decreases with increasing running velocity. Moreover, muscle-force production declines with increasing speed of contraction. Individual stature (leg length) strongly limits stride length such that conditioning of senior sprinters with optimized technique mainly must be targeted to enhance stride frequency. More muscle mass means more power and thereby greater ground-reaction forces in sprinting. However, as the athlete gets heavier, the energy cost of accelerating that mass also increases. This probably explains why body-mass index among world-class sprinters shows low variability and averages 23.7 ± 1.5 and 20.4 ± 1.4 for male and female sprinters, respectively. Performance development of world-class athletes indicates that ~8% improvement from the age of 18 represents the current maximum trainability of sprint performance. However, drug abuse is a huge confounding factor associated with such analyses, and available evidence suggests that we are already very close to “the citius end” of 100-m sprint performance.
Thomas Haugen, Espen Tønnessen and Stephen Seiler
A review of published studies monitoring sprint performance reveals considerable variation in start distance behind the initial timing gate. The aim of the current study was to generate correction factors across varying flying-start distances used in sprint testing with photocells.
Forty-four well-trained junior soccer players (age 18.2 ± 1.0 y, height 175 ± 8 cm, body mass 68.4 ± 8.9 kg) performed sprint testing on an indoor sprint track. They were allocated to 3 groups based on sprintperformance level. Times for 10- and 200-m sprint with foot placement ranging from 0.5 to 15 m back from the initial timing gate were recorded twice for each athlete.
Correction-factor equation coefficients were generated for each of the 3 analyzed groups derived from the phase-decay equation y = (y 0 − PL) × exp(−k × x) + PL, where y = time difference (0.5-m flying start as reference), x = flying-start distance, y 0 is the y value when time is zero, PL (plateau) is the y value at infinite times, and k is the rate constant, expressed in reciprocal of the x-axis time units; if x is in seconds, then k is expressed in inverse seconds. R 2 was ≥.998 across all athlete groups and sprint distances, demonstrating excellent goodness of fit. Within-group time differences were significant (P < .05) across all flying-start distance checkpoints for all groups. Between-groups time-saving differences up to 0.04 s were observed between the fastest and the slowest groups (P < .05).
Small changes in flying-start distances can cause time differences larger than the typical gains made from specific training, or even the difference between the fastest and slowest elite team-sport athletes. The presented correction factors should facilitate more meaningful comparisons of published sprint-performance results.
Thomas A. Haugen, Espen Tønnessen and Stephen Seiler
To compare sprint and countermovement-jump (CMJ) performance among competitive soccer players as a function of performance level, field position, and age. In addition, the authors wanted to quantify the evolution of these physical characteristics among professional players over a 15-y period.
939 athletes (22.1 ± 4.3 y), including national-team players, tested 40-m sprint with electronic timing and CMJ on a force platform at the Norwegian Olympic Training Center between 1995 and 2010.
National-team and 1st-division players were faster (P < .05) than 2nd-division (1.0–1.4%), 3rd- to 5th-division (3.0–3.8%), junior national-team (1.7–2.2%), and junior players (2.8–3.7%). Forwards were faster than defenders (1.4%), midfielders (2.5%), and goalkeepers (3.2%) over 0–20 m (P < .001). Midfielders jumped ~2.0 cm lower than the other playing positions (P < .05). Sprinting velocity peaked in the age range 20–28 y and declined significantly thereafter (P < .05). Players from 2006–2010 had 1–2% faster 0–20 m and peak velocity than players from the 1995–1999 and 2000–2005 epochs, whereas no differences in CMJ performance were observed.
This study provides effect-magnitude estimates for the influence of performance level, position, and age on sprint and CMJ performance in soccer. While CMJ performance has remained stable over the time, there has been a small but positive development in sprinting velocity among professional players.
Thomas A. Haugen, Espen Tønnessen and Stephen Seiler
The purpose of this investigation was to compare sprint and countermovement-jump (CMJ) performance among female competitive soccer players as a function of performance level, field position, and age. In addition, the authors wanted to quantify the evolution of these physical characteristics among elite players over a 15-y period.
194 female elite players (22± 4.1 y, 63 ± 5.6 kg), including an Olympic winning squad, tested 40-m sprint with electronic timing and CMJ on a force platform at the Norwegian Olympic training center from 1995 to 2010.
Moderate to large velocity differences across performance levels and positions were observed. National-team players were 2% faster than 1st-division players (P = .027, d = 0.5) and 5% faster than 2nd-division players (P < .001, d = 1.3) over 0–20 m. National-team players jumped 8–9% higher than 1st-division players (P = .001, d = 0.6) and junior elite players (P = .023, d = 0.5). Forwards were 3–4% faster than midfielders (P < .001, d = 0.8) and goalkeepers (P = .003, d = 0.9) over 0–20 m. No differences in velocity or CMJ height were observed among the age categories. Players from 2006–2010 were 2% faster (P < .05, d = 0.6) than players from 1995–1999 over 20 m, whereas no differences in 20- to 40-m velocity or CMJ performance were observed.
This study provides effect-magnitude estimates for the influence of performance level, age, and player position on sprint and CMJ performance in female soccer players. While 20- to 40-m velocity and CMJ performance have remained stable over the time, there has been a moderate but positive development in 0- to 20-m velocity among elite performers.
Espen Tønnessen, Erlend Hem, Svein Leirstein, Thomas Haugen and Stephen Seiler
The purpose of this investigation was to quantify maximal aerobic power (VO2max) in soccer as a function of performance level, position, age, and time of season. In addition, the authors examined the evolution of VO2max among professional players over a 23-y period.
1545 male soccer players (22 ± 4 y, 76 ± 8 kg, 181 ± 6 cm) were tested for VO2max at the Norwegian Olympic Training Center between 1989 and 2012.
No differences in VO2max were observed among national-team players, 1st- and 2nd-division players, and juniors. Midfielders had higher VO2max than defenders, forwards, and goalkeepers (P < .05). Players <18 y of age had ~3% higher VO2max than 23- to 26-y-old players (P = .016). The players had 1.6% and 2.1% lower VO2max during off-season than preseason (P = .046) and in season (P = .021), respectively. Relative to body mass, VO2max among the professional players in this study has not improved over time. Professional players tested during 2006–2012 actually had 3.2% lower VO2max than those tested from 2000 to 2006 (P = .001).
This study provides effect-magnitude estimates for the influence of performance level, player position, age, and season time on VO2max in men’s elite soccer. The findings from a robust data set indicate that VO2max values ~62–64 mL · kg−1 · min−1 fulfill the demands for aerobic capacity in men’s professional soccer and that VO2max is not a clearly distinguishing variable separating players of different standards.
Thomas Haugen, Gøran Paulsen, Stephen Seiler and Øyvind Sandbakk
Maximal aerobic and anaerobic power are crucial performance determinants in most sport disciplines. Numerous studies have published power data from elite athletes over the years, particularly in runners, cyclists, rowers, and cross-country (XC) skiers. This invited review defines the current “world records” in human upper limits of aerobic and anaerobic power. Currently,
Thomas A. Haugen, Espen Tønnessen, Jonny Hisdal and Stephen Seiler
The overall objective of this review was to investigate the role and development of sprinting speed in soccer. Time–motion analyses show that short sprints occur frequently during soccer games. Straight sprinting is the most frequent action before goals, both for the scoring and assisting player. Straight-line sprinting velocity (both acceleration and maximal sprinting speed), certain agility skills, and repeated-sprint ability are shown to distinguish groups from different performance levels. Professional players have become faster over time, indicating that sprinting skills are becoming more and more important in modern soccer. In research literature, the majority of soccer-related training interventions have provided positive effects on sprinting capabilities, leading to the assumption that all kinds of training can be performed with success. However, most successful intervention studies are time consuming and challenging to incorporate into the overall soccer training program. Even though the principle of specificity is clearly present, several questions remain regarding the optimal training methods within the larger context of the team-sport setting. Considering time-efficiency effects, soccer players may benefit more by performing sprint-training regimens similar to the progression model used in strength training and by world-leading athletics practitioners, compared with the majority of guidelines that traditionally have been presented in research literature.
Espen Tønnessen, Ida S. Svendsen, Bent R. Rønnestad, Jonny Hisdal, Thomas A. Haugen and Stephen Seiler
One year of training data from 8 elite orienteers were divided into a transition phase (TP), general preparatory phase (GPP), specific preparatory phase (SPP), and competition phase (CP). Average weekly training volume and frequency, hours at different intensities (zones 1–3), cross-training, running, orienteering, interval training, continuous training, and competition were calculated. Training volume was higher in GPP than TP, SPP, and CP (14.9 vs 9.7, 11.5, and 10.6 h/wk, P < .05). Training frequency was higher in GPP than TP (10 vs 7.5 sessions/wk, P < .05). Zone 1 training was higher in GPP than TP, SPP, and CP (11.3 vs 7.1, 8.3, and 7.7 h/wk, P < .05). Zone 3 training was higher in SPP and CP than in TP and GPP (0.9 and 1.1 vs 1.6 and 1.5 h/wk, P < .05). Cross-training was higher in GPP than SPP and CP (4.3 vs 0.8 h/wk, P < .05). Interval training was higher in GPP than TP, SPP, and CP (0.7 vs 0.3 h/wk, P < .05). High-intensity continuous training was higher in GPP than CP (0.9 vs 0.4 h/wk, P < .05), while competition was higher in SPP and CP than in TP and GPP (1.3 and 1.5 vs 0.6 and 0.3 h/wk, P < .01). In conclusion, these champion endurance athletes achieved a progressive reduction in total training volume from GPP to CP via a shortening of each individual session while the number of training sessions remained unchanged. This decrease in training volume was primarily due to a reduction in the number of hours of low-intensity, non-sport-specific cross-training.