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From Heart-Rate Data to Training Quantification: A Comparison of 3 Methods of Training-Intensity Analysis

Øystein Sylta, Espen Tønnessen, and Stephen Seiler

Purpose:

The authors directly compared 3 frequently used methods of heart-rate-based training-intensity-distribution (TID) quantification in a large sample of training sessions performed by elite endurance athletes.

Methods:

Twenty-nine elite cross-country skiers (16 male, 13 female; 25 ± 4 y; 70 ± 11 kg; 76 ± 7 mL · min−1 · kg−1 VO2max) conducted 570 training sessions during a ~14-d altitude-training camp. Three analysis methods were used: time in zone (TIZ), session goal (SG), and a hybrid session-goal/time-in-zone (SG/TIZ) approach. The proportion of training in zone 1, zone 2, and zone 3 was quantified using total training time or frequency of sessions, and simple conversion factors across different methods were calculated.

Results:

Comparing the TIZ and SG/TIZ methods, 96.1% and 95.5%, respectively, of total training time was spent in zone 1 (P < .001), with 2.9%/3.6% and 1.1%/0.8% in zones 2/3 (P < .001). Using SG, this corresponded to 86.6% zone 1 and 11.1%/2.4% zone 2/3 sessions. Estimated conversion factors from TIZ or SG/TIZ to SG and vice versa were 0.9/1.1, respectively, in the low-intensity training range (zone 1) and 3.0/0.33 in the high-intensity training range (zones 2 and 3).

Conclusions:

This study provides a direct comparison and practical conversion factors across studies employing different methods of TID quantification associated with the most common heart-rate-based analysis methods.

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Do Elite Endurance Athletes Report Their Training Accurately?

Øystein Sylta, Espen Tønnessen, and Stephen Seiler

Purpose:

The purpose of this study was to validate the accuracy of self-reported (SR) training duration and intensity distribution in elite endurance athletes.

Methods:

Twenty-four elite cross-country skiers (25 ± 4 y, 67.9 ± 9.88 kg, 75.9 ± 6.50 mL · min−1 · kg−1) SR all training sessions during an ~14-d altitude-training camp. Heart rate (HR) and some blood lactate measurements were collected during 466 training sessions. SR training was compared with recorded training duration from HR monitors, and SR intensity distribution was compared with expert analysis (EA) of all session data.

Results:

SR training was nearly perfectly correlated with recorded training duration (r = .99), but SR training was 1.7% lower than recorded training duration (P < .001). SR training duration was also nearly perfectly correlated (r = .95) with recorded training duration >55% HRmax, but SR training was 11.4% higher than recorded training duration >55% HRmax (P < .001) due to SR inclusion of time <55% HRmax. No significant differences were observed in intensity distribution in zones 1–2 between SR and EA comparisons, but small discrepancies were found in zones 3–4 (P < .001).

Conclusions:

This study provides evidence that elite endurance athletes report their training data accurately, although some small differences were observed due to lack of a SR “gold standard.” Daily SR training is a valid method of quantifying training duration and intensity distribution in elite endurance athletes. However, additional common reporting guidelines would further enhance accuracy.

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Correction Factors for Photocell Sprint Timing With Flying Start

Thomas Haugen, Espen Tønnessen, and Stephen Seiler

Purpose:

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.

Methods:

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.

Results:

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).

Conclusions:

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.

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9.58 and 10.49: Nearing the Citius End for 100 m?

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.

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The Multidisciplinary Process Leading to Return From Underperformance and Sustainable Success in the World’s Best Cross-Country Skier

Guro Strøm Solli, Espen Tønnessen, and Øyvind Sandbakk

Purpose: To investigate the factors associated with underperformance and the subsequent changes in training characteristics and supportive actions when returning to the world’s best cross-country skier. Methods: The participant is the most decorated winter Olympian, with 8 Olympic gold medals, 18 World Championship titles, and 114 World Cup victories. Training data were categorized by training form (endurance, strength, and speed); intensity (low, moderate, and high); and mode (running, cycling, and skiing/roller skiing). In addition, test data were retrospectively analyzed, and interviews were performed with the participant and her support team. Results: After the competitive season, the participant had 8 weeks without systematic training and an evaluation process aiming to detect the factors contributing to underperformance. Here physiological, technical, and psychological challenges were detected. As a consequence, the participant included less high-intensity training (1.2 vs 2.1 sessions/wk, P = .011); more moderate-intensity training (0.9 vs 0.4 sessions/wk, P = .016); and more low-intensity training (6.9 vs 5.9 sessions/wk, P = .036) during the general preparation phase but with similar total endurance training load as previous season. In addition, more strength training (1.6 vs 1.1 h/wk, P = .036) and new ski-specific strength exercises were included. Finally, the athlete’s autonomy when planning and adjusting training was increased, nontraining stressors were reduced, more frequent testing was included, systematic mental training was initiated, her nutritional strategy was adjusted, and her asthma treatment was optimized. Conclusions: Overall, the current case study could be used as a framework for the holistic approach to treating an overtraining condition and for generation of new hypothesis in this exiting area.

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Speed and Countermovement-Jump Characteristics of Elite Female Soccer Players, 1995–2010

Thomas A. Haugen, Espen Tønnessen, and Stephen Seiler

Purpose:

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.

Methods:

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.

Results:

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.

Conclusions:

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.

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Anaerobic Performance Testing of Professional Soccer Players 1995–2010

Thomas A. Haugen, Espen Tønnessen, and Stephen Seiler

Purpose:

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.

Methods:

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.

Results:

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.

Conclusions:

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.

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The Role and Development of Sprinting Speed in Soccer

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.

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VO2max Characteristics of Elite Female Soccer Players, 1989–2007

Thomas A. Haugen, Espen Tønnessen, Erlend Hem, Svein Leirstein, and Stephen Seiler

Purpose:

To quantify VO2max among female competitive soccer players as a function of performance level, field position, and age. In addition, the evolution of VO2max among world-class players over an 18-y period was quantified.

Methods:

Female players (N = 199, 22 ± 4 y, 63 ± 6 kg, height 169 ± 6 cm), including an Olympic winning squad, were tested for VO2max at the Norwegian Olympic Training Center between 1989 and 2007.

Results:

National-team players had 5% higher VO2max than 1st-division players (P = .042, d = 0.4), 13% higher than 2nd-division players (P < .001, d = 1.2), and 9% higher than junior players (P = .005, d = 1.0). Midfielders had 8% higher VO2max than goalkeepers (P = .048, d = 1.1). No significant differences were observed across outfield players or different age categories. There was a trend toward lower relative VO2max across time epochs.

Conclusions:

This study demonstrated that VO2max varies across playing-standard level in women’s soccer. No significant differences in VO2max were observed across outfield positions and age categories. Over time, there has been a slight negative development in VO2max among elite Norwegian soccer players.

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Maximal Aerobic Power Characteristics of Male Professional Soccer Players, 1989–2012

Espen Tønnessen, Erlend Hem, Svein Leirstein, Thomas Haugen, and Stephen Seiler

Purpose:

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.

Methods:

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.

Results:

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).

Conclusions:

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.