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Dive into the research topics where Patrizia Knechtle is active.

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Featured researches published by Patrizia Knechtle.


Scandinavian Journal of Medicine & Science in Sports | 2011

Participation and performance trends in ultra-triathlons from 1985 to 2009.

Beat Knechtle; Patrizia Knechtle; Romuald Lepers

We examined the changes in participation and performance trends in ultra‐triathlons, from the Double Iron (7.6 km swimming, 360 km cycling, 84.4 km running) to the Deca Iron (38 km swimming, 1800 km cycling, 422 km running), between 1985 (first year of a Double Iron) and 2009 (25 years). The mean finish rate for all distances and races was 75.8%. Women accounted for ∼8–10% of the ultra‐triathlons starters. For Double and Triple Iron, the number of finishers per year increased, from 17 to 98 and from 7 to 41, respectively. In the Deca Iron, the finishers per race have remained <20 since the first event was held, up to 2009. Concerning World best performances, the men were ∼19% faster than the women in both the Double and Triple Iron, and ∼30% faster in a Deca Iron. With the increasing length of ultra‐triathlons, the best women became relatively slower compared with the best men. Further investigations are required to understand why this gender difference in total performance time increased with the distance in ultra‐triathlons.


Journal of Strength and Conditioning Research | 2010

Differential correlations between anthropometry, training volume, and performance in male and female Ironman triathletes.

Beat Knechtle; Andrea Wirth; Barbara Baumann; Patrizia Knechtle; Thomas Rosemann; Senn Oliver

Knechtle, B, Wirth, A, Baumann, B, Knechtle, P, Rosemann, T, and Senn, O. Differential correlations between anthropometry, training volume, and performance in male and female Ironman triathletes. J Strength Cond Res 24(10): 2785-2793, 2010-We investigated in 27 male Ironman triathletes aged 30.3 (9.1) years, with 77.7- (9.8) kg body mass, 1.78- (0.06) m body height, 24.3- (2.2) kg·m−2 body mass index (BMI), and 14.4 (4.8) % body fat and in 16 female Ironman triathletes aged 36.6 (7.0) years, with 59.7- (6.1) kg body mass, 1.66- (0.06) m body height, 21.5 (1.0) kg·m−2 BMI, and 22.8 (4.8) % body fat to ascertain whether anthropometric or training variables were related to total race time. The male athletes were training 14.8 (3.2) h·wk−1 with a speed of 2.7 (0.6) km·h−1 in swimming, 27.3 (3.0) in cycling, and 10.6 (1.4) in running. The female athletes trained for 13.9 (3.4) h·wk−1 at 2.1 (0.8) km·h−1h in swimming, 23.7 (7.6) km·h−1 in cycling, and 9.0 (3.7) km·h−1 in running, respectively. For male athletes, percent body fat was highly significantly (r2 = 0.583; p < 0.001) associated with total race time. In female triathletes, training volume showed a relationship to total race time (r2 = 0.466; p < 0.01). Percent body fat was unrelated to training volume for both men (r2 = 0.001; p > 0.05) and women (r2 = 0.007; p > 0.05). We conclude that percent body fat showed a relationship to total race time in male triathletes, and training volume showed an association with total race time in female triathletes. Presumably, the relationship between percent body fat, training volume, and race performance is genetically determined.


Perceptual and Motor Skills | 2010

Predictor Variables for A 100-km Race Time in Male Ultra-Marathoners

Beat Knechtle; Thomas Rosemann; Patrizia Knechtle; Romuald Lepers

In 169 male 100-km ultra-marathoners, the variables of anthropometry, training, and prerace experience, in order to predict race time, were investigated. In the bivariate analysis, age (r = .24), body mass (r = .20), Body Mass Index (r = .29), circumference of upper arm (r = .26), percent body fat (r = .45), mean weekly running hours (r = –.21), mean weekly running kilometers (r = –.43), mean speed in training (r = –.56), personal best time in a marathon (r = .65), the number of finished 100-km ultra-runs (r = .24), and the personal best time in a 100-km ultra-run (r = .72) were associated with race time. Stepwise multiple regression showed that training speed (p < .0001), mean weekly running kilometers (p < .0001), and age (p < .0001) were the best correlations for a 100-km race time. Performance may be predicted (n = 169, r2 = .43) by the following equation: 100-km race time (min) = 1, 085.60 – 36.26 × (training speed, km/hr.) −1.43 × (training volume, km/wk.) + 2.50 × (age, yr.). Overall, intensity of training might be more important for a successful outcome in a 100-km race than anthropometric attributes. Motivation to train intensely for such an ultra-endurance run should be explored as this might be the key for a successful finish.


British Journal of Sports Medicine | 2009

Personal best marathon performance is associated with performance in a 24-h run and not anthropometry or training volume

Beat Knechtle; Andrea Wirth; Patrizia Knechtle; Kanai Zimmermann; Goetz Kohler

Objective: In this study, the influence of anthropometric and training parameters on race performance in ultra-endurance runners in a 24-h run was investigated. Design: Descriptive field study. Setting: 24-h run in Basel 2007. Participants: 15 male Caucasian ultra-runners (mean (SD) 46.7 (5.8 years), 71.1 (6.8 kg), 1.76 (0.07 m), body mass index 23.1 (1.84 kg/m2)). Interventions: None. Main outcome measures: Age, body mass, body height, length of lower limbs, skin-fold thicknesses, circumference of extremities, skeletal muscle mass, body mass, percentage of body fat, and training volume in 15 successful finishers were determined to correlate anthropometric and training parameters with race performance. Results: No significant association (p>0.05) was found between the reached distance and the anthropometric properties. There was also no significant association between the reached distance with the weekly training hours, running years, the number of finished marathons and the number of finished 24-h runs. The reached distance was significantly (p<0.05) positively correlated with the personal best marathon performance (r2 = 0.40) and the personal best 24-h run distance (r2 = 0.58). Furthermore, the personal best marathon performance was significantly and positively correlated (p<0.01) with the best personal 24-h run distance (r2 = 0.76). Conclusions: Anthropometry and training volume does not seem to have a major effect on race performance in a 24-h run. Instead, a fast personal best marathon time seems to be the only positive association with race performance in a 24-h run.


British Journal of Sports Medicine | 2008

Upper arm circumference is associated with race performance in ultra-endurance runners

Beat Knechtle; Patrizia Knechtle; Ingo Schulze; Goetz Kohler

Objective: To investigate the association of anthropometric parameters to race performance in ultra-endurance runners in a multistage ultra-endurance run. Design: Descriptive field study. Setting: The Deutschlandlauf 2006 race in Germany, where athletes had to run 1200 km within 17 consecutive days. There were no interventions. Subjects: In total, there were 19 male Caucasian ultra-endurancerunners (mean (SD) 46.2 (9.6) years, 71.8 (5.2) kg, 179 (6) cm, BMI 22.5 (1.9) kg/m2). Main outcome measurements: Determination of body mass, body height, length of lower limbs, skin-fold thicknesses, circumference of limbs, body mass index (BMI), percentage skeletal muscle mass (%SM), and percentage body fat (%BF) in 19 successful finishers in order to correlate anthropometric parameters with running performance. Results: A significant association of upper arm circumference with the total running time was found (p<0.05, r2 = 0.26). No significant association was found with the directly measured anthropometric properties body height, body mass, average skin-fold thickness and the circumference of thigh and calf (p>0.05). Furthermore, no significant association was observed between the running time and the calculated parameters BMI, %BF, and %SM (p>0.05). Conclusions: In an ultra-endurance run over 1200 km within 17 consecutive days, circumference of the upper arm was the only factor associated with performance in well-experienced ultra-endurance runners. Body mass, BMI, body height, length of limbs, skin-fold thicknesses, circumference of limbs and the calculated percentage body composition of skeletal muscle mass and body fat showed no association with running performance.


International Journal of Sports Medicine | 2011

Upper body skinfold thickness is related to race performance in male Ironman triathletes

Beat Knechtle; Patrizia Knechtle; Thomas Rosemann

We investigated the association between skinfold thickness and race performance in male and female Ironman triathletes. Skinfold thicknesses at 8 sites and percent body fat were correlated to total race time including the split times for the 3 sub disciplines, for 27 male and 16 female Ironman athletes. In the males, percent body fat (r=0.76; p<0.0001), the sum of upper body skinfolds (r=0.75; p<0.0001) and the sum of all 8 skinfolds (r=0.71; p<0.0001) were related to total race time. Percent body fat (r=-0.67; p<0.001), the sum of upper body skinfolds (r=-0.63, p=0.0004) and the sum of all 8 skinfolds (r=-0.59; p<0.001) were also associated with speed in cycling during the race. In the females, none of the skinfold thicknesses showed an association with total race time, average weekly training volume or speed in the sub disciplines in the race. The results of this study indicate that low skinfold thicknesses of the upper body are related to race performance in male Ironman triathletes, but not in females.


Journal of Strength and Conditioning Research | 2010

Training volume and personal best time in marathon, not anthropometric parameters, are associated with performance in male 100-km ultrarunners.

Beat Knechtle; Andrea Wirth; Patrizia Knechtle; Thomas Rosemann

Knechtle, B, Wirth, A, Knechtle, P, and Rosemann, T. Training volume and personal best time in marathon, not anthropometric parameters, are associated with performance in male 100-km ultrarunners. J Strength Cond Res 24(3): 604-609, 2010-We investigated the relation between selected anthropometric and training variables and the personal best time in a marathon with total race time in 66 Caucasian male nonprofessional ultrarunners in a 100-km run. In the multiple linear regression analysis, the average weekly training volume in kilometers (r2 = 0.224, p < 0.01) and the personal best time in a marathon (r2 = 0.334, p < 0.01) were significantly associated with total race time, whereas no anthropometric variable was related to race performance (p > 0.05). We conclude that high training volume and a fast time in a marathon were more important for a fast race time in male 100-km runners than any of the determined anthropometric variables.


Journal of Sports Sciences | 2012

Best performances by men and women open-water swimmers during the ‘English Channel Swim’ from 1900 to 2010

Evelyn Eichenberger; Beat Knechtle; Patrizia Knechtle; Christoph Alexander Rüst; Thomas Rosemann; Romuald Lepers

Abstract Little research has examined ultra-endurance swimming performances. The ‘English Channel Swim’, where swimmers have to cover a distance of 32 km between England and France represents a unique long-distance, open-water, sea-swimming challenge, and each year swimmers from all over the world try to succeed in this challenge. The best times in minutes and the nationality of successful men and women swimmers were analysed from 1900 to 2010. A total of 1,533 swimmers (455 women and 1,078 men) from more than 40 countries have successfully completed the ‘English Channel Swim’. Great Britain was the country most represented, with 38% of the total, followed by the United States with 20%. Swim speed has increased progressively for both sexes (P < 0.001) but was lower for women than for men (0.68 ± 0.15 m · s−1 vs 0.71 ± 0.16 m · s−1 respectively, P < 0.01). However, the best annual performances did not differ between the sexes (men: 0.89 ± 0.20 m · s−1; women: 0.84 ± 0.18 m · s−1, P > 0.05). The results suggest that the performance of women open-water ultra-distance swimmers may be similar to that of men. Further studies investigating anthropometrical and physiological characteristics of open-water ultra-swimmers are needed to compare mens and womens open-water ultra-swim performances.


Journal of Sports Sciences | 2011

What is associated with race performance in male 100-km ultra-marathoners - anthropometry, training or marathon best time?

Beat Knechtle; Patrizia Knechtle; Thomas Rosemann; Oliver Senn

Abstract We investigated the associations of anthropometry, training, and pre-race experience with race time in 93 recreational male ultra-marathoners (mean age 44.6 years, s = 10.0; body mass 74.0 kg, s = 9.0; height 1.77 m, s = 0.06; body mass index 23.4 kg · m−2, s = 2.0) in a 100-km ultra-marathon using bivariate and multivariate analysis. In the bivariate analysis, body mass index (r = 0.24), the sum of eight skinfolds (r = 0.55), percent body fat (r = 0.57), weekly running hours (r = −0.29), weekly running kilometres (r = −0.49), running speed during training (r = −0.50), and personal best time in a marathon (r = 0.72) were associated with race time. Results of the multiple regression analysis revealed an independent and negative association of weekly running kilometres and average speed in training with race time, as well as a significant positive association between the sum of eight skinfold thicknesses and race time. There was a significant positive association between 100-km race time and personal best time in a marathon. We conclude that both training and anthropometry were independently associated with race performance. These characteristics remained relevant even when controlling for personal best time in a marathon.


Perceptual and Motor Skills | 2010

Intra- and Inter-Judge Reliabilities in Measuring the Skin-Fold Thicknesses of Ultra Runners under Field Conditions

Beat Knechtle; Irena Joleska; Andrea Wirth; Patrizia Knechtle; Thomas Rosemann; Oliver Senn

Inter- and intra-judge reliabilities of skinfold measures were investigated in a sample of 27 men and 11 women ultramarathon runners. Two physicians had agreement higher than 90% in field measurements before an ultramarathon race.

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Andrea Wirth

University of St. Gallen

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Claudia Mrazek

University of St. Gallen

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