road cycling
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2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Harry Arne Solberg ◽  
Denis Mike Becker ◽  
Jon Martin Denstadli ◽  
Frode Heldal ◽  
Per Ståle Knardal ◽  
...  

PurposeThis paper sought to determine how a major sport event can become trapped in a winner's curse, in which the fierce competition to host the event forces organisers to spend more on acquiring and hosting it than what it is worth in economic terms.Design/methodology/approachThis study used a combination of document analysis and 47 in-depth interviews with 51 individuals representing various private and public organisations involved in the implementation of the UCI 2017 Road Cycling World Championship. Snowball sampling and a semi-structured interview guide were used to ensure coverage of all relevant information.FindingsThe organiser and the host municipal lacked the necessary experience with events of this size and character. Information from previous championships events was not transferred, and the municipality administration did not utilise experiences from hosting previous events. Limited financial resources prevented the organiser from hiring enough employees with the necessary competence. Lack of communication between the stakeholders who contributed in hosting the event reduced the quality of planning and preparations. A dubious culture and lack of seriousness within the Norwegian Cycling Federation, which was the owner of organising company, seemed to have been transferred to organiser.Originality/valueThe research identifies some of the reasons why major sports events so often turns out to be more problematic than expected in economic terms, not only for the organiser but also for actors in the public sector in the host city. The novelty is that it goes into depth on the underlying reasons and the dynamic forces behind these problems.


2021 ◽  
Vol 3 ◽  
Author(s):  
Leonid Kholkine ◽  
Thomas Servotte ◽  
Arie-Willem de Leeuw ◽  
Tom De Schepper ◽  
Peter Hellinckx ◽  
...  

Professional road cycling is a very competitive sport, and many factors influence the outcome of the race. These factors can be internal (e.g., psychological preparedness, physiological profile of the rider, and the preparedness or fitness of the rider) or external (e.g., the weather or strategy of the team) to the rider, or even completely unpredictable (e.g., crashes or mechanical failure). This variety makes perfectly predicting the outcome of a certain race an impossible task and the sport even more interesting. Nonetheless, before each race, journalists, ex-pro cyclists, websites and cycling fans try to predict the possible top 3, 5, or 10 riders. In this article, we use easily accessible data on road cycling from the past 20 years and the Machine Learning technique Learn-to-Rank (LtR) to predict the top 10 contenders for 1-day road cycling races. We accomplish this by mapping a relevancy weight to the finishing place in the first 10 positions. We assess the performance of this approach on 2018, 2019, and 2021 editions of six spring classic 1-day races. In the end, we compare the output of the framework with a mass fan prediction on the Normalized Discounted Cumulative Gain (NDCG) metric and the number of correct top 10 guesses. We found that our model, on average, has slightly higher performance on both metrics than the mass fan prediction. We also analyze which variables of our model have the most influence on the prediction of each race. This approach can give interesting insights to fans before a race but can also be helpful to sports coaches to predict how a rider might perform compared to other riders outside of the team.


Sports ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 136
Author(s):  
Christopher R. Harnish ◽  
Hamish A. Ferguson ◽  
Gregory P. Swinand

(1) Background: This report examines the unique demands of off-road triathlon (XT) by presenting physiological, field, and race data from a national champion off-road triathlete using several years of laboratory and field data to detail training and race intensity. (2) Methods: Laboratory and field data were collected when the athlete was at near peak fitness and included oxygen consumption (VO2), heart rate (HR), power output (W), and blood lactate (BLC) during cycling and running, while HR, cycling W, and running metrics were obtained from training and race data files over a period of seven years. Intensity was described using % HR max zones (Z) 1 < 75%, 2 = 75–87%, and Zone 3 > 87%, and W. An ordinary least squares analysis was used to model differences between event types. (3) Results: Weather conditions were not different across events. XT events had twice the elevation change (p < 0.01) and two-three times greater anaerobic work capacity (W’) (p < 0.001) than road triathlon (ROAD), but similar HR intensity profiles (max, avg, and zones); both events are predominately performed at >Z2 or higher intensity. Championship XT events were longer (p < 0.01), with higher kJ expenditure (p < 0.001). Ordinary Least Squares (OLS) modelling suggested three variables were strongly related (R2 = 0.84; p < 0.0001) to cycling performance: event type (XT vs ROAD), total meters climbed, and total bike duration. Championship XT runs were slower than either regional (p < 0.05) or ROAD (p < 0.01) runs, but HR intensity profiles similar. OLS modelling indicates that slower running is linked to either greater total bike kJ expenditure (R2 = 0.57; p < 0.001), or total meters gained (R2 = 0.52; p < 0.001). Race simulation data support these findings but failed to produce meaningful differences in running. Conclusions: XT race demands are unique and mirror mountain bike (MTB) and trail running demands. XT athletes must be mindful of developing anaerobic fitness, technical ability, and aerobic fitness, all of which contribute to off-road cycling economy. It is unclear whether XT cycling affects subsequent running performance different from ROAD cycling.


2021 ◽  
pp. 175-191
Author(s):  
Suzanne Ryder ◽  
Fiona McLachlan ◽  
Brent McDonald
Keyword(s):  

2021 ◽  
Vol 108 (Supplement_6) ◽  
Author(s):  
J Peacock ◽  
J Cobley ◽  
B Patel

Abstract Aim Cycle use has vastly increased over the last few years in the UK. The aim of this review was to evaluate the effect of cycling on the common conditions presenting to the urology clinic, in particular those of raised PSA, haematuria, soft tissue lesions (“cyclist nodules”) and pudendal nerve entrapment syndromes. Method A PUBMED search of the literature on cycling and genitourinary disorders was performed. The keywords included “Bicycling” AND “Prostate-specific antigen”, “Bicycling” AND “Haematuria”, “Bicycling” AND “Cyclist Nodules”, “Bicycling” AND “Pudendal Nerve Entrapment”. Results The literature suggests no significant change in total PSA levels after a bout of cycling, regardless of age. The type of cycling (mountain biking vs. road cycling) does not influence PSA levels. It is possible that the saddle used in cycling may displace the pressure across the perineal and gluteal region to effectively alleviate pressure on the prostate. Haematuria appears to be rare with cycling but has been described. Perineal nodular induration is a very rare - although possibly under diagnosed condition. It is thought to be caused by repetitive micro trauma from contact between the perineum and saddle. Pudendal nerve entrapment (PNE) represents the most common bicycling associated urogenital problem. Numbness in the perineum, penis, scrotum or the buttocks is the most common and most recognised symptom. Genital numbness may occur unrelated to erectile dysfunction (ED) although cycling related ED is invariably associated with genital numbness. Conclusions Urology Trainees and Consultants should be aware of how recreational and high-level cycling may result in presentation to the Urology clinic.


Author(s):  
Christopher R Harnish ◽  
Hamish A Ferguson ◽  
Gregory P Swinand

(1) Background: This report examines the unique demands of off-road triathlon (XT) by presenting physiological, field, and race data from a national champion off-road triathlete using several years of laboratory and field data to detail training and race intensity. (2) Methods: Laboratory and field data were collected when the athlete was at near peak fitness and included oxygen consumption (VO2), heart rate (HR), power output (W), and blood lactate (BLC) during cycling and running, while HR, cycling W, and running metrics were obtained from training and race data files over a period of seven years. Intensity was described using % HR max zones (Z) 1 &amp;lt; 75%, 2 = 75 - 87%, and Zone 3 &amp;gt; 87%, and W. An ordinary least squares analysis was used to model differences between event types. (3) Results: Weather conditions were not different across events. XT events had twice the elevation change (p&amp;lt;0.01) and two-three times greater W&rsquo; (p&amp;lt; 0.001) than road triathlon (ROAD), but similar HR intensity profiles (max, avg, and zones); both events are predominately performed at &amp;gt; Z2 or higher intensity. Championship XT events were longer (p&amp;lt;0.01) , with higher kJ expenditure (p&amp;lt;0.001). OLS modelling suggested three variables were strongly related (R2 = 0.84; p &amp;lt; 0.0001) to cycling performance: event type (XT vs ROAD), total meters climbed, and total bike duration. Championship XT runs were slower than either regional (p&amp;lt;0.05) or ROAD (p&amp;lt;0.01) runs, but HR intensity profiles similar. OLS modelling indicates that slower running is linked to either greater total bike kJ expenditure (R2 = 0.57; p&amp;lt;0.001), or total meters gained (R2 = 0.52; p&amp;lt;0.001). Race simulation data support these findings but failed to produce meaningful differences in running. Conclusions: XT race demands are unique and mirror MTB and trail running demands. XT athletes must be mindful of developing anaerobic fitness, technical ability, and aerobic fitness, all of which contribute to off-road cycling economy. It is unclear whether XT cycling affects subsequent running performance different from ROAD cycling.


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