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Power Meter Principles for Optimizing Testing, Training and Performance Strategies in Cycling
Published in Youlian Hong, Routledge Handbook of Ergonomics in Sport and Exercise, 2013
In regards to pacing strategies, quadrant analysis allows a cyclist to visualize how a given pace was actually achieved. In context to our Ironman triathlete example above, the goal for the cycle portion of the race would be to maintain a pace that allowed the athlete to spend a majority of his or her race pace time in quadrants 3 and 4 (Figure 20.7). On the other hand, if pacing was such that the triathlete pushed too large a gear at lower cadence or CPV, this would result in the triathlete spending too much time in quadrant 2. The end result of this type of pacing strategy would lead to unwanted loss of muscle glycogen prior to the start of the marathon race segment diminishing the athlete’s run performance. Thus, the use of quadrant analysis allows a triathlete and coach to fine tune effective strategies about pacing, rpm selection, gearing and even optimum crank length to help the rider achieve a target speed with the least detriment to glycogen stores prior to starting the post-ride marathon run.
A Day in the Life of Airman Basic Smith
Published in C.A.P. Smith, Kenneth W. Kisiel, Jeffrey G. Morrison, Working Through Synthetic Worlds, 2009
Peter Garretson, Nathan T. Denny
Steve was wearing standard issue under garments that were technological marvels akin to his glasses. His wearable computer integrated with the garments and could monitor body posture and dynamics as well as core temperature. Sensing that Steve was getting warm, his garments changed state to release heat more efficiently. His wearable computer monitored his running gait and overlaid virtual footprints for optimal pacing along with a metronomic beat to keep pace. Tiny translucent outlines reminded him to swing his arms slightly more and run slightly more erect. On the pavement appeared markers showing the remaining distance to go.
Systemic Innovation Toolset
Published in Alex Gorod, Leonie Hallo, Vernon Ireland, Indra Gunawan, Evolving Toolbox for Complex Project Management, 2019
Gerrit Muller, Kristin Falk, Marianne Kjørstad
Pacing is an approach where a set of high-level milestones, related to specific achievements, sets the pace of the innovation team. The milestones serve the investors’ need to monitor progress; often achievement of such milestone is a prerequisite for paying the next installment. Each milestone is stretching the team’s ability to keep the team sharp. The project team gets a financial and a technical incentive for making progress. Figure 23.7 shows an example of such pacing milestones.
Stepping up with GGIR: Validity of step cadence derived from wrist-worn research-grade accelerometers using the verisense step count algorithm
Published in Journal of Sports Sciences, 2022
Alex V. Rowlands, Benjamin Maylor, Nathan P. Dawkins, Paddy C. Dempsey, Charlotte L. Edwardson, Artur A. Soczawa-Stronczyk, Mateusz Bocian, Matthew R. Patterson, Tom Yates
To ensure a range of walking speeds as well as “preferred speeds” were covered, participants completed three walks in a park along a hard path standardised between participants to represent a slow, steady, and brisk pace, followed by three self-paced slow, steady, and brisk walks. For the standardised speeds, a steady walking speed based on leg length (predicted from height (Pheasant, 1982)), was calculated for each participant (Kramer & Sarton-Miller, 2008). The associated pacing frequency was determined (Soczawa-Stronczyk et al., 2019) to facilitate metronome regulation of pace. Standardised slow and brisk speeds were 10% below and above the steady speed, respectively. For the self-paced slow walk participants were asked to walk “at a pace they may use when strolling along chatting”, the self-paced steady walk “at their preferred pace”, and the self-paced brisk walk “at a pace that feels brisk or purposeful”. Finally, participants were given the option of a self-paced run around the park at a “comfortable and consistent pace which they could maintain for 5 km”. Each walk was straight “out and back” with a turn at the mid-point to return to the starting point and approximately 485 m long. The run was a loop round the park with some right angle turns and approximately 1,110 m long. Speed was calculated from the duration (start and end time) and distance of each walk/run.
Marathon pacing ability: Training characteristics and previous experience
Published in European Journal of Sport Science, 2020
P. Swain, J. Biggins, D. Gordon
Online public databases provided by the marathon race organisers were used to obtain the participant’s halfway and finish split times of the marathon. Pacing ability was calculated as the percentage change in pace between the second half and first half of the marathon, denoted as %Pchange. Based on the magnitude of the %Pchange, participants were categorised into three pacing ability groups based upon thresholds by Deaner et al. (2015): <10%Pchange ‘maintaining pace’, 10%–20%Pchange ‘moderate slowdown’ and >20%Pchange ‘marked slowdown’. Regarding the participants (n = 45) that completed the London marathon; 5 km split times were collected. The coefficient of variation (CV) was calculated from each 5 km split, denoted as 5kmCV to reflect pace variability. To minimise sex-based difference in endurance performance personal best times (e.g. 5, 10, 21 and 42 km) and 2017 marathon finishing time, a 12% adjustment factor was applied to women’s performance times. Details regarding the sex-based adjustment factor can be found elsewhere (Deaner et al., 2015).
Differences in pacing of cross-country skiers by nationality – The example of Vasaloppet 2004-2017
Published in Research in Sports Medicine, 2019
Pantelis T. Nikolaidis, Beat Knechtle
Despite the well-studied effect of nationality on performance, limited information exists about the relationship between nationality and pacing (Nikolaidis, Käch, et al., 2017). Pacing, i.e. the changes of speed during a race, is related to performance; thus, it would be of great interest for sports scientists and coaches to know its variation by nationality in XC skiing. The knowledge of whether athletes of a certain nationality pace differently from others might help XC skiers being prepared for the pacing of their opponents and managing their own pacing during the race. The present study focuses on Vasaloppet XC skiing race, the oldest and with the largest participation in the world.