Pacing Behavior and Tactical Positioning in 1500-m Short-Track Speed Skating

Purpose:To gain more insight in pacing behavior and tactical positioning in 1500-m short-track speed skating, a sport in which several athletes directly compete in the same race.Methods:Lap times and intermediate rankings of elite 1500-m short-track-skating competitors were collected over the season 2012–13 (N = 510, 85 races). Two statistical approaches were used to assess pacing behavior and tactical positioning. First, lap times were analyzed using a MANOVA, and for each lap differences between sex, race type, final rankings, and stage of competition were determined. Second, Kendall tau b correlations were used to assess relationships between intermediate and final rankings. In addition, intermediate rankings of the winner of each race were examined.Results:In 1500 m (13.5 laps of 111.12 m), correlations between intermediate and final ranking gradually increased throughout the race (eg, lap 1, r = .05; lap 7, r = .26; lap 13, r = .85). Moreover, the percentage of race winners skating in the leading position was over 50% during the last 3 laps. Top finishers were faster than bottom-place finishers only during the last 5 laps, with on average 0.1- to 1.5-s faster lap times of the race winners compared with the others during the last 5 laps.Conclusions:Although a fast start led to faster finishing times, top finishers were faster than bottom-placed finishers only during the last 5 laps. Moreover, tactical positioning at 1 of the foremost positions during the latter phase of the race appeared to be a strong determinant of finishing position.</jats:sec

Spatio-temporal Analysis of Remote Sensing and Field Measurements for Smart Farming

AbstractFor the optimization of crop yield and quality, there is an ongoing development in improving crop management advice, in order to cope with the spatial variability of the growth process, caused by local variations in, amongst others, soil composition, moisture and nutrition content. To achieve this improvement, reliable information is required on the actual status of the vegetation and the expected development and yield given different management scenarios. Remote sensing observations form a valuable information source for assessing the location of suboptimal growth, but hardly ever provide the cause of the arrearage. In order to determine this cause, the observations must be combined with other observations and models and analyzed integrally.This article presents the followed approach and initial results of a pilot project Smart Farming carried out in the Dutch North East Polder. Observations and data from several sources have been collected for a number of potato parcels in 2014. The collected data includes multi-temporal satellite and UAS observations, field based soil, vegetation and yield observations, soil type maps, height maps, historic parcel and crop information and meteorological data. A data driven approach was followed to determine the presence of relations between the various observations in order to couple location and probable cause of sub-optimal crop growth and determine temporal developments in series of observations. The available data was analyzed integrally using correlation, regression and histogram analysis techniques. All resulting spatial layers are visually presented in a GIS based web service environment, so that the advisor or farmer can view the raw and derived information interactively and form his/her conclusions

Exploring the Design of mHealth Systems for Health Behavior Change using Mobile Biosensors

A person’s health behavior plays a vital role in mitigating their risk of disease and promoting positive health outcomes. In recent years, mHealth systems have emerged to offer novel approaches for encouraging and supporting users in changing their health behavior. Mobile biosensors represent a promising technology in this regard; that is, sensors that collect physiological data (e.g., heart rate, respiration, skin conductance) that individuals wear, carry, or access during their normal daily activities. mHealth system designers have started to use the health information from physiological data to deliver behavior-change interventions. However, little research provides guidance about how one can design mHealth systems to use mobile biosensors for health behavior change. In order to address this research gap, we conducted an exploratory study. Following a hybrid approach that combines deductive and inductive reasoning, we integrated a body of fragmented literature and conducted 30 semi-structured interviews with mHealth stakeholders. From this study, we developed a theoretical framework and six general design guidelines that shed light on the theoretical pathways for how the mHealth interface can facilitate behavior change and provide practical design considerations

Pacing Behavior and Tactical Positioning in 500- and 1000-m Short-Track Speed Skating

Purpose: To explore pacing behavior and tactical positioning during the shorter 500- and 1000-m short-track competitions. Methods: Lap times and intermediate rankings of elite 500- and 1000-m short-track-skating competitors were collected over the 2012–13 season. First, lap times were analyzed using a MANOVA, and for each lap, differences between sex, race type, final ranking, and stage of competition were determined. Second, Kendall tau-b correlations were used to assess relationships between intermediate and final rankings. In addition, intermediate rankings of the winner of each race were examined. Results: Top-placed athletes appeared faster than bottom-placed athletes in every lap in the 500-m, while in the 1000-m no differences were found until the final 4 laps (P < .05). Correlations between intermediate and final rankings were already high at the beginning stages of the 50-m (lap 1: r = .59) but not for the 1000-m (lap 1: r = .21). Conclusions: Although 500- and 1000-m short-track races are both relatively short, fundamental differences in pacing behavior and tactical positioning were found. A fast-start strategy seems to be optimal for 500-m races, while the crucial segment in 1000-m races seems to be from the 6th lap to the finish line (ie, after ± 650 m). These findings provide evidence to suggest that athletes balance between choosing an energetically optimal profile and the tactical and positional benefits that play a role when riding against an opponent, as well as contributing to developing novel insights in exploring athletic behavior when racing against opponents

Successful pacing profiles of Olympic and IAAF World Championship middle-distance runners across qualifying rounds and finals

Purpose: This was the first study to analyze high-resolution pacing data from multiple global championships, allowing for deeper and rigorous analysis of pacing and tactical profiles in elite-standard middle-distance racing. The aim of this study was to analyze successful and unsuccessful middle-distance pacing profiles and variability across qualifying rounds and finals. Methods: Finishing and 100-m split speeds and season’s best times (SB) were collected for 265 men and 218 women competing in 800 m and 1500 m races, with pace variability expressed using coefficient of variation (CV). Results: In both events, successful athletes generally separated themselves from slower athletes in the final 200 m, not by speeding up, but by avoiding slowing compared with competitors. This was despite different pacing profiles between events in the earlier part of the race preceding the endspurt. Approximately 10% of athletes ran SBs, showing a tactical approach to elite-standard middle-distance racing, and possible fatigue across rounds. Men’s and women’s pacing profiles were remarkably similar within each event, but the previously undescribed seahorse-shaped profile in the 800 m (predominantly positive pacing) differed from the J-shaped negative pacing of the 1500 m. Pacing variability was high compared with world records, especially in the finals (CV: 5.2 – 9.1%), showing that athletes need to be able to vary pace and cope with surges. Conclusions: Previous studies have focussed more on athletes in finals, but the present study showed that the best athletes had the physiological capacity to vary pace and respond to surges through successive competition rounds

Preceding Race Efforts Affect Pacing and Short-Track Speed Skating Performance

Purpose: To examine whether preceding high-intensity race efforts in a competitive weekend affected pacing behaviour and performance in elite short-track speed skaters. Methods: Finishing and intermediate lap times were gathered from 500, 1000 and 1500 m Short Track Speed Skating World Cups during the seasons 2011-2016. The effect of preceding races on pacing behaviour and performance was explored using two studies. Study I: the effect of competing in extra races due to the Repechage (Rep) system, leading to an increased number of high-intensity race efforts prior to the subsequent main tournament race, was explored (500m: N=32, 1000m: N=34; 1500m: N=47). Study II: the performance of skaters over the tournament days was evaluated (500m: N=129, 1000m: N=54; 1500m: N=114). For both analytic approaches, a two-way repeated measures ANOVA was used to assess differences in pacing and performance within the skater over the races. Results: An additional number of preceding high-intensity race efforts due to the Rep system reduced the qualification percentage in the first main tournament race for the next stage of competition in all events (500m: Direct qualification=57.3%, Rep=25.0%; 1000m: Direct=44.2%, Rep=28.3%; 1500m: Direct=27.1%, Rep=18.2%), and led to a decreased pace in the initial two laps of the 500m event. In contrast, Tournament day (Saturday vs Sunday) only affected the pacing behaviour of female skaters during the 1500m event. Conclusion: High-intensity race efforts earlier on the day affected pacing and performance of elite skaters, while the effect of high-intensity race efforts from the previous day seem to be only marginal

Racing an Opponent Alters Pacing, Performance and Muscle Force Decline, But Not RPE.

Performing against a virtual opponent has been shown to invite a change in pacing and improve time trial (TT) performance. This study explored how this performance improvement is established by assessing changes in pacing, neuromuscular function and perceived exertion.After a peak power output test and a familiarization TT, twelve trained cyclists completed two 4-km TTs in randomized order on a Velotron cycle ergometer. Time trial conditions were riding alone (NO), and riding against a virtual opponent (OP). Knee-extensor performance was quantified before and directly after the TT using maximal voluntary contraction force (MVC), voluntary activation (VA) and potentiated doublet-twitch force (PT). Differences between the experimental conditions were examined using Repeated-measures ANOVAs. Linear regression analyses were conducted to associate changes in pacing to changes in MVC, VA and PT.OP was completed faster than NO (mean power output OP: 289.6±56.1W vs. NO: 272.2±61.6W; p=0.020), mainly due to a faster initial pace. This was accompanied by a greater decline in MVC (MVCpre-vs-post: -17.5±12.4% vs. -11.4±10.9%, P=0.032) and PT (PTpre-vs-post: -23.1±14.0% vs. -16.2±11.4%, P=0.041) after OP compared to NO. No difference between conditions was found for VA (VApre-vs-post: -4.9±6.7% vs. -3.4±5.0%, P=0.274). RPE did not differ between OP and NO.The improved performance when racing against a virtual opponent was associated with a greater decline in voluntary and evoked muscle force compared to riding alone, without a change in perceived exertion, highlighting the importance of human-environment interactions in addition to one's internal state for pacing regulation and performance