Time–Motion Analysis of a 2-Hour Surfing Training Session

2015 ◽  
Vol 10 (1) ◽  
pp. 17-22 ◽  
Author(s):  
Josh L. Secomb ◽  
Jeremy M. Sheppard ◽  
Ben J. Dascombe

Purpose:To provide a descriptive and quantitative time–motion analysis of surfing training with the use of global positioning system (GPS) and heart-rate (HR) technology.Methods:Fifteen male surfing athletes (22.1 ± 3.9 y, 175.4 ± 6.4 cm, 72.5 ± 7.7 kg) performed a 2-h surfing training session, wearing both a GPS unit and an HR monitor. An individual digital video recording was taken of the entire surfing duration. Repeated-measures ANOVAs were used to determine any effects of time on the physical and physiological measures.Results:Participants covered 6293.2 ± 1826.1 m during the 2-h surfing training session and recorded measures of average speed, HRaverage, and HRpeak as 52.4 ± 15.2 m/min, 128 ± 13 beats/min, and 171 ± 12 beats/min, respectively. Furthermore, the relative mean times spent performing paddling, sprint paddling to catch waves, stationary, wave riding, and recovery of the surfboard were 42.6% ± 9.9%, 4.1% ± 1.2%, 52.8% ± 12.4%, 2.5% ± 1.9%, and 2.1% ± 1.7%, respectively.Conclusion:The results demonstrate that a 2-h surfing training session is performed at a lower intensity than competitive heats. This is likely due to the onset of fatigue and a pacing strategy used by participants. Furthermore, surfing training sessions do not appear to appropriately condition surfers for competitive events. As a result, coaches working with surfing athletes should consider altering training sessions to incorporate repeated-effort sprint paddling to more effectively physically prepare surfers for competitive events.

2015 ◽  
Vol 10 (Special Issue 2) ◽  
Author(s):  
Low Chee Yong ◽  
Matthew James Wylde ◽  
Gabriel C.W. Choong ◽  
Dipna Lim-Prasad

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Yi-Chia Lee ◽  
Huang-Fu Yeh ◽  
Yen-Pin Chen ◽  
Chun-Yi Chang ◽  
Wei-Ting Chen ◽  
...  

Objectives: Accelerometer (Q-CPR) has been developed and promoted to monitor the quality of cardiopulmonary resuscitation (CPR). Although the device registers the occurrence of no-flow intervals, it does not provide comprehensive information on the causes leading to these no-flow intervals. This study is aimed to analyze causes leading to CPR interruptions registered by Q-CPR by reviewing corresponding video recordings of the resuscitation sessions. Methods: Accelerometer recordings (Q-CPR, Philips) of 20 CPR episodes from December 2010 to April 2014 in a tertiary university ED were obtained. Frequency, timing, duration, and types of no-flow intervals, defined as no-flow duration >= 1.5 seconds, were reviewed. Video recordings of the corresponding CPR sessions were reviewed. Causes leading no flow intervals registered by Q-CPR were categorized and analyzed. Results: The duration of CPR reviewed for the cases averaged 8.59 minutes (range 2.23 - 19.04 minutes). No-flow intervals (pauses >= 1.5 seconds) occurred 122 times (averaged one interruption every 1.27 minutes of CPR) with an average no-flow intervals of 6.45 seconds (range 1.54 - 51.50 seconds). Through detail review of the video-recordings corresponding to the no-flow intervals registered by Q-CPR, the leading causes of no-flow intervals are associated with pulse checks for pulseless electric activity- PEA (19.5%), pre-shock pauses (13.9%), ultrasound exam (11.6%) and intubation (9.6%), as displayed in the following chart. Conclusion: Video recording and time-motion analysis provide detailed information on the causes leading to no-flow intervals registered by QCPR, and could complement information acquired by Q-CPR. Measures should be taken to address leading causes of CPR interruption, especially pulse checks for PEA and pre-shock pauses, to promote quality of CPR.


2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Filipe Manuel Clemente ◽  
Pantelis Theodoros Nikolaidis ◽  
Cornelis M. I. Niels Van Der Linden ◽  
Bruno Silva

AbstractPurpose. The aim of the study was to examine the influence of small-sided and conditioned games (SSG) on the internal load (heart rate [HR] and perceived exertion), external load (Global Positioning System variables), and lower limb power (squat jump [SJ] and countermovement jump [CMJ]).Methods. Six collegiate male soccer players (age 20.3 ± 4.8 years; maximal oxygen uptake 42.9 ± 2.7 ml/kg/min; maximal HR 184.7 bpm) performed three 2-min bouts of 1 vs. 1 and two 3-min bouts of 3 vs. 3 format with a work-to-rest ratio of 1:1.5. Two-way ANOVA with repeated measures tested the effects of bouts and SSG formats on the internal and external load and on the lower limb power.Results. The 3Conclusions. Physiological and physical responses varied during bouts. Nevertheless, small differences between SSG formats were found. SSG bouts did not have significant impact on the lower limb power.


2020 ◽  
Vol 72 (1) ◽  
pp. 253-263 ◽  
Author(s):  
Manuel Ortega-Becerra ◽  
Alexis Belloso-Vergara ◽  
Fernando Pareja-Blanco

AbstractThis study aimed to describe the physical and physiological demands of adolescent handball players and compare movement analysis and exercise intensities between the first and second halves and between the different periods of the match. Fourteen adolescent handball players (age 15.7 ± 0.8 years, body mass: 65.6 ± 3.4 kg, body height: 169.5 ± 3.9 cm), played two friendly matches, in which no substitutions were made. The analysis was carried out with a Global Positioning System technology. The following physical variables were analyzed: Total distance covered (TD); distance covered at faster velocities than 18 km·h-1 (TDC>18km·h-1); number of accelerations (Accel) and decelerations (Decel); number of accelerations and decelerations higher than 2.78 m·s-2 (Accel>2.78 m·s-2 and Decel>2.78 m·s-2); number of sprints (Sprints); accelerations interspersed with a maximum of 30 s between them (RAS≤30s) and as a physiological variable the heart rate (HR) was examined. Significant differences (p < 0.01 –p < 0.001) between the first and the second half in all variables mentioned were observed, except in Accel>2.78 m·s-2 and Decel>2.78 m·s-2. This trend was also observed when comparing performance between the different 10-min periods. The 5th period (period 40-50 min) was the one that showed differences with respect to the previous ones. Adolescent handball players showed lower levels of exercise intensity, assessed by both time-motion and HR data, in the second half of matches, especially in the middle of this period.


Sports ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 139
Author(s):  
Toni Modric ◽  
Mario Jelicic ◽  
Damir Sekulic

Previous studies examined training/match ratios (TMr) to determine the training load relative to the match load, but the influence of the relative training load (RTL) on success in soccer is still unknown. Therefore, this study aimed to investigate the possible influence of RTL on final match outcome in soccer (win, draw, and loss). Running performances (RP) of soccer players (n = 21) in the Croatian highest national soccer competition were analyzed during the season 2020–2021. Data were measured by the global positioning system in 14 official matches and 67 training sessions. RTL was assessed by TMr, which were calculated as the ratio of RP during training and match in the same week, evaluating the following measures: TDr (total distance ratio), LIDr (low-intensity distance ratio), RDr (running distance ratio), HIDr (high-intensity distance ratio), ACCr (total accelerations ratio), DECr (total decelerations ratio), HI-ACCr (high-intensity accelerations ratio), HI-DECr (high-intensity decelerations ratio). All TMr were examined separately for each training session within in-season microcycles (categorized as days before the match day, i.e., MD minus). Spearman correlations were used to identify association between match outcome and TMr. The results indicated negative associations between match outcome and TDr, LIDr, ACCr and DECr on MD-1 and MD-2). In contrast, positive associations were evidenced between match outcome, and HIDr on MD-3 and TDr, LIDr, ACCr and DECr on MD-5 (p < 0.05; all moderate correlations). These findings demonstrate that final match outcome in soccer was associated with greater RTL of (i) high-intensity running three days before the match, (ii) total and low-intensity running, accelerations and decelerations five days before the match, and (iii) lower RTL of total and low-intensity running, accelerations and decelerations one and two days before the match.


2021 ◽  
Vol 30 (1) ◽  
pp. 105-111
Author(s):  
Adam Jones ◽  
Chris Brogden ◽  
Richard Page ◽  
Ben Langley ◽  
Matt Greig

Context: Contemporary synthetic playing surfaces have been associated with an increased risk of ankle injury in the various types of football. Triaxial accelerometers facilitate in vivo assessment of planar mechanical loading on the player. Objective: To quantify the influence of playing surface on the PlayerLoad elicited during footwork and plyometric drills focused on the mechanism of ankle injury. Design: Repeated-measures, field-based design. Setting: Regulation soccer pitches. Participants: A total of 15 amateur soccer players (22.1 [2.4] y), injury free with ≥6 years competitive experience. Interventions: Each player completed a test battery comprising 3 footwork drills (anterior, lateral, and diagonal) and 4 plyometric drills (anterior hop, inversion hop, eversion hop, and diagonal hop) on natural turf (NT), third-generation artificial turf (3G), and AstroTurf. Global positioning system sensors were located at C7 and the mid-tibia of each leg to measure triaxial acceleration (100 Hz). Main Outcome Measures: PlayerLoad in each axial plane was calculated for each drill on each surface and at each global positioning system location. Results: Analysis of variance revealed a significant main effect for sensor location in all drills, with PlayerLoad higher at mid-tibia than at C7 in all movement planes. AstroTurf elicited significantly higher PlayerLoad in the mediolateral and anteroposterior planes, with typically no difference between NT and 3G. In isolated inversion and eversion hopping trials, the 3G surface also elicited lower PlayerLoad than NT. Conclusions: PlayerLoad magnitude was sensitive to unit placement, advocating measurement with greater anatomical relevance when using microelectromechanical systems technology to monitor training or rehabilitation load. AstroTurf elicited higher PlayerLoad across all planes and drills and should be avoided for rehabilitative purposes, whereas 3G elicited a similar mechanical response to NT.


2017 ◽  
Vol 12 (6) ◽  
pp. 749-755 ◽  
Author(s):  
Nick B. Murray ◽  
Tim J. Gabbett ◽  
Andrew D. Townshend

Objectives:To investigate the relationship between the proportion of preseason training sessions completed and load and injury during the ensuing Australian Football League season.Design:Single-cohort, observational study.Methods:Forty-six elite male Australian football players from 1 club participated. Players were divided into 3 equal groups based on the amount of preseason training completed (high [HTL], >85% sessions completed; medium [MTL], 50–85% sessions completed; and low [LTL], <50% sessions completed). Global positioning system (GPS) technology was used to record training and game loads, with all injuries recorded and classified by club medical staff. Differences between groups were analyzed using a 2-way (group × training/competition phase) repeated-measures ANOVA, along with magnitude-based inferences. Injury incidence was expressed as injuries per 1000 h.Results:The HTL and MTL groups completed a greater proportion of in-season training sessions (81.1% and 74.2%) and matches (76.7% and 76.1%) than the LTL (56.9% and 52.7%) group. Total distance and player load were significantly greater during the first half of the in-season period for the HTL (P = .03, ES = 0.88) and MTL (P = .02, ES = 0.93) groups than the LTL group. The relative risk of injury for the LTL group (26.8/1000 h) was 1.9 times greater than that for the HTL group (14.2/1000 h) (χ2 = 3.48, df = 2, P = .17).Conclusions:Completing a greater proportion of preseason training resulted in higher training loads and greater participation in training and competition during the competitive phase of the season.


10.17159/5053 ◽  
2018 ◽  
Vol 30 (1) ◽  
pp. 1-6
Author(s):  
Z Webster

on the improvement of skills during training sessions. However, there is a certain level of physical effort required to execute these skills optimally which tend to get little focused attention during training. This could lead to players being physically unprepared for the demands of a match. Objective: The purpose of this study was to assess and compare the physical demands of a one-day cricket game and a training session of provincial cricket players, using GPS units. Methods:The study employed a quantitative design as it essentially collected numerical data from GPS units to describe and analyze the physical demands of ODGs and cricket training sessions preceding these games.   Results:There were significant differences across all sub-disciplines and movement categories during training and ODGs for provincial cricket players.


Kinesiology ◽  
2016 ◽  
Vol 48 (2) ◽  
pp. 213-222
Author(s):  
Matteo Corvino ◽  
Dinko Vuleta ◽  
Marko Šibila

The aim of the present study was to analyse load to which players were exposed to and effort they invested in 4vs4 small-sided handball games in relation to various court dimensions. Eight male amateur handball players participated in three eight-minute 4vs4 (plus goalkeepers) small-sided handball games. The three court dimensions were 12×24 m, 30×15 m and 32×16 m. Using Global Positioning System devices (SPI pro elite 15hz, GPSports), time-motion video analysis, and Borg’s scale for rating of perceived exertion (RPE), the following performance, physiological and psychological parameters were recorded: cyclic movements for distance covered, acyclic movements for the number of technical actions executed, heart rate, and RPE. Total distance travelled increased with the increase in court size (948.1±64.5, 1087.2±92.0 and 1079.8±90.6 on the 24×12 m, 30×15 m and 32×16 m court, respectively; p&lt;.05). Distance covered by the players in four speed zones revealed the substantial difference between the games played on the 24×12 and 30×15m court in the first and third (p&lt;.05; moderate ES) speed zone. On the 24×12 m court players covered more distance while moving in the first speed zone, but less distance when moving in the third speed zone (p&lt;.05; moderate ES). On the 32×16 m court the players covered less distance while moving in the first speed zone, but they covered more distance by moving in the third speed zone (p&lt;.05; moderate ES). There were no substantial differences found for the second and fourth speed zone cyclic movements and distances covered on all the three experimental court sizes. No statistical differences between the games played on various court dimensions were found in acyclic movements. No statistical differences were found in the analysis of heart rate. Further analysis of players’ self-evaluated effort confirmed the trend of heart rate values, showing no statistical differences in the RPE values among the three different court dimensions. Our findings indicate that changing court dimensions during 4vs4 small-sided handball games could influence load imposed on the players and their exertion.


2014 ◽  
Vol 9 (4) ◽  
pp. 680-688 ◽  
Author(s):  
Tim J. Gabbett

Purpose:A limitation of most rugby league time–motion studies is that researchers have examined the demands of single teams, with no investigations of all teams in an entire competition. This study investigated the activity profiles and technical and tactical performances of successful and less-successful teams throughout an entire rugby league competition.Methods:In total, 185 rugby league players representing 11 teams from a semiprofessional competition participated in this study. Global positioning system analysis was completed across the entire season. Video footage from individual matches was also coded via notational analysis for technical and tactical performance of teams.Results:Trivial to small differences were found among Top 4, Middle 4, and Bottom 4 teams for absolute and relative total distances covered and distances covered at low speeds. Small, nonsignificant differences (P = .054, ES = 0.31) were found between groups for the distance covered sprinting, with Top 4 teams covering greater sprinting distances than Bottom 4 teams. Top 4 teams made more meters in attack and conceded fewer meters in defense than Bottom 4 teams. Bottom 4 teams had a greater percentage of slow play-the-balls in defense than Top 4 teams (74.8% ± 7.3% vs 67.2% ± 8.3%). Middle 4 teams showed the greatest reduction in high-speed running from the first to the second half (–20.4%), while Bottom 4 teams completed 14.3% more high-speed running in the second half than in the first half.Conclusion:These findings demonstrate that a combination of activity profiles and technical and tactical performance are associated with playing success in semiprofessional rugby league players.


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