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On April 3, 2013, Ateme announced the availability of the first open source implementation of a HEVC software player based on the OpenHEVC decoder and GPAC video player which are both licensed under LGPL. The OpenHEVC decoder supports the Main profile of HEVC and can decode 1080p at 30 fps video using a single core CPU.[75] A live transcoder that supports HEVC and used in combination with the GPAC video player was shown at the ATEME booth at the NAB Show in April 2013.[75][76]
On September 5, 2014, the Blu-ray Disc Association announced that the 4K Blu-ray Disc specification would support HEVC-encoded 4K video at 60 fps, the Rec. 2020 color space, high dynamic range (PQ and HLG), and 10-bit color depth.[85][86] 4K Blu-ray Discs have a data rate of at least 50 Mbit/s and disc capacity up to 100 GB.[85][86] 4K Blu-ray Discs and players became available for purchase in 2015 or 2016.[85][86]
- Built-in support was removed in Windows 10 version 1709 due to licensing costs. The HEVC Video Extensions add-on can be purchased from the Microsoft Store to enable HEVC playback on the default media player app Microsoft Movies & TV.[110]
The study aims were to describe positional differences in the acceleration and sprint profiles of professional football players in match-play, and analyse start speeds required based on the intensity of accelerations and decelerations. This longitudinal study was conducted over thirteen competitive microcycles in a professional football team from LaLiga 123. Data were collected through electronic performance tracking systems. Every player was categorised based on the playing position: central defender (CD), full-back (FB), forward (FW), midfielder (MF), and wide midfielder (WMF). In respect of acceleration profile, positional differences were found for all variables (p < 0.05), except average magnitude of accelerations (ACCAVG, p = 0.56) and decelerations (DECAVG, p = 0.76). The sprint profile also showed positional differences for all variables (p < 0.05), apart from sprint duration (p = 0.07). In addition, although low-intensity accelerations required significantly greater start speeds (Vo) than high-intensity accelerations in WMF (0.4 ± 0.2 km/h; p < 0.05) and FW (0.4 ± 0.2 km/h; p < 0.05), no significant differences (p > 0.05) were found in CD, FB, and MF. However, high-intensity decelerations were performed at significantly higher Vo than low-intensity decelerations in MF (2.65 ± 0.1 km/h; p < 0.05), FW (3.3 ± 0.1 km/h; p < 0.05), FB (3.9 ± 0.4 km/h; p < 0.05), WMF (4.3 ± 0.3 km/h; p < 0.05), and CD (4.1 ± 0.7 km/h; p < 0.05). Therefore, positional differences exist for most variables of the acceleration and sprint profiles. In addition, different Vo were observed between high-intensity and low-intensity accelerations as well as high-intensity and low-intensity decelerations.
Citation: Oliva-Lozano JM, Fortes V, Krustrup P, Muyor JM (2020) Acceleration and sprint profiles of professional male football players in relation to playing position. PLoS ONE 15(8): e0236959.
During the past decade, there has been an increase in the literature related to athlete monitoring [1,2]. The large number of electronic performance tracking systems available on the market [2] has allowed a detailed understanding of football match demands, enabling coaches to achieve optimal training targets [1]. Football is a team sport that combines intermittent periods of high-intensity activity with longer periods of lower-intensity activity [3,4]. Professional football players cover around 10 km per match [3,5], but only 10% of the total distance is performed at high-intensity [3]. However, these high-intensity periods contribute in particular to neuromuscular fatigue, consequently increasing the risk of injury [6].
High-speed running actions, or sprints, are considered a prerequisite for successful performance in football [7,8]. In fact, sprinting skills are of prime importance in modern football [7,9]. For instance, straight sprints are the actions most frequently performed when scoring a goal [10], evading an opponent, and creating a shot on goal [11]. Thus, selection, testing, and physical conditioning of players should put emphasis on developing sprinting skills [8]. In addition, careful monitoring of these actions is necessary [9,12], taking into consideration different playing positions [13,14]. For example, a wide midfielder (WMF) may cover 294 ± 76 m of sprinting distance per match, whereas a central defender (CD) may cover 123 ± 48 m [13]. However, research on the sprint profile of professional football match-play has so far been limited [13], while different components of the sprint profile, such as sprint duration, start speed of each sprint or distance covered per sprint, have not yet been studied.
Some studies have tried to individualise (based on playing position) and contextualise both acceleration [13,15,20,22] and sprint profiles [7,13,14], but most studies have analysed these profiles separately. Also, little is known, for example, about the start speed required to perform a high-intensity acceleration or deceleration [23]. The aims of this study were therefore to: 1) describe the acceleration profile of players and compare it by playing position; 2) describe the sprint profile of players and compare it by playing position; and 3) analyse the start speed (Vo) required based on the intensity of the acceleration and deceleration by playing position. Regarding the first and second aims, we hypothesised that greater positional differences may be found, particularly, between defensive and offensive positions. When it comes to the third aim, we hypothesised that high intensity accelerations and decelerations would elicit greater start speeds than low intensity accelerations or decelerations.
The study was conducted over thirteen competitive microcycles in a professional football team from LaLiga 123. The team played one match per microcycle. The match location (home or away) alternated with each microcycle; seven matches were played away and six at home. The playing formation was 4-4-2 for all matches. Data were collected using wearable sensors (RealTrack Systems, Almería, Spain). In addition, every player was categorised based on their playing position: central defender (CD), full-back (FB), forward (FW), midfielder (MF), and wide midfielder (WMF).
The main purpose of this study was to describe the positional differences in the acceleration and sprint profiles of professional football players in match-play and to analyse the start speed (Vo) required based on the intensity of the acceleration and deceleration. This study showed positional differences for most variables of the acceleration and sprint profiles. Also, significant differences were observed in Vo when comparing high-intensity accelerations and high-intensity decelerations to low-intensity accelerations and low-intensity decelerations.
This study is the first to provide detailed information on the acceleration and sprint profiles of professional football players. Previous investigations [13,20,27] have described positional differences for some of the high-intensity profile variables examined in the present study but conclusions from most studies were limited because only a few variables, which are the most common in the literature, were analyzed. These studies have examined, for instance, professional Norwegian [13,20] and British [27] football teams, and found differences between playing positions for variables of the acceleration profile [13,20,27]. For example, WMF covered significantly greater ACCDIS (559 ± 232 m) and DECDIS (456 ± 107 m) than MF (ACCDIS: 559 ± 232 m; DECDIS 360 ± 120 m) [20]. Similarly, our study showed that WMF covered significantly greater ACCDIS (436.5 ± 86.3 m) and DECDIS (334.4 ± 74.5 m) than MF (ACCDIS: 260.7 ± 64.1 m; DECDIS 228.7 ± 54.5 m). The same study also found that FB was another position with greater ACCDIS covered (714 ± 298 m) than MF (559 ± 232 m) [20]. This suggests that playing in the lateral side of the pitch in addition to the offensive and defensive roles of FB let this position cover longer ACCDIS compared to central playing positions such as MF [28].
With regard to the frequency of the accelerations, another study clearly showed that the totals for ACCHIGH and DECHIGH were lower than for ACCLOW and DECLOW [29], which represent the nature of football as a sport that involves intermittent repeated periods of high-intensity activity [4] and thus, high neuromuscular fatigue may be developed [12]. In addition, our results support previous research reporting that WMF always performed a higher amount of ACCHIGH (35 ± 5 accelerations) and DECHIGH (62 ± 9 decelerations) than CD (ACCHIGH: 27 ± 7 accelerations; DECHIGH: 45 ± 8 decelerations) [27]. Consequently, the variable DIFFACDC also supports the same study, since the differences between playing positions were repeated once again and a higher number of DECHIGH than ACCHIGH was observed in all positions [27]. However, MF performed significantly greater ACCLOW and DECLOW than WMF (mean difference, ACCLOW: 62.1 ± 14.7 accelerations; DECLOW: 43.9 ± 13.9 decelerations) and FW (mean difference, ACCLOW: 54.1 ± 14.7 accelerations; DECLOW: 46.8 ± 13.9 decelerations) in our study, which may be explained by the fact that density increases (reduced area per player) as the ball is closer to the central zones of the pitch in match play [30]. Although WMF also had the highest DIFFACDC (-27 ± 4), this study reported that FW had the lowest DIFFACDC (-17 ± 4) [27]. Players, therefore decelerate at high-intensity more than they accelerate at high-intensity, so special focus on mechanical load indicators is recommended for strength and conditioning coaches [20]. When it comes to the magnitude of the accelerations and decelerations, the results cannot be compared to previous studies [31,32], since this is the first study to carry out this analysis in match-play. However, when analysing this variable in training contexts, differences between playing positions remained low for ACCMAX (0.17 ± 0.03 m/s2) and DECMAX (0.26 ± 0.03 m/s2) [32]. Consequently, this study supports the assertion that the acceleration profile is position-dependent and that different training strategies may be adopted to improve match performance and decrease risk of injury [12]. 2b1af7f3a8