Several studies have described the demands of football competition (Castellano et al., 2014; Di Salvo et al., 2007), serving as a benchmark for comparison with training demands (Owen et al., 2017; Stevens et al., 2017) or tasks within training (Beenham et al., 2017; Casamichana et al., 2012; Dellal et al., 2012; Gimenez et al., 2017). However, training tasks designed to replicate the average demands of matches will likely result in players being underprepared for the most demanding phases of football match-play (Gabbett et al., 2016).
The most demanding phases of the match have been studied using different methodologies. Dividing the match in to predefined periods of 15 minutes (Carling and Dupont, 2011) or 5 minutes (Bradley and Noakes, 2013; Di Mascio and Bradley, 2013) has shown higher activity peaks than the match average, with intensity being higher as the duration of the studied period decreased. For example, some players reached values of close to 140 m x [min.sup.-1] for distance covered and more than 40 m x [min.sup.-1] of distance covered at high speed in 5-minute periods (Bradley and Noakes, 2013). However, the most demanding passage of match-play may not fall completely within these pre-defined blocks. Therefore, these methods underestimate the most demanding passage of match-play (Varley et al., 2012).
Alternatively, a more practical and accurate approach would be to establish the most demanding passage of match-play using the rolling method (or moving average method). This procedure has been applied to Gaelic Football (Malone et al., 2017b), Rugby League (Delaney et al., 2016), Australian Football (Delaney et al., 2017a) and European football (Delaney et al., 2017b; Lacome et al., 2017). Delaney et al. (2017b) found differences between central defenders, wide midfielders, and forwards, with central defenders covering the least distance and the lowest metabolic power, while wide midfielders performed a greater number of accelerations and decelerations. High-speed running was greatest in forwards and wide midfielders (Delaney et al., 2017b).
Distance (m x [min.sup.-1]), distance covered at high speed (>5.5 m x [s.sup.-1]), average metabolic power, absolute values for acceleration and deceleration, and mechanical work have all been used to characterise the most demanding passages of play (Delaney et al., 2016; Delaney et al., 2017b; Lacome et al., 2017). The inclusion of variables that integrate the activity developed at high speed and accelerating/decelerating at high-intensity could be of interest to configure these periods. In this sense, high metabolic load distance (HMLD) is of interest, since it represents the distance covered (m) by a player when their metabolic power (energy consumption per kilogram per second) is above the value of 25.5 W x [kg.sup.-1] (Tierney et al., 2016). This value of 25.5 corresponds to when a player is running at a constant speed of 5.5 m x [s.sup.-1] on grass or when they are performing significant acceleration or deceleration activity (e.g. if they are accelerating from 2 to 4 m x [s.sup.2] over 1 second).
To date, most football research has only quantified isolated activity variables. However, an understanding of other activities occurring within the most demanding passages of play is also important. In football the activity of the player is multidirectional, multidimensional and iterative. Consequently, a detailed description of the activity performed by players during these most demanding passage of match-play would be of interest to managers, fitness coaches and team medical staff. For example, two players could obtain the same average metabolic power (AMP; W x [kg.sup.-1]) values over a given period of time, but the activity performed by the players could be vastly different (in one case, high intensity actions could be the result of greater high speed distance, and in another case the high intensity actions could be due to a higher number of accelerations or decelerations).
This information has significant practical application for the prescription of training, since it can serve as a benchmark when designing and evaluating the demands of the training tasks that are imposed on football players. Therefore, the purpose of this research was to identify the most demanding passage of match-play in football competition describing these periods through different variables, and determine the differences among positions through different criterion variables, and in different moving average durations.
An observational, retrospective cohort study was conducted during the 2015-2016 competitive season. Global positioning system (GPS) files were collected from a professional male soccer team during match-play. Position-specific activities for the most demanding passage of match-play were established using different criterion variables, and in different moving average durations.
Twenty-three professional football players (age: 20 [+ or -] 2 yr, mass: 70.2 [+ or -] 6.3 kg and stature: 1.78 [+ or -] 0.06 m) from the same Spanish 2nd B division team volunteered for this study. Data was collected throughout 37 competitive matches of the 2015-2016 competitive season (13 wins, 15 losses, 9 draw, final position 11th). A total of 605 individual global positioning system (GPS) files from match data of a professional male soccer team were collected. Each match was 90 min in duration, separated into two 45-min halves. Players were grouped according to their playing position, as central defenders (CD: n = 3; 95 GpS files), full backs (FB: n = 5; GPS 139 files), midfielders (MF: n = 3; GPS 101 files), wide midfielders (WMF: n = 5; GPS 110 files) and forwards (FW: n = 7; GPS 160 files). The mean ([+ or -] SD) number of observations per player was 26.3 [+ or -] 12.4. A typical training week consisted of 5 field sessions. The training week typically used the following schedule: session +1: recovery from the previous game for the players who competed for more than 60 minutes and compensatory session for the players who competed less than 60 minutes in the game; session -4: strength oriented training session with SSG in reduced space; session -3: training oriented towards endurance development/maintenance; session -2: training with tasks with tactical-technical objective; and session -1: activation drills replicating the tactical profile of competition, with low conditioning load and some set piece drills. These data arose from the daily player monitoring in which player activities were routinely measured over the course of the season, thus no authorization was required from an institutional ethics committee (Lacome et al., 2017). Data arose as a condition of the players' employment whereby they were assessed daily. Nevertheless, this study conformed to the Declaration of Helsinki and players provided informed consent before participating.
The STATSports software (Version 1.2) was then used for the computation of a moving average over each criterion variable (distance, HMLD and AMP), using four different durations (1', 3', 5' and 10'), and the maximum value for each duration was recorded. As a result, for each match, maximum values using three criterion variables were calculated for each of the 4 moving average durations. These four different durations were analysed because they correspond to the usual duration of the training drills in the team studied. Descriptive statistics and analysis were then calculated based on positions of play. These data were then averaged across all observations per position for between-group analysis.
The variables recorded were the distance covered per minute in competition (m x [min.sup.-1]), distance covered at high speed (HSR; >5.5 m x [s.sup.-1], m x [min.sup.-1]), distance covered at sprint (SPR; >7.0 m x [s.sup.-1], m x [min.sup.-1]), the number of high-intensity accelerations (ACC; >3 m x [s.sup.2], n x [min.sup.-1]), the number of high-intensity decelerations (DEC; 25.5 W x [kg.sup.-1], n x...