An eight-season analysis of the teams' performance in the Spanish LaLiga according to the final league ranking.

This study aimed to analyse the performance of 5,518 collective observations of the Spanish LaLiga teams for eight consecutive seasons (from 2011-12 to 2018-19), considering the final league ranking. The teams were divided into four groups: Europe (from 1st to 6th), Upper-Middle (from 7th to 11th), Lower-Middle (from 12th to 17th) and Relegation (from 18th to 20th). The variables recorded were: Passes, Successful Passes, Crosses, Shots, Goals, Corners, Fouls, Width, Length, Height, distance from the goalkeeper to the nearest defender (GkDef), total distance covered (TD) and number of points accumulated. The main results were that: 1) Europe, being superior to the rest of the groups, showed lower values of Length from 2015-16, and lower values of GkDef from 2014-15; 2) Upper-Middle showed lower values of Length from 2015-16; 3) Lower-Middle showed fewer Shots from 2013-14, and lower values of Length, GkDef and TD from 2014-15; and, 4) Relegation barely showed significant differences between seasons in any variable. The study concludes that the teams of the Europe, Upper-Middle and Relegation groups showed quite stable performance, while the teams of the Lower-Middle group presented a worsening in different dimensions as the seasons progressed. The information provided in this study makes it possible to have reference values that have characterized the performance of the teams for each group.

The impact of COVID-19 lockdown on soccer positional and physical demands in the Spanish La Liga.

The present study aimed to analyse the playing surface area, dispersion and distance covered of professional football teams comparing the pre-lockdown and post-lockdown periods. Positional and match physical demands data were collected from all matches played in the First Spanish Division (n = 760) during season 2019/2020. Pre-lockdown (1st-27th matchday) and post-lockdown periods (28th-38th matchday) were compared. Variables related to team-level spatial (i.e., convex hull, team width and team length) and physical performance (i.e., total distance and high-speed running distance) were analysed using an optical tracking system (i.e., ChyronHego). In addition, these variables were concerned with respect to the match location contextual variable. Linear mixed models were used to examine the difference between the pre-lockdown and post-lockdown periods following a hierarchical structure considering players, matches and teams. The results revealed that the pandemic lockdown affected the teams' performance when comparing the periods before and after lockdown, showing a general decrease in the average values of the spatial and physical variables measured. The current data could assist practitioners in making informed decisions in order to design and improve training plans for similar situations in which teams return to competition after an unusual period with no training.

Analysis of Playing Area Dimensions in Spanish Professional Soccer: Extrapolation to the Design of Small-Sided Games With Tactical Applications.

ABSTRACT: Caro, O, Zubillaga, A, Fradua, L, and Fernandez-Navarro, J. Analysis of playing area dimensions in Spanish professional soccer: Extrapolation to the design of small-sided games with tactical applications. J Strength Cond Res 35(10): 2795-2801, 2021-The aims of this study were to examine (a) the width and length dimensions of the playing area in 4v4 situations during competition, (b) the influence of the pitch zone where the ball is on 4v4 dimensions, and (c) the influence of match status on the dimensions of 4v4 situations. Data were collected from 25 matches from the Spanish La Liga of the 2007-2008 season using the Amisco system. Length, width, and individual playing area (IPA) of the rectangle that included the nearest 4 players to the ball from each team were collected in a total of 8,727 4v4 game situations. The pitch zone and match status were also considered for these 4v4 situations. To determine factors that affect 4v4 game situations, 1-way analysis of variance was used. The influence of the pitch zone where 4v4 situations took place showed significant differences (p < 0.001) between the zones where different principles of the game apply. The areas of the 4v4 situations ranged from 14.70 ± 4.69 × 17.18 ± 6 to 17.09 ± 5.16 × 20.34 ± 5.93 m, and the IPA of the 4v4 playing rectangle ranged from 46.33 ± 20 to 35.48 ± 16.95 m2, being larger in the central zones of the pitch. The length of the 4v4 rectangle showed a significant reduction in the closer zones to the goal. Match status did not affect the dimensions of these 4v4 game situations significantly. The findings of this study suggest that the size of 4v4 situations proposed for training should be designed according to the pitch zone where playing actions take place.

Tactical Variables Related to Gaining the Ball in Advanced Zones of the Soccer Pitch: Analysis of Differences Among Elite Teams and the Effect of Contextual Variables.

Attacking tactical variables have been commonly studied in soccer to analyze teams' performance. However, few studies investigated defensive tactical variables during match-play and the influence of contextual variables on them. The aims of the present study were (1) to examine the defensive behaviors of soccer teams when gaining the ball in advanced zones of the pitch and (2) to evaluate the effect of contextual variables on these defensive behaviors. A sample of 1,095 defensive pieces of play initiated in the opposing half of the pitch obtained from 10 matches of the season 2010/11 of La Liga and involving 13 teams was collected using the semiautomated tracking system Amisco Pro. Five defensive tactical variables, the outcome of defensive pieces of play, and contextual variables (i.e., match status, venue, quality of opposition, and match period) were recorded for every defensive piece initiated in the opposing half of the pitch. Results showed that there were significant differences among teams in the outcome of defensive pieces of play originating from the opposing half (χ2 = 111.87, p < 0.01, φc = 0.22), and in the outcome of offensive pieces of play following ball gains (χ2 = 49.92, p < 0.001, φc = 0.22). Cluster analysis revealed four groups describing different defensive behaviors from high-pressure to a defense close to their own goal. Match status (χ2 = 25.87, p < 0.05, φc = 0.11) and quality of opposition (χ2 = 21.19, p < 0.05, φc = 0.10) were the contextual variables that showed a significant effect on defensive pieces of play initiated in the opposite half of the pitch. Teams winning gained more balls in the zone close to their own goal, and losing teams gained more balls in advanced zones of the pitch. Moreover, the greater the quality of the opponent the lesser the chance of gaining the ball in advanced zones of the pitch. Neither venue or match period influenced the defensive pieces of play analyzed. Soccer teams could employ a similar analysis to improve their performance and prepare for opposition teams in competition.

Attacking and defensive styles of play in soccer: analysis of Spanish and English elite teams.

The aim of this study was to define and categorise different styles of play in elite soccer and associated performance indicators by using factor analysis. Furthermore, the observed teams were categorised using all factor scores. Data were collected from 97 matches from the Spanish La Liga and the English Premier League from the seasons 2006-2007 and 2010-2011 using the Amisco® system. A total of 19 performance indicators, 14 describing aspects of attacking play and five describing aspects of defensive play, were included in the factor analysis. Six factors, representing 12 different styles of play (eight attacking and four defensive), had eigenvalues greater than 1 and explained 87.54% of the total variance. Direct and possession styles of play, defined by factor 1, were the most apparent styles. Factor analysis used the performance indicators to cluster each team's style of play. Findings showed that a team's style of play was defined by specific performance indicators and, consequently, teams can be classified to create a playing style profile. For practical implications, playing styles profiling can be used to compare different teams and prepare for opponents in competition. Moreover, teams could use specific training drills directed to improve their styles of play.