An Extensive Comparative Analysis of Successful and Unsuccessful Football Teams in LaLiga

Technical and tactical evolution of the offensive team sequences in LaLiga between 2008 and 2021. Is Spanish football now a more associative game?

The aim of this investigation was to study the technical and tactical evolution of the offensive team sequences in the Spanish football teams from 2008/09 to 2020/21. A comparative analysis including twelve variables related to the development of offensive sequences in 4940 matches was performed from 2008/09 to 2020/21 seasons of the Spanish professional football league (LaLiga). All match observations were recorded using a validated video tracking system. Multilevel linear mixed models were used to examine the differences across seasons, considering the effects of contextual variables. The number of passes per sequence (2.4 [CI: 2.2-2.5] vs 3.2 [CI: 3.0-3.4]; +33.3%), the passing accuracy (72.1 [CI: 70.6-73.5] vs 76.9 [CI: 75.4-78.3]%; +6.8%) and the average duration of the team sequences (6.4 [CI: 5.9-6.8] vs 8.3 [CI: 7.8-8.7] seconds; +25.76%) showed a small increasing trend over the seasons (P < 0.05). In contrast, variables such as the direct speed of progression (2.2 [CI: 2.1-2.3] vs 1.6 [CI: 1.5-1.7] metres/second; -24.5%), key passes (8.1 [CI: 7.6-8.5] vs 6.8 [CI: 6.3-7.2]; -15.8%), and the sequences that ended in the attacking third (64.8 [CI: 62,7-66.8] vs 57.1 [CI: 55.1-59.2]; -11.7%) or in a shot (13.0 [CI: 12.4-13.6] vs 10.2 [CI: 9.6-10.8]; -21.6%) showed a small decreasing trend from 2008/09 to 2020/21 (P < 0.05). Spanish professional football teams slightly evolved technically and tactically towards a more associative style of play that includes longer passing sequences. This evolution also involved a decreasing speed of progression and fewer technical actions such as through balls, key passes and shots.

Are EFI data valuable? Evidence from the 2022 FIFA World Cup group stage

The 2022 World Cup used new Enhanced Football Intelligence (EFI) data, stoppage time calculation methods and substitution rules that were introduced by FIFA. The aim of this study is to explore the effectiveness of EFI in match analysis and to identify the key indicators that influence the match and provide a reference for coaches' tactical design and training. Data were derived from the FIFA website, including EFI data for 48 matches at the group stage of the Qatar World Cup. A total of 46 indicators were used for analysis and the average values of the corresponding indicators for the different competition results were used in the analysis to identify the key index that determines the outcome of the competition. Apart from scoring more goals and having more assists, winning teams had significantly more attempts on target than drawing and losing teams (p < 0.05); Winning teams had significantly more attempts inside the penalty area, completed defensive line breaks and receptions behind the defensive line than losing teams (p < 0.05). There is no difference in possession between matches with different results (p > 0.05). Goals were significantly correlated with completed defensive line breaks and receptions behind the defensive line (r = 0.27-0.30, p < 0.01). Attempts on target was significantly positively correlated with receptions, final third entries and line breaks (r = 0.31-0.67, p < 0.01) and negatively correlated with defensive pressures applied (r = -0.35, p < 0.01). The efficiency of the offense is more important. Teams need to have more receptions, final third entries and line breaks to get more shots on target rather than possession. This study may help coaches to interpret the game from a multi-dimensional perspective and coaches can use EFI to help their teams improve their match performance.

Differences in playing style and technical performance according to the team ranking in the Spanish football LaLiga. A thirteen seasons study

This study aimed to explore the differences in playing style and technical performance according to the ranking level in Spanish football teams. The sample comprised 38 professional teams that competed in LaLiga from 2008/09 to 2020/21, with a total of 4940 matches. The teams were grouped by their final ranking position: Champion (1st); Champions League (2nd-4th); Europa League (5th-6th); middle teams (7th-17th); and relegated teams (18th-20th). Linear mixed models were used to examine the effects of the team ranking on variables related to playing style and technical performance. The F2 statistic was calculated as effect size (ES). Regarding the style of play, the Champion teams initiated offensive sequences from a more advanced field position than the remaining ranking groups with a descending effect as the ranking position decreased (p < 0.001; ES = medium). The sequence duration and passes per sequence showed a decreasing effect across ranking groups (both p < 0.001; ES = small). In contrast, the direct speed showed an increasing effect as the ranking position decreased (p < 0.001; ES = small). A decreasing effect was observed in the number of sequences ending in the final third as the ranking position decreased (p < 0.001; ES = large) while no effect was found for the sequences ending in a shot. There was a reduction effect in ball possession, passing accuracy, through balls and crosses as the teams' ranking decreased (all p < 0.001; ES = small-to-large). In summary, higher-ranked teams had an advanced starting position, longer offensive sequences, slower progression speed, more ball possession, higher passing accuracy, and more crosses and through balls than lower-ranked teams. Football coaches should consider that adopting a playing style focused on regaining the ball possession in advanced field zones and using long passing sequences can be an effective tactical strategy to improve the teams' ranking during the season.

Social Network Analysis: Mathematical Models for Understanding Professional Football in Game Critical Moments—An Exploratory Study

Considering the Social Network Analysis approach and based on the creation of mathematical models, the aim of this study is to analyze the players’ interactions of professional football teams in critical moments of the game. The sample consists in the analysis of a 2019/2020 season UEFA Champions League match. The mathematical models adopted in the analysis of the players (micro analysis) and the game (macro analysis) were obtained through the uPATO software. The results of the networks indicated a performance pattern trend more robust in terms of the mathematical model: Network Density. As far as it concerned, we found that the Centroid Players had a decisive role in the level of connectivity and interaction of the team. Regarding the main critical moments of the game, the results showed that these were preceded by periods of great instability, obtaining a differentiated performance in the following mathematical models: Centrality, Degree Centrality, Closeness Centrality, and Degree Prestige. We concluded that the networks approach, in concomitance with the dynamic properties of mathematical models, and the critical moments of the game, can help coaches to better evaluate the level of interaction and connectivity of their players toward the actions imposed by opponents.

The relationship between running distance and coaches' perception of team performance in professional soccer player during multiple seasons

This study analyzed how the physical movement profile of soccer matches evolved throughout a season by assessing the variability of different metrics depending on the season phase. In addition, the evolution of running distances was investigated in the relation to the team performance based on the coaches’ perception. Games from four consecutives Spanish LaLiga seasons (n = 1520) were recorded using an optical tracking system (i.e., ChyronHego). Total distance (TD), distance covered between 14 and 21 km h⁻¹ (MIRD), 21–24 km h⁻¹ (HIRD), and > 24 km h⁻¹ (VHIRD) were analyzed, as well as the number of efforts between 21 and 24 km h⁻¹ (Sp21) and > 24 km h⁻¹ (Sp24). Seasons were divided into four phases (P): P1 (matches 1–10), P2 (11–19), P3 (20–29), and P4 (30–38). Linear mixed models revealed that soccer players covered significantly greater distances and completed a higher number of sprints in P2 and P3. Also, team performance evaluated by soccer coaches was positively related to TD, HIRD, VHIRD and Sp21 in P1. A negative relationship was observed between team performance and distance covered at speeds below 21 km h⁻¹ in P2 and P3. Team performance was negatively related to TD, MIRD, and HIRD, and Sp21 in P4. As conclusion, the team performance perceived by coaches is related to the movement profile throughout a season, and it significantly influences the evolution of soccer players’ movement profiles. Specifically, it seems that the players of the best teams have the best physical performance at the beginning of the season with respect to the rest of the phases.

Influence of contextual factors on physical demands and technical-tactical actions regarding playing position in professional soccer players

Background

The aim of this study was to analyse the physical demands and technical-tactical actions for each playing position according to game location and final outcome in professional soccer players.

Methods

A convenience sample was obtained from twenty-one professional male soccer players, belonged to same soccer team of the Spanish Second Division. Players’ physical demands were monitored during each match using a portable 18 Hz GPS unit and 600 Hz triaxial accelerometer. These analysed demands were total distance, moderate speed running distance (>14.4 km·h^-1), high-speed running distance (>19.8. km·h-1), sprint distance (>25.0 km·h^-1), number of accelerations between 2 and 4 m·s^-2 and above 4 m·s^-2, and number of decelerations between 2 and 4 m·s^-2 and above 4 m·s^-2. The data related to technical-tactical actions were obtained from WyScout®, a computerized multiple-camera tracking system based on the OPTA® track analysis tool. The obtained indicators were general, defensive and offensive.

Results

For all players, higher total distance (p = 0.045; effect size [ES] = 0.24, small effect) was covered and greater deceleration 2-4 m·ss^-2 (p = 0.001; ES = 0.68, medium effect) was performed when the team plays at home and lose and for all players, playing at home and winning demanded higher defensive volume (p =0.014; ES = − 1.49, large effect) and nº interceptions (p =0.031; ES = − 1.40, large effect) in comparison to playing at home and losing.

Conclusions

The physical demands and technical-tactical actions vary when contextual game factors (i.e., match location and final outcome) are considered. We can confirm that, although the training of physical demands does not influence the final result of the match, the training of technical tactical actions could help to achieve an optimal performance of the team to win matches.

Association between offensive and defensive playing style variables and ranking position in a national football league

The aim of this study was to determine the association of playing style and efficacy variables with football success in a professional football league. Match statistics were obtained from 23 football teams competing in the 2017-2018 and 2018-2019 seasons of the Spanish national league(LaLiga). Offensive and defensive playing style and efficacy variables were calculated. Pearson's correlation coefficient tests and principal component analysis (PCA) were applied to establish the influence of these variables on the number of points obtained at the end of the season and on the ranking position. In isolation, the efficacy of completion showed the highest association with ranking points and position. A two-dimension PCA explained 77.8% of the variance in the ranking position. In dimension-1 (58.5%), game initiative and attack building, and in dimension-2 (19.3%), efficacy of defensive containment and a lower rate of long passes were within the variables that explained more variance in the ranking position. Success in football, measured by ranking position at the end of the Spanish national league, was associated with several playing style and efficacy variables. Overall, a dominant game style with high efficacy to finish attacking plays, and an offensive game initiative, are most associated with successful football.

Success Factors in the FIFA 2018 World Cup in Russia and FIFA 2014 World Cup in Brazil

Research on success factors in football focusing on national teams is sparse. The current study examines the success factors during the World Cup 2018 in Russia and the World Cup 2014 in Brazil. A total of 128 matches were analyzed using a generalized order logit approach. Twenty-nine variables were identified from previous research. The results showed that defensive errors (p = 0.0220), goal efficiency (p = 0.0000), duel success (p = 0.0000), tackles success (p = 0.0100), shots from counterattacks (p = 0.0460), clearances (p = 0.0130), and crosses (p = 0.0160) have a significant influence on winning a match during those tournaments. Ball possession, distance, and market value of the teams had no influence on success. Overall, most of the critical success factors and those with the highest impact on winning close games were defensive actions. Moreover, the results suggest that direct play and pressing were more effective than ball possession play. The study contributes to a better understanding of success factors and can help to improve effectiveness of training, match preparation, and coaching.

Influence of Players' Maximum Running Speed on the Team's Ranking Position at the End of the Spanish LaLiga

The maximum running speed that a football player can attain during match play has become one of the most popular variables to assess a player's physical talent. However, the influence of a player's maximum running speed on football performance has not yet been properly investigated. The aim of this study was to determine the influence of a player's peak/maximum running speed on the team's ranking position at the end of a national league. A second aim was to investigate differences in maximum running speed among playing positions. To fulfil this aim, the peak/maximum running speeds of 475 male professional football players were recorded for 38 fixtures of the Spanish first-division league (LaLiga) from the 2017-2018 season (7838 data points). Players' peak running speeds in each match were assessed with a validated multicamera tracking system and associated software (Mediacoach®). Players' maximum running speed was established as the fastest running speed they attained during the entire season. Most players (53.5% of the total) had a maximum running speed in the range of 32.0-33.9 km/h, with only three players (0.6%) with a maximum running speed of over 35.0 km/h. Overall, forwards were faster than defenders and both types of players were faster than midfielders (33.03 ± 1.35 > 32.72 ± 1.32 > 32.08 ± 1.63 km/h; p < 0.001). There was no association between teams' maximum running speed and ranking position at the end of the league (r = -0.356, p = 0.135). The correlations between teams' maximum speeds and ranking position were low for defenders (r = -0.334, p = 0.163), midfielders (r = 0.125, p = 0.610), and forwards (r = -0.065, p = 0.791). As a result, the variance in the ranking position at the end of the season explained by a team's maximum speed was of only 7.5%. Finally, as an average for all teams, players' peak running speeds remained stable at ~30.7 ± 0.6 km/h throughout the whole season. These results suggest that successful and less successful football teams have squads with players able to obtain similar maximum running speeds during match play throughout the season. Hence, players' maximum running speeds have a poor association with the team's ranking position at the end of the Spanish professional national league.