26 Jun LALIGA’s new tactical synchrony model: how it interpreted the latest FC Barcelona – Real Madrid ElClásico
At LALIGA, we regularly publish research that meets the highest scientific standards—both in methodology and in rigorous data treatment. However, we also recognize something essential: coaches need translations. Translations that bridge science and practice. That turn complex models into useful tactical tools. That convert graphs into smart, pitch-side questions.
That’s the purpose of this analysis. Today, we present a positional analysis model based on team tactical synchrony. And we apply it to a specific case: the most recent ElClásico (Matchday 35 of LALIGA EA SPORTS 2024/25).
What does this model measure?
This model uses a longitudinal graph to represent the behavior of both teams’ blocks during effective game time. It shows:
- Each team’s block depth in every live sequence (from the deepest outfield player to the most advanced, excluding the goalkeeper).
- The team’s average position (centroid).
- The spatial overlap between both blocks, highlighting compressed or dominant phases.
- And, crucially, the relationship between these dynamics and the scoreline, allowing tactical impact of each goal to be read.
The model is enhanced with two synchronized video views: tactical camera with real-image graphic overlays, and 2D radar view including analyses of width, depth, line distances, and convex hulls in the central zone. This allows visual validation of the graph and extends analysis to aspects such as:
- Defensive line positioning.
- Real tactical width in attack and defense.
- Occupation of the opposition’s penalty area.
- Goalkeeper’s distance to goal line and last defender.
What did ElClásico reveal?
The match’s tactical synchrony reveals two clearly distinct phases:
- Real Madrid’s explosive start (minutes 0–9): Two early goals and a favorable scoreline—but without positional dominance. Madrid’s block stays in mid-zone and even drops deeper after the 0–2. The model shows no lasting presence in the opponent’s half despite the lead. What does this mean? That the approach remained reactive rather than expansive.
- FC Barcelona’s positional dominance (minutes 10–45): The graph shows Barça’s block stepping forward, sustaining presence in advanced zones, and repeatedly entering Madrid’s area. This positional superiority converts into three goals (19’, 32’, 34’), plus another just before half-time (45’). The post-match report confirms this visually backed dominance, noting that Barça had 10 shots inside the box in the first half versus only 2 for Madrid.
After the break, Madrid cautiously pushes its lines forward (up to the 70’ mark), eventually scoring to make it 4–3. But in the final 20 minutes, Barça reasserts control through positional structure. The model shows their block regaining height, while Madrid struggles to settle in advanced zones. Barça’s positional attacks increase again in this stretch, as do their advanced possession zones and player count beyond the ball, which is also confirmed by video overlays.
How can this model help you as a coach?
- Can you tell when your team is sitting deep by design… or because it can’t get out?
- Can you spot whether your team’s presence in the opponent’s half is structural… or just momentary?
- Do you really know how often your team gets into the opposition’s box, beyond possession or shot stats?
This model doesn’t just give answers. More importantly, it triggers the kind of questions every coaching staff should be asking. Because it shows:
- Where the match is being played and for how long.
- Which team manages to structure itself in the opponent’s half.
- How blocks evolve after a goal, a substitution, or a momentum shift.
- How often the opposition area is truly occupied—based on real positioning, not isolated stats.
Plan smarter. Adjust faster. Read the game better.
With tools like this, training sessions can respond to what actually happened. Was there a failure to establish presence in the opposition half? Was the defense set too deep? Did line synchrony break down? Was there a structural collapse after conceding? Now, you can answer—with data and video.
ElClásico wasn’t just won or lost. It was played, occupied, structured. And this time, it was measured.
Scientific basis
The model described here builds on metrics widely supported in academic literature. Studies have applied centroid and convex hull measures to track how teams adapt structurally throughout a match, particularly after scoring or conceding. These metrics help distinguish between reactive retreats and organized tactical blocks, offering a robust base for match interpretation.
Key references:
- Bartlett, R., Button, C., Robins, M., Dutt-Mazumder, A., & Kennedy, G. (2012). Analysing team coordination patterns from player movement trajectories in soccer: methodological considerations. International Journal of Performance Analysis in Sport, 12(2), 398–424. https://doi.org/10.1080/24748668.2012.11868610
- Lorenzo-Martínez, M., Gómez-Ruano, M. A., Pino-Ortega, J., & González-Rodenas, J. (2020). Tactical Behaviour of Elite Football Teams Depending on Match Status: A Systematic Review. International Journal of Environmental Research and Public Health, 17(18), 6831. https://doi.org/10.3390/ijerph17186831
- Praça, G. M., Bredt, S. D. G. T., Chagas, M. H., & Greco, P. J. (2024). Effects of goal scoring on collective tactical behavior in professional soccer. Kinesiology, 56(1), 53–61. https://doi.org/10.26582/k.56.1.5
- Rico-González, M., Pino-Ortega, J., Nakamura, F. Y., & Los Arcos, A. (2021). Team Sports Performance Indicators From Positioning Tracking System Data: A Systematic Review. Biology of Sport, 38(4), 625–640. https://doi.org/10.5114/biolsport.2021.104920
- Romero Clavijo, S., Rojas-Valverde, D., & Gómez-Carmona, C. D. (2022). Spatiotemporal analysis of soccer teams: Centroid and surface area movement in different playing formations. Motriz: Revista de Educação Física, 28, e102200117. https://doi.org/10.1590/s1980-657420220011721