ReSpo.Vision

What you're seeing here is one of the less visible - but fundamental -steps behind ReSpo.Vision optical tracking: homography. A football broadcast gives us a 2D image captured by a camera that is constantly changing its perspective as it pans, tilts and zooms. To turn detections from that video into useful tracking data, we first need to understand how what the camera sees corresponds to the actual football pitch. That's what homography helps us do. It maps points from the camera image onto a standardized representation of the pitch, creating the spatial reference needed to determine where players and the ball are located. Why does this matter? Because virtually everything that comes afterwards depends on that spatial foundation. Player distances, team width and length, defensive line height, speed, positioning or spatial relationships between players all rely on knowing where objects actually are on the pitch. Small inaccuracies at this stage can propagate into the tracking data and, eventually, into the metrics and conclusions derived from it. The analyst working with the final dataset may never see the homography process itself. But the quality of their analysis depends on it. Reliable tracking data starts long before the first x,y coordinate is generated. #FootballAnalytics #TrackingData #ComputerVision #SportsTech #FootballTech

One of the biggest challenges in football analysis is distinguishing an observation from a genuine tactical tendency. Good analysts spot patterns quickly. They identify overloads, pressing triggers and recurring movements after watching just a few clips. But the real challenge isn't making those observations—it's knowing whether they reflect a team's actual game model or simply an isolated moment shaped by the opponent, the game state or the context of a single match. Without objective evidence, even the strongest observations remain hypotheses that can be challenged. That's where tracking data becomes valuable. Not because it replaces video, but because it allows analysts to validate their conclusions before turning them into recommendations. Instead of relying solely on what they think they saw, analysts can ask deeper questions. What consistently triggers this behaviour? Which off-ball movement creates the space? Does this pattern persist against different opponents and defensive structures? Tracking data doesn't tell analysts what to think. It provides the objective evidence needed to support their reasoning, communicate findings with greater confidence and make better-informed decisions. At ReSpo.Vision, that's how we believe tracking data should fit into the analysis workflow—not as a replacement for video, but as the missing step between observation and decision. #FootballAnalysis #PerformanceAnalysis #SportsAnalytics #TrackingData #SportsTech #ComputerVision

One of the fundamental challenges in football analytics is understanding the ball, not just the players. Player tracking tells us how players move across the pitch. X,y,z ball tracking adds another dimension: it describes how the ball travels between them. Not just where it starts and ends, but how it gets there—its trajectory, height, speed, flight time, and relationship to the players around it. For analysts, that additional layer of information enables a deeper understanding of actions on the pitch. 💡 How difficult was a pass to execute? 💡 How much defensive pressure did it bypass? 💡 Which passing trajectories are most effective against different defensive structures? 💡 How should goalkeeper distribution or crossing quality be measured beyond completion rate? Combined with player tracking, x,y,z ball tracking provides a richer foundation for analysing how actions develop—from the movements that create an opportunity to the path the ball takes. At ReSpo.Vision, every day we explore what's possible when player and ball tracking are analysed together. #FootballAnalytics #SportsAnalytics #TrackingData #ComputerVision #SportsTech

Only four matches remain at the FIFA World Cup 2026™ - Canada, Mexico and the United States: FFF - Fédération Française de Football vs Real Federación Española de Fútbol The Football Association vs Asociación del Fútbol Argentino Then, later this week: 🥉 The third-place match 🏆 The final Four matches will decide the fate of the trophy. But beyond the action on the pitch, every major tournament is also an operational challenge for the competition organizer. In today's carousel, we look at tracking data from that perspective—sharing four principles worth considering when building competition-wide tracking data coverage. Enjoy the final week of the tournament. ⚽ FIFA #FIFAWorldCup #WorldCup2026 #FootballAnalytics #TrackingData #SportsTech

Every good football decision starts with reliable observations. In elite football, analysts are expected to answer high-stakes questions: Did the defensive structure actually break down❓ Was the pressing effective❓ Did a player create value without touching the ball❓ Which movements consistently create space❓ Which patterns lead to high-quality chances❓ These answers don't come from watching the match twice. They come from the metrics, models, and insights built on top of tracking data: player positioning, movement trajectories, inter-player distances, team compactness, pressing intensity, passing lanes, spatial control, and countless other features. But every one of those analyses depends on one thing: The reliability of the underlying observations. ✅Computer vision isn't the final insight. It's the foundation that transforms video into structured, trustworthy tracking data that analysts can build on with confidence✅ Because every conclusion—and every decision—inherits the strengths and the weaknesses of its inputs. Yes—it was Van Persie's flying header against Spain. ReSpo.Vision #FootballAnalytics #SportsAnalytics #TrackingData #ComputerVision #DataScience

Earlier this month at #CVPR2026, our Chief Data Scientist & Co-Founder Łukasz Grad presented part of the research behind one of the hardest problems in sports tracking: ✅ reconstructing the full 3D flight of a football from a single broadcast camera ✅ Accompanying this work, we’re publicly releasing two football datasets containing per-frame triangulated 3D ball trajectories to foster further research in sports AI, tracking, and computer vision. Why does this matter? Reliable, open datasets let the research industry to develop new methods that are then used in elite high-stakes football environments. A lot of sports AI discussion focuses on outputs - we’re equally interested in the modelling underneath: physics, reconstruction quality, and validation that ultimately determines whether tracking data is reliable enough to support real football decisions. This research, presented at #CVSports, reflects part of the technical foundation behind how we approach tracking at ReSpo.Vision. Link to the project page in the comment below! #sportstech #trackingdata #sports #football #performance #sportsanalytics

The wait is finally over! 🕛 🗓️ Today, the FIFA World Cup 2026™ - Canada, Mexico and the United States 🏆 Before a new tournament gives us new stories, new heroes and new emotions, we went back to one of the greatest finals football has ever seen: Argentina vs France, Lusail Stadium 2022. For nearly 70 minutes, Argentina controlled the match through compactness, coordinated pressure and repeated high-intensity defensive actions. But late in normal time, the physical dynamics began to change. Our tracking data suggests a reduction in repeated high-intensity actions. And when games become stretched, few players are more dangerous attacking space than Kylian Mbappé. This is how tracking data becomes truly valuable: ✅ not only measuring physical output, but helping explain how tactical dynamics evolve throughout a match. Enjoy the tournament ⚽ ReSpo.Vision Asociación del Fútbol Argentino FFF - Fédération Française de Football FIFA #FIFAWorldCup #WorldCup2026 #FootballAnalytics #TrackingData #SportsTech #PerformanceAnalysis #FootballData #ReSpoVision

Vitinha was officially named Player of the Match in Paris Saint-Germain's UEFA Champions League Final victory over Arsenal Football Club in #Budapest. At first glance, his passing map might not look spectacular. Yet he seemed to be everywhere. Looking at the ReSpo.Vision's tracking data, one thing stands out: Vitinha consistently made himself available as a passing option while operating under pressure. Among PSG players, he combined one of the highest passing availability rates with one of the highest volumes of pressure. More importantly, he kept possession and allowed PSG to keep attacking. The result? A remarkable area of influence just outside Arsenal's penalty area, helping PSG maintain territorial control throughout the match and repeatedly restart attacking sequences. #RespoVision #UCLfinal #UCL #PSGARS #sportsanalytics #sportsAI

Football organizations increasingly treat tracking data as a core part of their performance infrastructure. But one important question is often overlooked: ➡️ Who ultimately controls the data generated from your matches? ⬅️ In elite football, performance tracking is not just “analytics.” It can include: ⚽ tactical behaviors 👦 development of youth players 📈 long-term strategy That makes tracking a high-sensitivity operation. And not all processing models operate the same way. Some ecosystems are designed around: - centralized platforms - redistribution models - broad commercial accessibility, including media and betting-related environments At ReSpo.Vision, matches are processed on demand from customer-provided footage. The generated datasets remain exclusive to the requesting organization — not redistributed into shared commercial tracking pools. Because in elite football, how data is handled may become just as important as the data itself. #sports #football #performance #trackingdata #sportstech #sportsanalytics

Tracking data is becoming increasingly accessible across football. But in high-stakes workflows, accessibility alone is not enough. Organizations focused on long-term performance need data they can rely on consistently — across matches, environments, and analytical workflows. At ReSpo.Vision, we focus on a different layer of the process: ✅selected and analytically relevant matches ✅reliable data for high-stakes decisions ✅flexible, infrastructure-independent tracking All generated from a single broadcast video. #FootballAnalytics #SportsTech #ComputerVision #TrackingData #AI #FootballTechnology #PerformanceAnalysis