Soccer Visualization at AVIZ

This page groups the effort of the AVIZ team in better understanding and communicating sport data, and since we are European, we work with soccer. We conducted three projects:

  • SoccerStories: A Kick-off for Visual Soccer Analysis (Best Paper Honorable Mention at InfoVis 2013)
  • A Table! Improving Temporal Navigation in Soccer Ranking Tables (CHI 2014)
  • Real-Time Crowdsourcing of Detailed Soccer Data (SportVis workshop, VIS 2013)



SoccerStories is a visualization interface to support analysts in exploring soccer data and communicating interesting insights. Currently, most analyses on such data relate to statistics on individual players or teams. However, soccer analysts we collaborated with consider that quantitative analysis alone does not convey the right picture of the game, as context, player positions and phases of player actions are the most relevant aspects. We designed SoccerStories to support the current practice of soccer analysts and to enrich it, both in the analysis and communication stages. Our system provides an overview+detail interface of game phases, and their aggregation into a series of connected visualizations, each visualization being tailored for actions such as a series of passes or a goal attempt. To evaluate our tool, we ran two qualitative user studies on recent games using SoccerStories with data from one of the world's leading live sports data providers. The first study resulted in a series of four articles on soccer tactics, by a tactics analyst, who said he would not have been able to write these otherwise. The second study consisted in an exploratory follow-up to investigate design alternatives for embedding soccer phases into word-sized graphics. For both experiments, we received a very enthusiastic feedback and participants consider further use of SoccerStories to enhance their current workflow.



Charles Perin, Romain Vuillemot, Jean-Daniel Fekete. SoccerStories: A Kick-off for Soccer Visual Analysis. Proceedings of the IEEE Transactions on Visualization and Computer Graphics (InfoVis'13), Oct. 2013, Atlanta, GA, USA. IEEE


Not public yet but demo soon--or at least one day--available.

High-res screenshots

Click on the thumbnails to access medium/high-resolution screenshots
Note that in these screenshots the player runs with the ball are represented using straight plain lines instead of squiggly lines, due to a bug from SVG update


Phases small multiples variations

Faceted views of a shot on goal:

Default view

With brushing

With "spray" mode

Faceted views of crossover/corner kicks and long runs:


Long run

A series of passes in a phase represented using different faceted views:

Original phase

Original group of passes

Using a complete node-link

Using a filtered node-link

Using a hiveplot

Using an adjacency matrix

Using a tag cloud

À Table! Improving Temporal Navigation in Soccer Ranking Tables


À Table! is an enhanced soccer ranking table to improve temporal navigation, by combining two novel interaction techniques. Ranking tables order soccer teams as rows, and columns contain e. g., their points or number of scored goals. Because they are a snapshot of a championship at a time t, they are constantly updated with new results. Such updates change the rows vertical order, which makes the tracking of a team, over time, difficult. We observed that current tables on the web do not support such changes very well, are generally hard to read, and lack dynamic interactions. This contrasts with the extensive use of temporal trends by soccer analysts in articles. We introduce two interactive techniques to better explore time: DRAG-CELL is based on direct manipulation of values to browse ranks; VIZ-RANK uses a transient line chart of team ranks to visually explore a championship. An on-line evaluation with 143 participants shows that each technique efficiently supports a set of temporal tasks, not supported by current ranking tables, while not breaking the flow of users. This paves the way for efficiently introducing advanced visual exploration techniques to millions of soccer enthusiasts who use tables everyday, as well as other application domains which use ranking tables.



Charles Perin, Romain Vuillemot, Jean-Daniel Fekete. À Table! Improving Temporal Navigation in Soccer Ranking Tables . Proceedings of the 2014 Annual Conference on Human Factors in Computing Systems (CHI 2014), Apr 2014, Toronto, ON, Canada. ACM



Investigating the Direct Manipulation of Ranking Tables


We introduce a novel time navigation technique to update ranking tables by direct manipulation. The technique allows users to drag a table's cells to change the time period, while a line chart overlays on top of the table to provide an overview of the changes. The line chart is also a visual hint to control the pace at which data are updated. We explore the design and usability of this technique for table variations in size, time spans and data variability. We report the results of a usability study, using academic citation rankings and economic complexity datasets, and discuss design implications coming with real-world scenarios such as missing data and affordance.



Romain Vuillemot, Charles Perin. Investigating the Direct Manipulation of Ranking Tables. Proceedings of the 2015 Annual Conference on Human Factors in Computing Systems (CHI 2015), Apr 2015, Seoul, Korea. ACM



Real-Time Crowdsourcing of Detailed Soccer Data


We explore how spectators of a live soccer game can collect detailed data while watching the game. Our motivation arouse from the lack of free detailed sport data, contrasting with the large amount of simple statistics collected for every popular games and available on the web. Assuming many spectators carry a smart phone during a game, we implemented a series of input interfaces for collecting data in real time. In a user study, we asked participants to use those interfaces to perform tracking tasks such as locating players in the field, qualifying ball passes, and naming the player with ball while watching a video clip of a real soccer game. Our two main results are 1) the crowd can collect detailed–and fairly complex–data in real-time with reasonable quality while each participant is assigned a simple task, and 2) a set of design implications for crowd-powered interfaces to collect live sport data. We also discuss the use of such data into a system we developed to visualize soccer phases, and the design implications coming with the visual communication of missing and uncertain detailed data.


Charles Perin, Romain Vuillemot, Jean-Daniel Fekete. Real-Time Crowdsourcing of Detailed Soccer Data. Proceedings of What's the score? The 1st Workshop on Sports Data Visualization (SportVis'13), Oct. 2013, Atlanta, GA, USA. IEEE


E-mail all co-authors

  • Charles Perin
  • Romain Vuillemot
  • Jean-Daniel Fekete