The Visual Analytic Turn

Seventeen years ago, Usama Fayyad, Gregory Piatesky-Shapiro and Padhraic Smyth wrote:

Across a wide variety of fields, data are being collected and accumulated at a dramatic pace. There is an urgent need for a new generation of computational theories and tools to assist humans in extracting useful information (knowledge) from the rapidly growing volumes of digital data. These theories and tools are the subject of the emerging field of knowledge discovery in databases (KDD).

I revisited their article in the AI Magazine this week after a number of finds prompted me to think about the visual analytic turn in sport.

The first visualisation that grabbed my attention was an English Premier League fixture strength table prepared by Neil Kellie (shared with me by Julian Zipparo). Neil used Tableau Public for his visualisation.


Neil developed his table by using a static star rating and a form rating combined to give a score for each fixture. This becomes a dynamic table as the season progresses. It has prompted me to think about how we weight previous year’s ranking in a model.

The Economist added its weight to the Fantasy Football discussions with its post on 16 August. The post uses topological data-analysis software provided by Ayasdi to visualise Opta data on the different attributes of players. In an experimental interactive chart:

the data is divided into overlapping groups. These groups contain clusters of data—in this case footballers with similar attributes—which are visualised as nodes. Because the groups overlap, footballers can appear in more than one node; when they do, a branch is drawn between the nodes. Some nodes have multiple connections, whereas others have few or none.


There is a 2m 32s introduction to the Ayasdi Viewer on YouTube. Lum et al (2013) exemplify their discussion of topology with an analysis of NBA roles. Their insights received considerable publicity earlier this year (“this topological network suggests a much finer stratification of players into thirteen positions rather than the traditional division into five positions”).

Back at Tableau Public, I found news of a Fanalytics seminar. One of the presenters at the workshop is Adam McCann.  Adam’s most recent blog post is a comparison of radar and parallel coordinate charts. Adam led me to a keynote address by Noah Iliinsky: Four Pillars of Data Visualization (46m YouTube video). Noah works in IBM’s Center for Advanced Visualization.


This snowball sample underscores for me just how many remarkable people are in the visualisation space. I am interested to learn that a number of these people are using Tableau Public … to share sport data.

In other links this week, Satyam Mukherjee shared his visualisation of Batting Partnerships in the first Ashes Test 2013:




Simon Gleave’s 26 Predictions: English Premier League forecasting laid bare reminded me of the discussions following Nate Silver’s analysis of the 2012 Presidential Elections. I enjoyed Simon’s juxtaposition of 26 pre-season Premier League predictions, “13 which are at least partially model based, and 13 from the media. The models select Manchester City as title favourites but the journalists favour Chelsea”. Simon’s post introduced me to James Grayson and his reflection on predictions about performance. I think Simon and James have a very impressive approach to data.

This week’s links have left me thinking about an idea I had back in 2005. I wondered at that time if I could become skilful enough to combine the insights offered by Edward Tufte and Usama Fayyad. More recently, I have been wondering if I could do that with the virtuosity that pervades Snow Fall.

Visualising Sport Performance Data

I find the quality and quantity of website data about sport performance staggering.

I wrote about the possibilities of secondary data analysis at the Asian Football Cup 2011.

Recently I have been looking at data from the ICC Cricket World Cup and noticed this Cricinfo game summary:

There is a dropped catch icon  and a wicket icon that provide links to text summaries of the event.

I have been looking at some rugby union sites too.

Foxtel have a record of game events in Super Rugby that I have found particularly useful in tracing sequence of scores:

The RSB Six Nations’ website provides a data report of each game available for download:

I like the elegant simplicity of the Cricinfo graphic, the concise information in the Foxtel graphic and the detail in the RSB Six Nations’ website data.

I acknowledge that these are secondary sources but they do provide a great permanent record for investigation. Perhaps it is my fascination with Edward Tufte‘s work has nourished my interest in visualisation.

Photo Credit

World Wide Web Visualization 4717

Immigrants, Natives and Wayfinders

It has been another wonderfully busy week at the University of Canberra. There have been some great discussions about teaching and learning. I have been hoping to write about a number of ideas that arose from those discussions whilst trying to think about some of the digital immigrant and digital native conversations going on at the Growing Up in Australia conference in Melbourne.

A fortuitous checking of my Twitter account led me to Sylvia’s Generation Yes‘s blog post about the Circle of Life: the technology-using educator edition. Her post was the catalyst to write this post about educational technology and digital status. (Her conclusion took my thoughts back to Erica McWilliam and the role of the teacher in another line of thought and then on to a report about creativity.)

Some fragments from the discussions about the use of digital technology this week include:

Michael Bittman (University of New England, Australia) and Leonie Rutherford (Deakin University, Australia) presented a paper on Digital Natives, Issues and Evidence About Children’s Use of New and Old Media. The abstract of their paper can be found here (page 7). (Their abstract took me back to Mark Prensky‘s work and last year’s discussion of these ideas by Sue Bennett and her colleagues. I accessed the Digital Natives blog for the first time via a Wikipedia link.)

Leigh Blackall discussed the role of the Popular Internet in Teaching and Research at a University of Canberra workshop on teaching and learning. His work excites me and it was great to hear him develop his ideas in person.

I liked hearing about James Neil’s use of Wikiversity at the same workshop too. James is a passionate advocate for Open Access.

All  these opportunities to reflect on our digital status led me back to ideas discussed in CCK08 in relation to wayfinding and to a paper delivered by George Siemens earlier this year ‘Learning and technology: success and strategy in a digital world‘. They led me back even further to my fascination with notational analysis and cartography stimulated by Alfred Wainwright (he compiled handwritten and hand-drawn Pictorial Guides to the Lakeland Fells that resonate so perfectly with Edward Tufte‘s work).

… and thence back to Sylvia Martinez‘s post and the building of expertise in the cycle of life:

You attempt something on a wide scale, collaborating with other like-minded educators. You find renewed energy as you work with students or teachers and see things change. You find books, even some written decades or centuries ago that support your beliefs. You become better able to articulate the “why” of all this. You think about going back to school. You find experts outside of your newly constructed network.

I am wondering if rather than being an immigrant or native there are opportunities for wayfinding that are triggered by biography but are nourished by the willingness to travel.

Photo Sources

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