Visualising Performance Data: #ENGvAUS Netball Test Series 2016

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I have been following the three-match netball test series in England.

Australia won the series 3v0.

I found Champion Data’s record of the games very helpful.

In advance of more interactive visualisations, I am sharing a box plot of goals scored in the 12 quarters played.

3 Test Box Plot

I used BoxPlotR to generate this visualisation.

(In this plot, centre lines show the medians; box limits indicate the 25th and 75th percentiles as determined by R software; whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles; data points are plotted as open circles. n = 12 sample points.)

I have been thinking about random walk behaviour in court games.

My plot of shots at goal and goals scored for the first test match is:

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This was the closest game in terms of goals scored. England missed just five attempts at goal in the whole game (Australia missed eleven).

In all three tests, Australia had more goal attempts than England.

I was thinking about how to visualise momentum in these games.

For the second test, I thought I would identify any examples of one team dominating play. These data do indicate a shift in momentum in the game and highlight Australia’s dominance of the third quarter.

My blocks of colour are intended to indicate dominance of play by Australia (dark green) or England (red) per minute played.

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I see some fascinating opportunities to create interactive visualisations of these data.

Photo Credit

Third Test (Australian Diamonds, Twitter)

Synoptic Vision

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Two years ago, I explored the possibility of visualising actual performance compared to predicted performance … after a visit to the Sydney Moderns Exhibition and learning about Roy de Maistre ‘s use of colour.

This week, a Kevin Ferguson post has encouraged me to think about how video might be used as a synoptic tool for performance analysts.

Kevin wrote about watching 50 Western films and compressing each film into single frames of form and light. To create his image of each film, Kevin extracted one frame from every 10 seconds of the film and summed with the others to create a real image.

Kevin suggests that the images have the potential to be evocative and to allow an emotional response “confirmed or denied once you come to discover what the image really is”.

I found Kevin’s approach fascinating. He introduced me to:

His approach to brightness, hue and saturation took me back to and beyond Roy de Maistre.

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Kevin’s April 2015 post is full of detail about his approach to the creation of images. He has another technical post about ImageJ written in 2013.

In the 2013 post, Kevin discusses the approach he has taken to re-visualise film

Since a film (along with, most often, its audio track) operates primarily by visual means, we should recognize the film itself as already a “visualization.” Just as with data visualization

Kevin quotes Victor Shklovsky:

The purpose of art is to impart the sensation of things as they are perceived and not as they are known. The technique of art is to make objects ‘unfamiliar,’ to make forms difficult, to increase the difficulty and length of perception because the process of perception is an aesthetic end in itself and must be prolonged.

Kevin’s two posts have prompted me to think about all the video we have in sport from training and competition environments. I wondered how we might use these to add a new dimension to our understanding of performance by increasing the difficulty and length of perception … and stimulating discussions about aesthetic understanding.

I wondered if we might use Kevin’s approach to re-visualisation as a new form of trigger images.

This is my visualisation of an AFL Champion team’s performance based on data:

H-Compare

A team that improved during an AFL season appears like this:

R-Compare

I wondered what synoptic vision of these performances Kevin’s video methodology might produce.

Kevin concludes his 2015 post thus:

As a scholar, though, what use are these average looks — which strip out virtually all narrative, characterization, plot, sound, dialogue, and action? I don’t yet have a cogent answer to that question, but I do have a strong suspicion that film studies will benefit from new modes of visualization such as this one, which represent film texts from an otherwise impossible perspective — in this case, along the z-axis that compresses the film’s time into a single frame of form and light.

I am hopeful that sport might grasp these “new modes of visualisation … from an otherwise impossible perspective”.

Perhaps we might then explore the essence of sport.

Photo Credits

Monument Valley 02 (Rich Michaels, CC BY-NC-ND 2.0)

Lights, Abstract (Louis Vest, CC BY-NC 2.0)

Visualising Data 130707

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Yesterday,  I wrote about Gregory Crewdson.

I am not sure if the documentary had primed me to be on the look out for visualisations of data but I found three interesting examples this week.

Three Visualisations

Battle of Gettysburg

The first is the Smithsonian’s Cutting-Edge Second Look at the Battle of Gettysburg. In the post that shares the second look, Anne Kelly Knowles notes that “the technological limits of surveillance during the American Civil War dictated that commanders often decided where to deploy their troops based largely on what they could see”. She asks “What more might we learn about this famous battle if we put ourselves in commanders’ shoes, using today’s digital technology to visualize the battlefield and see what they could see?”

This approach reminded me of Philippe Mongin’s paper, A Game-Theoretic Analysis of the Waterloo Campaign and Some Comments on the Analytic Narrative Project.

Anne, researcher Dan Miller and cartographer Alex Tait worked together to provide this perspective.

Alex recreated the 1863 terrain based on a superb map of the battlefield from 1874 and present-day digital data. Dan and I captured troop positions from historical maps. Our interactive map shows Union and Confederate troop movements over the course of the battle, July 1 – 3, 1863. Panoramic views from strategic viewpoints show what commanders could – and could not – see at decisive moments, and what Union soldiers faced at the beginning of Pickett’s Charge. You will also find “viewshed” maps created with GIS (Geographic Information Systems). These maps show more fully what was hidden from view at those key moments.

Tour de France 2013

The second visualisation is of the 2013 Tour de France by Cycling the Alps.

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I was interested to see the gamification option in this visualisation. The 3D Stage tour and the Stage game both require the Google earth plugin to run the visualisation.

AAR 214

The third visualisation took me to a new world of data. Earlier today, Charlie White posted data about the Asiana Airlines Flight 214 (AAR 214) crash landing in San Francisco. He noted Steve Baker’s use of the flight tracking website FlightAware to compare two approaches to the airport by the same flight number.

Crash

The Mashable post has prompted a robust exchange about the validity of these two data juxtapositions.

One comment noted: “The difference between Fri and Sat was wind direction. Today, the wind was extremely shifty, switching almost 180 deg, from N to S. The plane was landing with a sort of tail wind, which every pilot knows is not good. The SFO landing strip is at 135 deg, and the wind was from 210.”

There are other data available from FlightAware.

New Literacies?

Brief Encounters and these three visualisations raise some important issues about the literacies we need to use data rich visualisations. I am fascinated by the skills that deliver these visualisations.

One visualisation that has had an enormous impact on my thinking is the New York Time’s Snow Fall: The Avalanche at Tunnel Creek. I learned with interest that the author John Branch had won a Pulitzer Prize for Feature Writing for the story.

In its nomination submission, The New York Times wrote:

Rarely, we suspect, has there ever been a more fully realized partnership of fine writing and state of the art multimedia put before the features jury, and we encourage you to experience the story the way our online readers did: by clicking on the link submitted here.

I wrote about Snow Fall at the time of its publication. It was a transformational moment for me as I thought about how to re-present data. These three recent examples shared here add to this changing environment.

Photo Credits

Frame grab from Brief Encounter trailer

Frame grab from Smithsonian post Cutting-Edge Second Look at the Battle of Gettysburg

Frame grab from Mashable post FlightAware Shows Path of Crashing Plane original image from Steve Baker.