2017 in review: curating an open educational resource for sport informatics and analytics

In the last year, I have been able to spend time on most days curating the OERu course Sport Informatics and Analytics.  The ease of editing Wikieducator makes this curation a delight rather than an obligation.

One of the features of the OERu guidelines for course sharing is the inclusion of an outline for the course that contains links to all pages and sections. This outline has grown significantly in 2017 as I have added topics to the course. I am particularly interested how these links (120 at the moment) can be used as microcontent and create an opportunity for open badges in 2018.

The main sections of the course are:

Course description

Introductions

Pattern Recognition

Performance Monitoring

Audiences and Messages

Ethical Issues

The Quantified Self

Using R

Visualising Data

Feedforward

Communities of Practice

Knowledge Discovery

Capstone

Six European Football Leagues Going into Christmas 2017

I have been following scoring patterns in six European football leagues (EPL, Ligue 1, Bundesliga, Serie A, Eredivisie and Primera) in the 2017-2018 season.

I have a particular interest in the outcome of scoring first and not losing in games in these leagues.

Prior to midweek games on 13 December 2017, the range of my data (n=875 games) thus far is:

In Ligue 1, the % of games in which the team that has scored first and not lost has ranged between 86% and 89%. In Serie A, the range is 72% to 80%. The other four leagues fit between these two leagues.

My BoxplotR visualisation of nine observations for these leagues is:

The box plot statistics are:

The EPL is about to enter an intense fixture period and I will be interested to observe any changes in pattern.

A separate project is to examine the games in which the team that scores first has lost (n=96 of the 875 games played). The Eredivisie has the largest number of these games (n=23 out of 134 games) and the Primera the smallest number (n=12 out of 150 games).

Photo Credit

Marco Verratti (PSG Officiel, Twitter)

Fireworks (AjaxDaily, Twitter)

A four decade journey in performance analysis and analytics

The end of a calendar year is a good time to reflect on learning journeys. This December, I have been thinking back over four decades.

My fascination with performance analysis and analytics started with my role as a teacher of physical education and as a young coach in the 1970s. In 1977, I started to take responsibility for coaching club rugby union. My role models were Tony Gray, Jim Greenwood, Ray Williams and John Dawes. I think my roots in applied performance analysis were set then. Thereafter, whatever work I did in analysis was focussed on supporting coaches and athletes.

A decade later, in 1987, I was starting the write up of my part-time PhD at the University of Surrey. I had spent three years observing the teaching of physical education in two schools and was immersed in the ethnographic literature. My supervisor introduced me to the work of Miller Mair and from that time I have been keen to explore performance analysis and analytics as storytelling and story sharing.

These are the kinds of things I learned from Miller:

Our worlds are structured in metaphor and images. We can only tell stories from conjured images of what we suppose we are and what we suppose we know, within the language and assumptions of our place and time.

Every telling (whether in psychotherapy, science, the market place or the lovers bed) is a composition with personal intentions. Every telling is partial, suffused with personal interest.

Every telling has to be in some manner and style. Even when we seek to be plain and blunt we are using stylistic devices for signifying plainness and bluntness.

Science has tried to be ‘the story to end all stories’, or a story trying its hardest not to seem like a story at all, but the way things are. Every group has its own sanctioned ways of telling for different purposes and contexts, its ways of listening, ways of evaluating. The ‘hard’ approaches to science have their own ways of telling set up in such a way as to seem and claim to be above and separate from mere telling, beyond any contamination in the telling itself.

But stories are partial and political. We all have vested interests in our psychological and other tellings.

My thesis ended up being a collection of stories. Two of them are:

Do people who have lost their voice have to do it?

Anush and basketball fever

I had started doing some hand notations of rugby and lacrosse whilst I was at St Mary’s College at Strawberry Hill (1978-1986) and had been using VHS video recordings of performance. By the time my PhD was submitted, I had written a book about the use of video in sport.

The next decade took me into the digital era but strongly connected to storytelling (Are we all performance analysts? (1998)). I was fortunate to spend this decade at the Cardiff Institute of Higher Education (later UWIC and subsequently Cardiff Met).

I was a guest at the Sports Coach conference in Melbourne in November 1998.

I took with me  one of the first digital cameras and an early example of a portable analysis system that had been developed by Tony Kirkbride. My presentation to the conference is archived on Slideshare.

These are two of slides I shared at the conference:

and

I provided an example of my own use of digital stills in coaching as I tried out the new technology.

A decade later, I was at the Australian Institute of Sport (AIS) in Canberra. I rode the wave of digital technologies and was part of a decade that saw the full-fledged software as a service era and the emergence of a video repository for online and near line access on demand. In 2005, I had the opportunity to develop a proposal for funding for three analytics positions. We were also using Australia’s supercomputers and high speed infrastructure to share large amounts of swimming video and data (up to 1tb). By 2007, we had started a data analytics project for the Beijing Olympics that contributed to a gold medal performance and had developed a stable machine learning approach to support cricket coaches in the Ashes Series.

The opportunities I had at the AIS gave me wonderful freedom to explore and champion disruption in the support an institute could offer to the daily training and competition environments.  I was fortunate that my line managers were able to see beyond the narrow limits of videography and coding and embrace a digital age that celebrated knowledge discovery in databases.

Much of my work in the decade following the AIS innovations has been spent exploring open access sharing. In 2017, my focus has been to use the plethora of online education platforms to continue my own learning and to share resources with others in a world that now sees the sharing, aggregating and curating of digital artifacts as a normal activity.

My most recent learning experiences have been with R and ggplot 2.

Reflecting on this four decade journey from analogue to digital experiences has been a fascinating experience. It was helped by a presentation I gave in Ireland earlier this year, Are We There Yet?

What excites me is how present day researchers are using technologies and creating innovative communities of practice that are accelerating our understanding of performance.

When I started my learning journey in the 1970s, it was possible to aspire to be a polymath in performance analysis and analytics. Four decades on the flourishing of all forms of enquiry make that much more difficult.

I am relishing the next decade and am wondering what my experience will be when I look back from 2027.

I am hopeful it will be more like:

than

Photo Credits

Interesting sidelines (scsmith4, CC BY-NC-ND 2.0)

Miller Mair (Constructivist Psychology)

2008 McLaren Park CX Tilt Shift (Steven Woo, CC BY-NC-SA 2.0)

Geen hulp voor Giusto Cerutti (Nationaal Archief, no known copyright restrictions)