Developing resources for #abbotsthon17

The banner for the Knowledge Exchange Conference to be held in Dubli, October 2017

I was in Dublin last week and had the opportunity to meet Alan Swanton, Performance Analyst Lead, and Daragh Sheridan, Head of Capability and Expertise, at Sport Ireland Institute.

Alan has made a brave decision to invite me to participate in the HPX 2017 Knowledge Exchange Conference in Dublin in October. I am delighted that Daragh supported Alan’s decision.

My participation has two parts. The first is a one day hackathon (#abbotsthon17) with performance analysts on 5 October the day before the start of the conference. The second is a presentation on the first morning of the conference. It is titled Performance Analysis and Data Analytics – Are we there yet?  (There is a draft of the presentation on Google Slides.)

This blog post is a place holder for resources I am developing for the workshop and conference. It is connected also to a MailChimp autoresponder idea for the workshop.

By coincidence, shortly after my meeting with Alan and Daragh I saw Oisin Kelly’s sculpture, the Chariot of Life. The website notes:

Kelly’s large copper-bronze sculpture depicts the figure of a charioteer said to represents reason controlling the emotions.

This seems a great starting point for a conversation about performance analysis.

A photograph of Oisin Kelly's sculpture 'The Chariot of Life', Dublin.

Photo Credit

Chariot of Life (Keith Lyons, CC BY 4.0)

Mastodon: Sharing R Resources

I am delighted I have a Mastodon account (@KeithLyons). It provides a 500 character space for each toot.

It came to my help today.

I follow Mara Averick (@dataandme) on Twitter. I have been offline for a couple of days and found a treasure trove of links on her account.

I posted this:

I had hoped to use David Libeau’s WordPress plugin to post my toot in the way that Twitter is embedded … but that remains a work in progress.

The links Mara shared that are of direct relevance to #cssia17 included:

R powered web applications with Shiny (a tutorial and cheat sheet with 40 example apps)

“Creating and running simple web applications is relatively easy and there are great resources for doing this. But when you want more control of the application functionality understanding the key concepts is challenging. To help you navigate the creation of satisfying Shiny applications we’ve assembled example code below that demonstrates some of the key concepts.”

What is it we do in Performance Analysis?

One of Jacquie Tran‘s delightful sketchnotes appeared in my Twitter feed a couple of days ago …

It coincided with a message I received from Jamie Coles and the subsequent guest posts that appeared on Clyde Street today.

Doug‘s definition of performance analysis includes ‘insight’, ‘information’ and ‘decisions’. Jacquie’s note of his definition sent me off thinking about some other words too … ‘augmentation’, ‘support’ and ‘actionable’.

In my thinking, I returned to two seminal papers from the same year, 1991, that helped me reflect on what the craft of performance analysis might involve at the time I was establishing the Centre for Notational Analysis in Cardiff:

Ian Franks and Gary Miller, Training coaches to observe and remember. Their abstract:

This study tested a video training method that was intended to improve the observational skills of soccer coaches. Three groups of soccer coaches were tested prior to and following a training period. The experimental group was exposed to a video training programme that was designed to highlight certain key elements of soccer team performance. Although both control groups were exposed to the same video excerpts as the experimental group, they were given different orienting activities. The subjects in control group 2 were asked to discuss these excerpts with a colleague and then write a report on what they had seen, while control group 1 members repeated prior test conditions that required them to remember certain events that preceded the scoring of goals. The results indicate that, although all coaches were incapable of remembering more than 40% of pertinent information, the subjects in the experimental group improved their ability to recall all events that surrounded the ‘taking of shots’.

Richard Schmidt‘s, Frequent augmented feedback can degrade learning: Evidence and interpretations. His abstract includes these observations:

Several lines of evidence from various research paradigms show that, as compared to feedback provided frequently (after every trial) less frequent feedback provides benefits in learning as measured on tests of long-term retention.  … several interpretations are provided in terms of the underlying processes that are degraded by frequent feedback.

I do think both are very important primary sources for performance analysts. They form part of the epistemological foundations that informed Doug’s presentation.

His definition also includes ‘effective’ and ‘efficient’ dimensions. Both emphasise for me the social skills of the performance analyst in harmony with the everyday coaching environment and the rhythms of a season.

Jacquie’s sketchnote raised again for me the inevitable merging of performance analysis and analytics. I revisited Chris Anderson’s (2014) definition of sports analytics as:

The discovery, communication, and implementation of actionable insights derived from structured information in order to improve the quality of decisions and performance in an organization.

And Bill Gerard’s (2016) proposal for “a narrow definition of sports analytics” as the analysis of tactical data to support tactics-related sporting decisions. He suggests “this narrow definition captures the uniqueness and the innovatory nature of sports analytics as the analysis of tactical performance data.”

I am immensely grateful to Jacquie for this prompt. I was not able to attend at which Doug and others presented and found her visualisation of the day very welcome.