Coach education: watch making and pinball?

This is a photo of the Prague astronomical clock, or Prague orloj (Czech: Pražský orloj [praʃskiː orloj]), is a medieval astronomical clock located in Prague, the capital of the Czech Republic. The clock was first installed in 1410, making it the third-oldest astronomical clock in the world and the oldest one still operating.

This morning, John Kessel shared a poem with me (and his network of coaches) written by Terry Pettit.

The title is If I Could Coach Again. I copy it in full as a postscript to this post.

The poem arrived early morning here in Braidwood and made a great start to my day. The first line … “If I could coach again, I would speak in a softer voice”.

The poem landed just as I had finished reading a post in The Scholarly Kitchen that contained this quote:

The world changed from having the determinism of a clock to having the contingency of a pinball machine. (Heinz Pagels,  The Cosmic Code: Quantum Physics as the Language of Nature, 1982.)

There is a visualisation in the post. Although it refers directly to scholarly publishing and communication, I thought a visualisation of coach education environments might look similar:

A visualisation of the Future Lab's 2021 tech trends which appear as a pinball table.

Todd Carpenter, the author of the post, noted that the creators of the visualiation, the Future Lab group:

envisioned the new environment of our community as a giant pinball machine, with different components ricocheting the “ball” of value around the field of play, buffeted by bumpers, and potentially high-scoring opportunities in service of various areas. Just like a true pinball machine, there are risks and gutters where one’s ball can be lost.

This took me back to “the determinism of a clock” and this example of design and production:

The journey from John’s shared poem to this post was completed by contemplating Charles Jennings’ discussion of knowledge and learning transfer.

We can’t and don’t transfer knowledge between people.

We can create and use techniques and approaches that help and facilitate knowledge acquisition. We can share information in the form of data and our own insights. We can create environments where people are likely to have their own insights – their lightbulb moments – and we can help people extract meaning and learn through their own experiences.

But we don’t transfer knowledge. Not between people, or even between organisations.

Somewhere in this amalgam there is an opportunity to contemplate precision and chance in coach education. In Terry’s words we can open our practice to anyone who might be interested … watchmakers and pinball wizards.

A photograph at the end of a rugby union final in 2017. The coach thinks this is the start of a learning journey with a group of players and his own coaching.

Photo Credits

Prague 313 (fourthandfifteen, CC BY 2.0)

The end of the beginning (Keith Lyons, CC BY 4.0)

Postscript: the poem

If I Could Coach Again
I would speak in a softer voice
I would let players discover
More things for themselves
I would find ways
For players to take care
Of themselves
I would empower my assistants
To speaker in a louder voice
I would recruit a more
Diverse roster
I would control less
And empower more
I would travel
In the preseason
I would encourage each
Team member
To befriend the disabled
The disenfranchised
The people less fortunate
I would take more
Risks in scheduling
On the road
I would purchase
Season tickets and give
Them to people who
Did not have access
I would open practice
To any who wanted to watch
I would fight harder
For opportunities for women
I would risk losing more
Matches in the season
To prepare for the tournament
I would work to develop
The trust that I had with setters
With other positions
I would let go of the game
When I got to home
To my family
I would wait until the next day
To speak to a player
Who had not played her best
I would make the effort to understand
What players are dealing with
Off the court
I would let players know they are
More than their performance
I would share more with other coaches
But this is not going to happen
Because my time has passed
I have left the arena
And I will not coach again.

Dealing With Data Deluge

I have spent much of the last two days in conversations with coaches about personalising learning environments for athletes and their colleagues.

I think this ability to personalise coaching and modulate training is a characteristic of the (+) of the coach I discussed here.

A recurring theme in conversations has been the growth in pervasive sensing data in training and competition environments. I have become increasingly interested in how computational intelligence might help with these data.

Whilst contemplating these issues, I received an alert from The Scholarly Kitchen to Todd Carpenter’s Does All Science Need to be Preserved? Do We Need to Save Every Last Data Point?

In his post Todd observes:

There are at present few best practices for managing and curating data. Libraries have developed, over the decades, processes and plans for how to curate an information collection and to “de-accession” (i.e., discard) unwanted or unnecessary content. At this stage in the development of an infrastructure for data management, there is no good understanding of how to curate a data collection. This problem is compounded by the fact that we are generating far more data than we have capacity to store or analyze effectively.

He notes “the much deeper questions of large datasets and what to preserve, at what level of detail and granularity, and whether all data is equally important to preserve are questions that have yet to be fully addressed”.

Todd pointed to Kelvin Droegemeier‘s presentation, A Strategy for Dynamically Adaptive Weather Prediction: Cyberinfrastructure Reacting to the Atmosphere the U.S. National Academies Board on Research Data and Information ( a copy of the presentation here).

In his presentation, Kelvin asked a fundamental research question “Can we better understand the atmosphere, educate more effectively about it, and forecast more accurately if we adapt our technologies and approaches to the weather as it occurs?“.

To do so Kelvin noted the need to “Revolutionize the ability of scientists, students, and operational practitioners to observe, analyze, predict, understand, and respond to intense local weather by interacting with it dynamically and adaptively in real time“. He emphasised the need for adaptive systems and the provision of service oriented architecture.

This architecture for Linked Environments for Atmospheric Discovery is outlined in slide 19 of his presentation:

In his discussion of Kelvin’s paper, and the issue of volume of data, Todd suggests:

One can certainly maintain the highest grain data if in retrospect it was an extraordinary discovery or event.  However, if fine grain detail was collected and nothing of consequence occurred, does that fine-grain detail need to be preserved? Probably not, without some other specific reason to do so. Obviously, this is a simplification, since you will want to retain some version of the data collected for re-analysis, but the raw data and the resolution of that data need not be preserved on an ongoing basis.

I do think these are issues of importance for sport as volumes of pervasive sensing data are acquired. I see significant parallels between the prospective study of injury risk and Kelvin’s discussion of local weather variation.

There are important issues related to curation too. I see Todd’s post as an excellent introduction to the granularity of data and the decisions we make about the costs and benefits of collecting and storing data. A recent paper (Balli and Korukoğlu, 2012) raises an interesting question about how early these data can be collected for talent identification purposes.

Photo Credit

The British Coach Giving a Few Weight Lifting Hints