Charles, Richard, Neil and Simon: the stories we craft

Tom Fenton and Rob Carroll have published a story about Charles Reep (link). It is titled Football’s Pioneer – The Charles Reep story.

Earlier this year, Richard Pollard published Invalid Interpretation of Passing Sequence Data to Assess Team Performance in Football: Repairing the Tarnished Legacy of Charles Reep in the Open Sports Sciences Journal (link).

Both posts have encouraged me to think about how we craft stories. Tom’s introduction indicates that Charles’ achievements have been forgotten and marginalised (link). Richard suggests that a 2005 paper makes “erroneous and misleading statements” about Charles and that “a basic misunderstanding of how to interpret and assess the effectiveness of passing sequences of different lengths” is at the heart of the issue (link).

Tom concludes:

Whatever you think of Charles Reep’s tactical influence, his legacy on Sport Analytics is not only undeniable, it is simply invaluable, for the industry we see and admire today, would not be the same without him and his priceless notes.

Richard ends his paper with this comment:

The way in which the 2005 paper has been used by others to discredit Reep, while at the same time claiming definitive proof that direct football is less effective than keeping possession, is a salutary warning as to how easily false information can disseminate itself.

Much of my professional life has sought to integrate qualitative observation, the analysis of performance, teaching and coaching. I have spent a great deal of time thinking about ethnography and autoethnography and my PhD thesis completed in 1989 (link) was an ethnographic account of the teaching of physical education in two schools located next to each other.

In writing that thesis, I became very interested in the ways stories are socially constructed. Ctlifford Geerz had an enormous impact on me and once I had read about his work in ‘thick description’ (link) I saw the process of observation, the art of teaching and coaching quite differently. From then on, I took culture to be “a web of analysis” and an interpretive science “in search of meaning”.

This search of meaning led me to see story sharing as a way of talking about practice (link). Stories were built with careful observation and written in ways that embraced language, reader receptivity and poetics. At that time, I was emboldened by the publication of John Van Maanen’s approach in Tales From The Field (link). In looking at different kind of tales, John notes that conveying social reality requires authorial voice. His book explores how this voice is crafted in realist, confessional and impressionist tales.

In an Epilogue to a 2010 print edition of the Tales (link), John wrote:

Our writing is both explicitly and implicitly designed to persuade others that we know what we’re talking about and they ought therefore to pay attention to what we are saying. (2010:147)

Re-reading this after looking at Tom, Rob and Richard’s accounts of Charles Reep took me back to think about authorial voice and how we might construct a life history and a socially constructed account of a very special time in sport analytics.

Richard Pollard

Richard, Neil and Simon knew Charles very well at that point in time and are primary sources of Charles’s life. I have corresponded with Richard and Neil about their experiences with Charles and their own careers as analysts. I have not spoken with Simon Hartley and I think about this absence has on the story I would like to construct about the life and times of all four of them.

Richard, for example, has kept every letter Charles sent him dating back to 1960, and has stored Charles’ match analyses and other documents shared over the years. He also has two years of Simon’s analyses of Watford performance. Richard has kept all his correspondence with Bernard Benjamin about the authorship of both papers on Skill and Chance (link) (link).

Richard completed his thesis in 1989 at the University of the South Pacific. It was titled Measuring the effectiveness of playing strategies at soccer (link). Information about this thesis was contained in a paper written by Richard and Charles that appeared in the Journal of the Royal Statistical Society in 1997 (link).

Neil Lanham

Neil has shared some of his experiences with me in email correspondence and these emails have become important insights for me as I try to fit Neil’s story into Charles’, Richard’s and Simon’s stories. Neil’s memoirs were to be published this year. They will make for fascinating reading.

I have written about Neil’s work but have yet to provide an account of his work with Wimbledon, Dave Bassett and Graham Taylor. I have not addressed Neil’s early use of computers in 1985 and the impact this had on his work. I hope to explore Neil’s contact with Charles over a long period of time. In one personal correspondence to me, Neil observes “to know Reep you need to have trod in his footsteps”.

Treading in Charles, Richard, Neil and Simon’s footsteps will be a fascinating journey and one that raises important questions about authorial voice. As an action researcher I am keen to share these stories with them before I post public blogs about them. I see the production of stories as an iterative and participatory process.

Charles Reep

This process will require an understanding of documents. Jean-François Rouet and colleagues (1996) (link) note that historians “must carefully select information from documents and evaluate it in the context of who wrote the document, what type of document it is, and how the document relates to other documents on the same topic”. This requires us to reason about documents and reason with documents.

This reasoning acknowledges, as Sam Wineburg (1998) (link) points out, that “historians do not go into the archive to find carefully excerpted documents, serially presented, each with an explanatory sentence at the top”.

These challenges require the writer to be a critical friend in the story gathering, story crafting and story sharing aspects in the search of meaning. Erin Comollo (2019) (link), amongst others, points out that we can “engage in joint construction of knowledge through conversation and other forms of collaborative analysis and interpretation”.

In doing so, I believe, the art of writing provides the opportunity for the critical friend, as Arthur Costa and Bena Kallick (1993) indicate, to be “a trusted person who asks provocative questions, provides data to be examined through another lens, and offers critique of a person’s work as a friend” (link).

To date, we have had partial stories about Charles, Richard, Neil and Simon. There is an opportunity to extend these stories and provide thick description of a pivotal moment of sport analytics in England. It requires a comprehensive, co-operative story-making effort. The outcome could be an inclusive and participatory account that is reflective and critical. Perhaps a story that addresses concerns raised by Richard and Neil in their various responses to accounts of Charles, his practices and impacts. It would be important to have Simon’s take on this too.

There is so much to write about and share.

Photo Credit

Champions of the world (The Football Times)

 A Football Pink report of the Swindon Town v Bristol Rovers game, played on Saturday, 18 March 1950.

Richard Pollard (Personal Correspondence)

Neil Lanham (Personal Correspondence)

Charles Reep (The Sun)

Watford v Southampton 1980 (YouTube)

#RWC2019: patterns after 29 games

29 games have been completed at #RWC2019 (link). I have continued with my idea of characterising the games played with a single number (link). This number is the median ratio of kicks and passes divided by lineouts and scrums. My hope is that this expresses the mobility of each game.

I am using data form the official World Rugby website (link) to curate my data for the tournament. I have noted that these numbers do change after the games have played (particularly the number of passes). I have used data twenty four hours after the completion of the game as a record of that game. I am collecting the data as a Google Sheet (link) with tabs for each game played.

I have used ggplot to visualise data and I am using the data to help me improve my use of R. These visualistions include:

  • ggplot
  • geom_point
  • geom_vline
  • geom_smooth
  • labs
  • annotate
  • size
  • theme_minimal
  • a colour blind palette (link)

My visualisations of the 29 games are including identified outliers are:

I have a Ratio for each game. The tournament median is 2.31 and is expressed by a geom_hline default size and shape in black.

The Ratio is expressed with a geom-smooth function in order to see what the trends in the data look like. The confidence limits are set by default at 95%. I have used the loess method with my small number of data points. The grey area expresses the confidence band for the regression line drawn with the method. The confidence interval can be turned of with se = FALSE or set at a level you specify:

Passes with a geom_hline set at the median number of passes (258):

Passes with a geom-smooth:

Kicks during the game with geom_hline set at a median set at 58 kicks per game:

Kicks with geom_smooth:

Penalties and Free Kicks Conceded with geom_point with a geom_hline set at a median of 16 penalties and free kicks conceded per game:

Penalties and free kicks conceded presented with a geom_smooth function:

Lineouts and scrums have medians of 25 and 13 respectively per game:

Lineouts and scrums with a geom_smooth:

Photo Credit

Lineout Win (World Rugby)

Time at #FIFAWWC 2019

FIFA provided Match Facts for each of the games played at the 2019 Women’s World Cup (link). From these Facts is was possible to construct a time profile of the World Cup.

The data available suggest that the median ball in play time was 55 minutes. The median game time was 97 minutes. The ball was not in play for a median time of 43 minutes. Three of the games went to extra time (Norway v Australia, France v Brazil, Netherlands v Sweden).

Ball in Play ranged from 41 minutes (Germany v Nigeria) to 73 minutes (Norway v Australia).

The geom_smooth profile of ball in play was:

I used a smoothing method to look at trends in the time data (link). The grey area visualises confidence levels (95% confidence level interval for predictions from a linear model) . The confidence limits can be varied (link). In this example, I used Loess smoothing as I had less than 1000 data points.

The FIFA data made it possible to calculate ball not in play time.

In the Netherlands v Sweden game there were 63 minutes of time when the ball was not in play. This was an extra time game.

The total game length varied from 93 minutes (Japan v Scotland, Jamaica v Australia) to 135 minutes (France v Brazil). The three extra time games are indicated in red.

The FIFA data were particularly helpful in constructing time profiles of the games.. Data were presented for each half. Extra time data were included in the match report. As well as describing what occurred these data raise important questions about ball in play time.

Photo Credit

France v Brazil (FIFA Live Blog)