Adelaide will play Carlton in the 2019 AFLW Grand Final (link) at the Adelaide Oval on Sunday, 31 March.
I have been collecting secondary data of points scoring from the official AFLW site (link) and have been thinking about what kind of final we might have.
I am particularly interested in the robustness of median performance profiles and the possibility of estimating some naive priors.
Points Scoring
Points Conceding
Points Difference
Data
The data include naive priors for performance in the Final in attack and defence with which to monitor each team’s tactical response to opponent and within game adaptation.
Centre lines show the medians. Box limits indicate the 25th and 75th percentiles. Whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles. Outliers are represented by dots.
This is my third season of collecting performance information from the official AFLW website. I have been struck by the increasing amount of coverage given to the tournament and the quality of the media images being shared.
This post is headed by Michael Wilson‘s photograph of Tayla Harris. I think it is a wonderful picture and speaks to the athleticism of AFLW.
Researchers have some important decisions to make about the ways they share their discoveries.
Back in 2017, I was struck by Biecek Przemysław and Marcin Kosiński’s discussion of the use of the R package archivist (link). They discussed the opportunities we have to enable auditable and replicable analysis. Two years earlier, Data Carpentry facilitated a Reproducible Research in R workshop (link).
This week ,two finds have sent me off thinking about the explicit sharing of research journeys and discoveries.
The first find was Stencila, an open source project, that aims to make reproducible research more accessible (link). I noted that “Stencila provides a set of open-source software components enabling researchers to enable reproducible research … using interactive source code”.
I found Stencila through a link to Giuliano Maciocci, Michael Aufreiter and Nokome Bentley’s (2019) paper Introducing eLife’s first computationally reproducible article (link). This exemplifies the potential of a Reproducible Document Stack approach to open sharing. Researchers can use their existing word processing and spreadsheet tools and can embed R and Python code blocks that can generate live interactive plots using the Plotly.js library. Stencila uses the Mini formula language (link).
A second find, thanks to a Stephen Downes’ alert, was Alice Meadows, Laurel Haak and Josh Brown’s (2019) discussion of persistent identifiers (link). They note persistent identifiers “for people (researchers), places (their organizations) and things (their research outputs and other contributions) are foundational elements in the overall research information infrastructure”.
They add:
Supporting research includes supporting the research information infrastructure: the tools and services that researchers use which enable them to spend more time doing research and less time managing it – as well as the virtual building blocks on which those tools and services depend, such as metadata, standards and, the topic of this article, persistent identifiers (PIDs).
Meadows, Alice, Laurel L. Haak, and Josh Brown. 2019. “Persistent Identifiers: The Building Blocks of the Research Information Infrastructure”. Insights 32 (1): 9. DOI: http://doi.org/10.1629/uksg.457
I have mentioned before that one of my founding ideas for the International Journal of Performance Analysis in sport was to enable a paper in any language (with an English abstract or summary) that shared openly video and data resources. At that time the platforms available did not permit open sharing.
This week has brought back those memories of a global community sharing research journeys. It must be profoundly exciting entering the research community now or transforming existing practices as we become much more transparent about these journeys.
