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Tag: Netball

Using Shiny

Mitch Mooney (link) has created a Shiny application for netball. He has aggregated and curated 12,500 data points from publicly available sources. Shiny is an R package that makes it possible to build interactive web apps straight from R. Mitch's Shiny application is a remarkable resource for netball and it provides us with an important example of how to collect and share data. I see it (link) as a great way to support user interaction and inquiry. It is for me a powerful...

Super Netball 2019

The Super Netball 2019 season started this weekend (link). My data for the 2017 and 2018 seasons are: Photo Credit NSW Swifts (Twitter)

Netball Quad Series September 2018

I used BoxPlotR to visualise the scores by quarter in the 2018 Netball Quad Series that concluded today. The four teams in the series were: Australia, England, New Zealand and South Africa. The centre lines show the medians; box limits indicate the 25th and 75th percentiles as determined by R software; whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles, outliers are represented by dots; data points are plotted as open circles. n = 6 sample points. Winning teams in light blue, losing teams in light green. Photo Credit Australian Diamonds (Twitter)

2018 Netball #QuadSeries in South Africa

The Netball Quad Series concluded at the weekend in South Africa. The teams in the tournament were: Australia, England, New Zealand and South Africa. Champion Data provided data for the tournament. I have used their data for my secondary analysis. My record of the six games as a box plot (using BoxPlotR) for winning teams per quarter (light green) and losing teams per quarter (light blue): The centre lines show the medians; box limits indicate the 25th and 75th percentiles as determined by R software; whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles, outliers are represented by...

Visualising Performance Data: #ENGvAUS Netball Test Series 2016

I have been following the three-match netball test series in England. Australia won the series 3v0. I found Champion Data's record of the games very helpful. In advance of more interactive visualisations, I am sharing a box plot of goals scored in the 12 quarters played. I used BoxPlotR to generate this visualisation. (In this plot, centre lines show the medians; box limits indicate the 25th and 75th percentiles as determined by R software; whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles; data points are plotted as open circles. n = 12 sample points.) I have been thinking about random...

#NWC2015: secondary data analysis, scenarios and consequences

Introduction The volume and quality of data made available online from international sporting events is making secondary data analysis more possible. I tend to look at data that do not have too complicated operational definitions but that permit some granularity. Champion Data are provide the data services to the 2015 Netball World Cup in Australia. Champion Data have worked with netball since 2009. We are into the second week of competition and into the Qualification Phase of matches. Scoring Patterns Champion Data offer the following choices in looking at game data (a grab from the Australia v England game): I used the 'All' and 'Scoring'...

Home Ground, Home Advantage

I have been thinking about home a great deal lately.  In May I wrote about my hometown memories and the experience opened me up to other narratives about home. Three items (see Talking About Home below) have attracted my attention recently just at a time when I am talking with coaches about planning their competition programs. These coaches are involved in 'home' and 'away' fixtures and we have been discussing what home advantage might mean in performance terms. Sport There is a fascinating research literature about home advantage. In the last decade there has been discussion of: Association Football (2010, 2009,...