Time of Possession: technical aspects

This blog post summarizes the technical details of how the data and graphics in Analyzing time of Possession in 7s were generated. Writing that blog post was an educational exercise to get familiar with the Python statistical programming ecosystem. Up until this point, most of the analysis work at Starting 7s was conducted in the R programming language. Inspired by the words of educational technologist Seymour Papert*, who famously said “You can’t think seriously about thinking without thinking about thinking about something,” this analysis and blog post were conducted in a similar spirit. You can’t seriously learn to use a new tool without learning to use the new tool to do something.

The remainder of this blog post describes the tools and techniques used to conduct the possession analysis in Python.

* Perhaps not coincidentally, it is worth noting that Seymour Papert was South African, and occasionally used rugby examples to animate his thought experiments.

Continue reading Time of Possession: technical aspects

Visualizing directional tackle data


Sports coaches are not always interested in the statistics, graphs, and charts that their analysts produce. However, in my experience, rugby and American football coaches are always interested in tackle data.  One on one tackling is the cornerstone of team defense in both sports. Missed tackles lead to big plays. They are usually the difference between a good and bad defense. So it is easy to understand why coaches are so interested in tackle data. But assessing tackle performance is notoriously difficult.

Starting 7s recently published an article on Rpubs describing an approach to visualizing tackle data. It categorizes tackle attempts by the clock face number that corresponds to the tackler’s tracking angle relative to the ball carrier. We plot the data using polar coordinate charts that map tackles to their corresponding clock face numbers. Using this approach coaches can quickly see where the majority of their team’s — or their opponent’s — tackle attempts are made and missed.

Continue reading Visualizing directional tackle data