The latest Team Dashboard appears below.
In a number of previous blogs here we've looked at the metrics on which each team is ranked highest and lowest. This week we add a completely new table for the blog, which looks at the ranking of each team across all of the metrics on the main Team Dashboard.
Teams in the table are ordered based on their current competition ladder ordering. You can see at a glance on which of the dashboard metrics each team is doing relatively well or poorly in comparison to its ladder position.
For example, Richmond, who sit 1st on the ladder, are a surprising 17th on Opponent Scoring Shot Conversion, while the Gold Coast, who lie second-last on the ladder, are an equally surprising 3rd on that same metric.
The columns here map in a fairly obvious way to columns on the main Team Dashboard excepting, perhaps, the last column, which uses the number of expected wins for each team based on the MoS Win Production Function.
At the foot of the table are the rank correlations between the teams' ladder positions and their ranking on the Dashboard metric in question.
- a correlation of +1 implies a perfect agreement between two sets of metric rankings
- a correlation of -1 implies a perfect agreement in that the team 1st on one metric is last on the other, and the team 2nd on one is second-last on the other, and so on.
- a correlation of 0 implies that there is no relationship at all between two sets of metric rankings (so knowing a team's ranking on one metric would give you no information by which to infer its ranking on the other)
We can see then, for example, that there is a high level of agreement between teams' ladder positions and their ranking on Scoring Shots Conceded, since the relevant correlation coefficient is +0.90. Conversely, there is almost no relationship at all between the teams' ladder positions and their ranking on Opponent Scoring Shot Conversion, since the correlation coefficient is -0.13.