Posts from February 2020 (15)

Team Ratings for Round 12

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 76 matches played, 58 of which were correctly predicted, a success rate of 76.3%.
Here are the predictions for last week’s games.

Predictions for Round 12

Here are the predictions for Round 12. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 11

I missed posting predictions for this round thinking that there was a longer break between games. Because I use an algorithm and code and no subjective analysis, these predictions are exactly what I would have posted and I am posting them now for completeness.

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 70 matches played, 54 of which were correctly predicted, a success rate of 77.1%.
Here are the predictions for last week’s games.

Predictions for Round 11

Here are the predictions for Round 11. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 3

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 14 matches played, 8 of which were correctly predicted, a success rate of 57.1%.
Here are the predictions for last week’s games.

Predictions for Round 3

Here are the predictions for Round 3. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 2

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 7 matches played, 5 of which were correctly predicted, a success rate of 71.4%.
Here are the predictions for last week’s games.

Predictions for Round 2

Here are the predictions for Round 2. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Back in early December, I wrote about a political ad authorised by Simon Bridges, showing the price of fuel.

As I said the, the numbers do not remotely match the graph.  A graph using those numbers would look more like

Dylan Reeve and other people complained to the Advertising Standards Authority, both about the graph itself and about the choice of numbers, which (in his opinion and mine) was cherrypicked in a misleading way.

The ASA decided (in a split decision) that the graphic was not misleading

The majority said the data displayed was correct which saved the hyperbolic graphic from being misleading, given the political medium used and the principles of advocacy advertising.

I believe this is decision is bad in terms of norms for mainstream political advertising, and that it’s likely to be factually incorrect as to the impact of the graphic.

The cherrypicked numbers are misleading, but they are misleading in a way that is, sadly, routine in political advertising.  I’ve written about examples from both parties here since StatsChat started. My starting point for any political advocacy involving numerical comparisons is always that the numbers are likely to be correct as quoted, but chosen to mislead. Given the established norms,  I can understand the ASA not wanting to get involved.

The distorted graph, on the other hand, seems to be new.  I was genuinely surprised at the extent of the distortion — well beyond common tricks of perspective or false baseline.

If writing the numbers on a misleading graph was enough to stop it being misleading, there would be no point having data graphics.  The whole point of data graphics is that they provide a clearer and more forceful impression of the data than just tabulating the numbers.  Misleading graphs are misleading.