Posts from August 2018 (17)

Team Ratings for Round 25

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 184 matches played, 112 of which were correctly predicted, a success rate of 60.9%.
Here are the predictions for last week’s games.

Predictions for Round 25

Here are the predictions for Round 25. 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, 9 of which were correctly predicted, a success rate of 64.3%.
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 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.
Note that Cheetahs2 refers the Cheetahs team when there is a Pro14 match. The assumption is that the team playing in the Pro14 is the top team and the Currie Cup team is essentially a second team.

Performance So Far

So far there have been 5 matches played, 4 of which were correctly predicted, a success rate of 80%.
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.

When government policies change in different ways in different parts of the country, you can try to estimate the impact of the changes by comparing trends in affected and unaffected areas.  This week I’ve seen two examples, one in the NZ media and one from a Twitter request.

Chris Knox, in the Herald, has both an interactive graph and a story about the changes in petrol prices, using data from Gaspy. There was a clear jump of 11.5c/litre when the 11.5c/litre tax was increased.  What’s not so clear is whether petrol companies have subsequently tried to spread the price rise to other parts of the country.  Averaged over the whole rest of the country the gap has narrowed from the 11.5c start, but that’s driven by the South Island.  In the Waikato and Bay of Plenty regions, which were previously the most similar to Auckland, there’s no sign of price spreading.

So, right now, it’s unclear whether Auckland is bearing the whole cost (as it should) or just most of it.  The Herald story makes this fairly clear, quoting the economist Sam Warburton, who has been looking at the data — but also quoting someone who doesn’t need data to be sure that the costs are being borne by the regions. A similar analysis was done by Peter Ellis, using Sam Warburton’s data from pricewatch.co.nz, with basically similar conclusions.

The other example from this week is a research paper looking at how fatal workplace injuries changed in US states that introduced medical cannabis laws. They found a decrease starting at the time of legislation and slowly increasing to about a 1/3rd reduction after five years, compared to states without legal medical cannabis.  The analysis looks sensible and the data on fatal workplace injuries are of high quality, but there’s still a bit of potential concern about publication bias — the researchers might have published a negative result, but I wouldn’t have heard about it and told you.  I’ve written before about an analysis that suggested banning single-use plastic bags caused deaths from food poisoning —  and while the analysis looked reasonable it was clear based on additional data that the conclusion wasn’t plausible.

On the cannabis issue what’s most unclear is the contribution of various possible reasons to the reduction (if it is real):

• medical cannabis works to treat, say, pain or nausea, so people are healthier and better rested and don’t get injured
• medical cannabis substitutes for legal or illegal opioid use, and while it might increase injury risk compared to nothing, it’s better than opioids
• medical cannabis ends up in recreational use and substitutes for alcohol, and while it might increase injury risk compared to nothing, it’s better than alcohol
• medical cannabis ends up in recreational use and substitutes for alcohol, and people are less likely to use at work.
• it actually makes you safer

To the extent that the second reason is important in the US, where there’s an opioid use epidemic, it won’t generalise to New Zealand. The other reasons would probably generalise.

Team Ratings for Round 24

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 176 matches played, 106 of which were correctly predicted, a success rate of 60.2%.
Here are the predictions for last week’s games.

Predictions for Round 24

Here are the predictions for Round 24. 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.

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.
Note that Cheetahs2 refers the Cheetahs team when there is a Pro14 match. The assumption is that the team playing in the Pro14 is the top team and the Currie Cup team is essentially a second team.

Performance So Far

So far there have been 2 matches played, 1 of which were correctly predicted, a success rate of 50%.
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.

This year’s census already been the subject of some news reports, some of which have quoted me.  I’ve now been appointed to an external data quality panel advising StatsNZ,  and I will be much more limited in what I can say in the future here or to journalists.  That’s partly just ordinary confidentiality to make the panel discussions work effectively, and partly because we’ll be seeing unreleased data whose disclosure is prohibited by the Statistics Act.

Team Ratings for Round 1

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.

Note that Cheetahs2 refers to the Cheetahs team when there is a Pro14 match. The assumption is that the team playing in the Pro14 is the top team and the Currie Cup team is essentially a second team.

Predictions for Round 1

Here are the predictions for Round 1. 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.

• From the Guardian: Mapping the world’s cities where you can live comfortably without heating or air conditioning reveals how few boast such ideal climates.  Among the cities that apparently don’t need heating or AC are Auckland and Melbourne.  Not entirely convincing.
• From the Herald:  Scientists accidentally discover pill which could stop weight gain. What they actually discovered was a way to genetically engineer mice not to gain weight.  There’s a drug used to treat glaucoma that affects the same biochemical mechanism that the genetic engineering did — but it’s used as eyedrops to treat glaucoma, so that’s not great evidence it would be safe and effective as a pill.
• Peter Ellis has been analysing petrol-price data after the Auckland tax was imposed: “after the spike caused by the tax, fuel prices in Auckland and in the rest of the country are converging somewhat (although much less than the full cost of the tax), and plausibly this is because of companies’ price adjustments down in Auckland and up elsewhere to spread the cost of the tax over a broader base.”
• I’ve written a program to produce a map of Wellington-area buses showing how many are late.  It’s not quite real-time; it shows roughly the past hour. The map is here (you can click on the markers); the (more-technical) blog post explaining how it works is here.