Posts from August 2022 (17)

Team Ratings for Week 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 8 matches played, 5 of which were correctly predicted, a success rate of 62.5%.
Here are the predictions for last week’s games.

Predictions for Week 2

Here are the predictions for Week 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 22

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 160 matches played, 108 of which were correctly predicted, a success rate of 67.5%.
Here are the predictions for last week’s games.

Predictions for Round 22

Here are the predictions for Round 22. 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 Wednesday Game for Round 1

Because of the unusual scheduling of games in the NPC, I will be giving a forecast for the Wednesday game on a Tuesday and forecasts for the weekend games after the Wednesday game.

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, 4 of which were correctly predicted, a success rate of 57.1%.
Here are the predictions for last week’s games.

Predictions for Wednesday Game for Round 1

Here are the predictions for Wednesday Game 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.

• There’s a new version of ESR’s Wastewater Covid dashboard. It has information on which variants are being found, by location and over time
• Hashigo Zake, the Wellington craft beer bar, has a new Twitter bot tweeting out the CO2 concentration inside the bar. I summarised a couple of days of it:
  
• How far can you go by train in 5 hours? A map of Europe
• How likely are people to win the lottery: the Washington Post did a quiz
• Jamie Morton in the Herald has a good discussion of the Stats NZ review of the population denominator used in Covid vaccine stats.  The HSU undercounts somewhat, especially for Māori and Pacific Peoples, but it has the virtue of counting ethnicity the same way that the vaccination data does, and of including people in NZ who are not residents.

Team Ratings for Week 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.

Predictions for Week 1

Here are the predictions for Week 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.

Team Ratings for Round 21

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 152 matches played, 102 of which were correctly predicted, a success rate of 67.1%.
Here are the predictions for last week’s games.

Predictions for Round 21

Here are the predictions for Round 21. 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.

Radio NZ reported an estimate by the charity Orange Sky “One in six kiwis have been homeless and tonight about 41,000 of us will bed down without adequate access to housing”.  I saw some skepticism of these figures on Twitter, so let’s take a look.

Based on the 2018 Census, researchers at the University of Otago estimated

• 3,624 people who were considered to be living without shelter (on the streets, in improvised dwellings – including cars – and in mobile dwellings). 
• 7,929 people who were living in temporary accommodation (night shelters, women’s refuges, transitional housing, camping grounds, boarding houses, hotels, motels, vessels, and marae). 
• 30,171 people who were sharing accommodation, staying with others in a severely crowded dwelling. 
• 60,399 people who were living in uninhabitable housing that was lacking one of six basic amenities: tap water that is safe to drink; electricity; cooking facilities; a kitchen sink; a bath or shower; a toilet.

So, the figure of 41,000 is a surprisingly close match to the Census data for those first three groups — if you’d only count the first group or the first two, you would obviously get a smaller number.  Because it would be hard to estimate current homelessness from a YouGov survey panel, I suspect the number did come from the Census,  and the ‘new study’ the story mentions is responsible for the ‘one in six’, though Orange Sky actually gives the number as ‘more than one in five (21%)’.

Do the two figures match? Well, if about a million people had ever been homeless (in the broad sense) and 41,000 currently are, that’s a ratio of 25.  The median age of adults (YouGov interviews adults) is probably in the 40s, so if the typical person who was ever homeless spent less than a couple of years homeless the figures would match.  The People’s Project NZ say that homelessness in NZ is mostly short-term — in the sense that most people who are ever homeless are only that way for a relatively short time (which isn’t the same as saying most people who are currently homeless will be that way for a short time).

So, the figures aren’t obviously implausible, and given that they’re presented as the result of research that should be able to get reasonable estimates, they may well be reasonably accurate.