Posts from January 2026 (15)

Team Ratings for the Super Bowl

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 284 matches played, 172 of which were correctly predicted, a success rate of 60.6%.
Here are the predictions for last week’s games.

Predictions for the Super Bowl

Here are the predictions for the Super Bowl. 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 Week 11

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, 50 of which were correctly predicted, a success rate of 65.8%.
Here are the predictions for last week’s games.

Predictions for Week 11

Here are the predictions for Week 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 16

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 105 matches played, 85 of which were correctly predicted, a success rate of 81%.
Here are the predictions for last week’s games.

Predictions for Round 16

Here are the predictions for Round 16. 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

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 50 matches played, 37 of which were correctly predicted, a success rate of 74%.
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.

• From the BBC “Vitamin D deficiency linked to hospital admissions”. This is from a large British study correlating vitamin D levels in the blood with hospital admissions for respiratory infections. You might say “Someone ought to do a clinical trial to see if giving people vitamin D reduces infections or if  it’s just correlation”. Someone has, here in NZ. Also, if you combine all the trials on this question you get an estimate of somewhere between a 10% reduction and a 4% increase. It’s still possible that it works in people with especially low vitamin D or something, but across a range of diseases randomised clinical trials of vitamin D have been robustly disappointing in comparison to correlational studies.
• From Derek Lowe, a post on extremely bad clinical trial conduct. This isn’t fraud by Big Pharma — if it counts as fraud, Big Pharma is a victim (along with some, but possibly not all, of the trial participants)
• “A very detailed map of Trump’s job approval” from Strength In Numbers (click to embiggen). “The basic idea is that we fit a model predicting approval based on demographics and geography, then use Census data to weight those predictions by the actual population composition of each area. Election results are used to calibrate estimates to sensible baselines, so we have a real-world check against our survey data. It lets us produce reliable estimates even for places where we only have a handful of direct survey respondents.”
  
• From the Guardian, Australian supermarket online prices per each can be very different from the in-store per-kg prices. Most dramatically, green capsicums were allegedly 50% more expensive per each.
• Bogus polls show increases in church attendance by young adults: Pew Research

Right now, it is very cold in the central and eastern United States.  Minneapolis has been in the news (for this as well as the bad sort of ice), but it’s not just there. The Mayor of New York has warned locals about a major snowstorm (and suggested it would be a good time to stay home and borrow the e-book or audiobook of  Heated Rivalry from the city libraries). There’s freezing weather in parts of Texas that are really not built to handle it.

Various people, as usual, have said the cold weather refutes global warming.

As you all know, the issue with global warming  is that it’s global (there’s a hint in the name) rather than local.  I always recommend looking at global temperature patterns.  Here’s the global temperature anomaly, from Climate Reanalyzer, at the University of Maine

The map is based on today’s weather forecast around the world, averaged over 24 hours and compared to the average for the same day of the year from 1979 to 2000.  As you can see, it’s unusually cold in the USA. It’s also unusually cold in a band across Asia. On the other hand, it’s unusually warm in Greenland and the far north of North America and in Siberia.

This image shows a view around the north pole

You can see here the problem is that the cold that belongs up in the Arctic has slipped down over Asia and North America.  There isn’t extra cold in the world, it’s just in unusual places.  This sort of unusual movement of north polar air is perfectly consistent with global warming models.

Team Ratings for the Conference Finals

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 282 matches played, 170 of which were correctly predicted, a success rate of 60.3%.
Here are the predictions for last week’s games.

Predictions for the Conference Finals

Here are the predictions for the Conference Finals. 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 the Divisional Finals

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 278 matches played, 167 of which were correctly predicted, a success rate of 60.1%.
Here are the predictions for last week’s games.

Predictions for the Divisional Finals

Here are the predictions for the Divisional Finals. 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.

The top baby names from 2025 are out, together with historic data to look at trends. Sadly, the historic data for boys’ names and for girls’ names come as three-page PDF tables with very small print, not as some conveniently computer-readable or human-readable format.  We can still see some interesting trends

The top names last year were Noah for boys (244 times) and Isla for girls (179 times). There has always been more variability in girls’ names: there are always more boys with the most popular name than girls with the most popular name.

The total number of births in NZ has been broadly stable since the 1950s but the number of babies with the most popular name has steadily been decreasing, implying increasing name diversity. In 1954 there were 1389 Johns; in 1979 there were 707 Michaels; in 2004 there were 504 Joshuas. For girls, the numbers were 779 Christines in 1954, 578 Sarahs in 1979, and 352 Emmas in 2004.

There aren’t any names that appear in the top 100 for both boys and girls. There are few names that, over history, have been in both lists but I haven’t found any that were in both lists in the same year — the closest was Kim. a top-100 name for boys in 1961 and 1962 and for girls in quite a few years starting from 1968.

This was on a real-estate agent’s advertising leaflet at a local café

If you aren’t from around here, those are neighbourhoods in south central Auckland.

Statisticians often complain about pie charts because it’s hard to make numerical comparisons between the categories, especially compared to a bar chart

The poor visual comparison might actually be a virtue in this case if the point is just that these neighbourhoods are similar.  In any case, there’s a deeper problem: pie charts are fundamentally about the relationship between portions and a total — slices and the whole pie.  In this example there is no meaningful total that the separate medians are components of.  There isn’t a pie for these to be slices of.