Stats Chat

Team Ratings for Round 5

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 12 matches played, 9 of which were correctly predicted, a success rate of 75%.
Here are the predictions for last week’s games.

Predictions for Round 5

Here are the predictions for Round 5. 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 November, I wrote

The Covid vaccine is safe and effective and it’s good that most eligible people are getting it. But how much protection does it give? If you look at the NZ statistics on who gets Covid, it seems to be extraordinarily effective: the chance of ending up with (diagnosed) Covid for an unvaccinated person is about 20 times higher than for a vaccinated person.

That’s probably an overestimate.

The issue was that during the Auckland Delta outbreak, unvaccinated people were probably more likely to be exposed to Covid than vaccinated people, and this was exaggerating the (real, but smaller) benefit of the vaccine.

Things have changed. The case diagnoses for vaccinated and unvaccinated people are about equal as a proportion of the population.  Partly this is because the vaccine is less effective against infection with Omicron, but now I think the social factors may well be leading to an underestimate of the vaccine benefit.  The point of the traffic-light system was to reduce virus exposure for unvaccinated people, both so they would be less likely to pass the virus on and so they’d be less likely to end up in hospital.  Reports in the news about unvaccinated people and about businesses that don’t like the system suggest that it does at least reduce the presence of unvaccinated adults in crowded indoor public settings.  You could reasonably expect, then, that unvaccinated adults are less exposed than vaccinated adults and that their equal case rate shows the vaccine is working.

In the absence of any other information it would be hard to decide how much to believe this explanation, but we do have other information. Other countries, with more cases and more data, have better estimates of the benefit of the vaccine than you can get from the published NZ data.  The vaccine does reduce infections with Omicron.  It doesn’t work as well as it did against Delta, and the benefit falls off more rapidly with time, but there is a benefit.   From the overseas data we’d expect the vaccine to working in New Zealand too, and the data we have are consistent with that expectation.

Even if we weren’t preventing cases of Omicron, there are at least two arguments for continuing to have vaccine rules. First, Delta is not actually gone — it’s still 5-7% of sequenced cases in MIQ and the community. It’s a small *fraction* of the outbreak, but the numbers haven’t gone down much. Second,  hospitalisation matters. As you may remember, we had hospitals even before Covid.  They’re important for treating everything from cancer to car crashes.  Keeping them available for non-Covid uses has always been a key motivation of the Covid strategy.

The numbers don’t decide anything; whether to change the rules is a policy question. But the inputs to policy should be the best estimates we can get of vaccine effectiveness, not the crude case counts.

• Stats NZ had to take down NZ.Stat, one of the main public interfaces to official statistics.  They’re being very helpful by email to people who need the data, but it’s a problem — and it’s not really the right interface for people who just wanted to look up a few numbers.  Eric Crampton wrote about why this matters (feel free to ignore the comments about wellbeing indicators)
• The NZ Open Source Assocation awards include one to the Ministry of Health for the Covid trace app, and to the University of Auckland Computational Evolution group for their phylogenetic inference software, BEAST
• Measuring things you don’t have any real way to interpret, from XKCD
  
• “Creepiness” Is the Wrong Way to Think About Privacy from Slate. It’s a useful heuristic, but it’s not an analysis.  As an illustration of how intuitions can be non-generalisable, the chair of George W. Bush’s bioethics council thought eating ice-cream in public was offensive.
• The power of selection bias: “In a series of tweets with an authentic February 7 timestamp, the self-described “industry insider working deep within Nintendo” showed an apparently deep foreknowledge of details that Nintendo wouldn’t officially reveal until the evening of February 9, two days later.”. He did it by making lots of predictions and then deleting all the ones that didn’t pan out.
• Tim Harford explains Arrow’s Impossibility Theorem: it’s hard to take a set of individual preferences and turn them into a group decision

Team Ratings for Week 15

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 71 matches played, 49 of which were correctly predicted, a success rate of 69%.
Here are the predictions for last week’s games.

Predictions for Week 15

Here are the predictions for Week 15. 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 18

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 115 matches played, 83 of which were correctly predicted, a success rate of 72.2%.
Here are the predictions for last week’s games.

Predictions for Round 18

Here are the predictions for Round 18. 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 1

A couple of comments for the start of this competition.

I have in the past have had reasonable success rating new teams at -10, and have done that this time. The Waratahs were a total disaster last year and rated -11. I don’t believe they will be worse than the new teams so did adjust their rating to -9. Even this may be viewing them a little negatively. Overall, be aware this is a new competition in a number of ways, and initially I may not achieve very good results.

I have predicted a result for the opening game involving Moana Pasifika, which seems unlikely to go ahead.

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 17

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 94 matches played, 51 of which were correctly predicted, a success rate of 54.3%.
Here are the predictions for last week’s games.

Predictions for Round 17

Here are the predictions for Round 17. 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.

For the past couple of years I’ve been arguing against Covid testing for people who don’t have symptoms and aren’t at high risk of exposure: they’ll have only a minute chance of testing positive, so we won’t learn anything, and we have better uses for the testing resources.  The only country that’s been doing systematic surveillance of Covid has been the UK, where the background prevalence has been, let’s say, somewhat higher than it had been here.

New Zealand is now getting a substantial Covid outbreak.  We’ll be over 1000 new cases some day soon, and it will start to matter for hospital planning purposes whether we’re detecting 20% of infections or 10% or 1% — because hospital numbers follow infection numbers with a long enough lag that the information is useful.

We’ve got two possible approaches to estimating the population Covid burden. One is wastewater testing, the other is random sampling.  Both approaches will keep working no matter how high the Covid prevalence is and no matter what fraction of infections are diagnosed and reported.  Sampling is more expensive, but has the advantage that it actually counts people rather than counting viruses and extrapolating to people.  Using both would probably help balance their pros and cons.

Sampling doesn’t have to be ‘simple random sampling’. If we know there’s more Covid in Auckland than in Oamaru, we can sample at a higher rate in Auckland and a lower rate in Oamaru.  We can also do adaptive sampling, where you take more samples in places where you find a hotspot.  Statistical ecologists trying to count plant and animal populations have studied this sort of problem quite a lot over the years — and statistical ecology is, fortunately, an area where NZ has expertise. But even simple random sampling would work, and would give us an estimate of infections and symptomatic cases across the country, and help plan the short to medium term response.

• Good discussion of the overinterpretation of opinion polls from Mediawatch. Hayden Donnell jokingly says “That is, of course, except for Mediawatch, which is the only truly objective outlet in town” — but like StatsChat, Mediawatch has the luxury of not commenting on stories where we don’t have anything to say.
• In contrast to well-conducted opinion polls, Twitter polls are completely valueless as a way of collecting and summarising popular opinion. This means that while they’re fine for entertainment (yay  @nickbakernz) and collecting reckons from your friends, it’s probably not a good idea to rage-retweet batshit political polls.  Let them get 37:0 in favour of banning arithmetic or whatever, rather than 37:1000 against.
• A summary of where the various non-profit Covid vaccines have got to, from Hilda Bastian
• One of the repeated themes of this blog is that you need to measure the right things if you’re going to base decisions on them.  The “Drug Harm Index” may not qualify here because it’s not clear decisions are made based on it, but it’s still worth looking at whether it measures harm the right way.  As Russell Brown points out, the index would say “that cannabis is New Zealand’s most harmful drug – accounting for $626 million in “community harm” every year. Would you be surprised if I told you more than a third of that was lost GST?”
• According to the MoH vaccination data, the vaccine roll-out for kids is going well on average, with 43% having had their first shot, but the differences by ethnicity are about the same as they were for adults. At the start of the Delta outbreak in August  (according to Hannah Martin at Stuff)  just over 40% of Aucklanders had had a first dose, 33% of Pacific people and 28% of Māori. That’s almost creepily close to the current situation with 5-11 year olds across the country now — the percentage for Māori being slightly lower this time.  Equity being a priority doesn’t seem to have had much impact.
  
• Interesting post from Pew Research on writing survey questions: in particular, ‘agree:disagree’ questions give you more ‘agree’ results than forced choice “pineapple or pepperoni” questions on the same issues.
• In New Zealand there are some issues with denominators for vaccination rates — the population that’s used undercounts minority groups.  This seems to be much worse in the UK: from Paul Mainwood on Twitter
  

Team Ratings for Postponed Games

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 111 matches played, 82 of which were correctly predicted, a success rate of 73.9%.
Here are the predictions for last week’s games.

Predictions for Postponed Games

Here are the predictions for Postponed Games. 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.