Archives (240)

Team Ratings for Rounds 4 and 5 Postponed Matches

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 41 matches played, 28 of which were correctly predicted, a success rate of 68.3%.
Here are the predictions for last week’s games.

Predictions for Rounds 4 and 5 Postponed Matches

Here are the predictions for Rounds 4 and 5 Postponed Matches. 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 12 matches played, 7 of which were correctly predicted, a success rate of 58.3%.
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 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 63 matches played, 44 of which were correctly predicted, a success rate of 69.8%.
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 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 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.

Team Ratings for Round 10

So this year it is a constant battle to keep up with changes to schedules and I lost a skirmish last week with details of the postponed games. The predictions for last week are what I would have given if I had the match details correct.

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 56 matches played, 38 of which were correctly predicted, a success rate of 67.9%.
Here are the predictions for last week’s games.

Predictions for Round 10

Here are the predictions for Round 10. 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 6 matches played, 4 of which were correctly predicted, a success rate of 66.7%.
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 8

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 37 matches played, 27 of which were correctly predicted, a success rate of 73%.
Here are the predictions for last week’s games.

Predictions for Round 8

Here are the predictions for Round 8. 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 Mitre 10 Cup 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 74 matches played, 49 of which were correctly predicted, a success rate of 66.2%.
Here are the predictions for last week’s games.

Predictions for the Mitre 10 Cup Finals

Here are the predictions for the Mitre 10 Cup 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.

It’s quite difficult to exaggerate how bad the US coronavirus epidemic is. The Washington Post has managed.  They have a map showing the probability that a gathering of 10 local people for Thanksgiving will include at least one Covid case. They say

At the county level nationwide, the average estimated risk of running into a coronavirus-positive person at a 10-person gathering is just a hair under 40 percent. 

As the note on the map says, it assumes the actual case prevalence is 10 times the number of people with positive tests.  That’s a bit high — it comes from much earlier in the year, when testing was rarer).  It’s also a bit high if we assume that obviously unwell people (who are included in the prevalence estimate) are more likely to skip the celebration.

On top of that, though, the calculations (based on this paper) assume Covid infection status for the 10 participants is independent.  That was a reasonable approximation for the original paper, which looked at public gathering.  It’s not a great assumption for Thanksgiving, where people tend to attend in household groups.  The ‘effective’ gathering size will be less than the number of individuals, and closer to the number of households participating. So, if the prevalence is 1%, the risk based on three independent households is about 3%; the risk based on 10 independent people is about 10%. The truth will lie somewhere between.

And, as you can tell from looking at the map, there’s something wrong with saying the nationwide average risk is 40%, since 0-20% range includes nearly all the high-population parts of the US. The 40% is an average of counties, with no easy way to translate it into a risk for people.

Why am I pointing this out, when the map only strengthens the sensible public-health advice to stay the fuck away from Thanksgiving dinners? Because it is not true that 40% of the ten-person Thanksgiving gatherings in the US (and the vast majority of those in the Dakotas) should expect to come down with Covid this week, and people will notice that it wasn’t true. The truth doesn’t just matter for ethical reasons, it matters for any effective risk communication that isn’t just a one-shot attempt.

There’s a new study from Denmark that, if you don’t read carefully, looks like it has found evidence that masks don’t work to stop Covid. You’ll probably be hearing about it. [Update: on Newshub now] Here’s the NYTimes take.

The study randomly allocated 5000 people to wear masks or not, and found 42 people with antibodies to the Covid virus in the mask group and 53 in the no-mask group. From the abstract, the researcher concluded

The recommendation to wear surgical masks to supplement other public health measures did not reduce the SARS-CoV-2 infection rate among wearers by more than 50% in a community with modest infection rates, some degree of social distancing, and uncommon general mask use.

The results for actual diagnosed infection were a bit better: 5 vs 10.

Let’s look at the ‘limitations’ reported in the abstract

Inconclusive results, missing data, variable adherence, patient-reported findings on home tests, no blinding, and no assessment of whether masks could decrease disease transmission from mask wearers to others. [emphasis added]

So, based on a study that was too small, they argue that a mask doesn’t reduce your personal chance of being infected by more than half, and they didn’t look at whether it reduces your risk of infecting other people.

In NZ, our mask advice (and, from today, rules) is based on the benefits both ways, but more on reducing your risk to other people. Here’s the message from Toby Morris and Siouxsie Wiles

and

and

It’s hard to get rigorous evaluations of the benefits of masks. Most of the evidence we have comes from theory (it stops droplets, so it should reduce infection), from individual examples (eg two hair stylists who didn’t infect any of their clients), and from comparisons of trends between countries, states, and counties with different polices.

There are good reasons to believe masks reduce risk. It would be nice to have the sort of evidence we have for the new vaccines, but that’s not going to happen — and at least masks are safe and only slightly annoying.