Posts from March 2021 (28)

Team Ratings for Week 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 14 matches played, 10 of which were correctly predicted, a success rate of 71.4%.
Here are the predictions for last week’s games.

Predictions for Week 5

Here are the predictions for Week 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.

Team Ratings for Round 14

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, 41 of which were correctly predicted, a success rate of 57.7%.
Here are the predictions for last week’s games.

Predictions for Round 14

Here are the predictions for Round 14. 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 88 matches played, 59 of which were correctly predicted, a success rate of 67%.
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 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, 8 of which were correctly predicted, a success rate of 100%.
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.

Q: Did you see 90% of Covid deaths are due to obesity?

A: No

Q: It’s on Newshub: “90 percent or 2.2 million of the 2.5 million deaths from the pandemic disease so far were in countries with high levels of obesity.”

A: So, if that’s true, what countries are we talking about?

Q: With high levels of obesity? Australia, New Zealand, some of the Pacific Island nations, USA, UK,…

A: And what don’t those countries have in common?

Q: Lots of Covid deaths, I suppose.  But Australia and NZ and the Pacific Island countries didn’t have many deaths just because they didn’t have many cases. They don’t tell you anything about the risk

A: Neither does the ‘report’, which says, according to Newshub, “the majority of global COVID-19 deaths have been in countries where many people are obese, with coronavirus fatality rates 10 times higher in nations where at least 50 percent of adults are overweight”

Q: That sounds bad, though? Ten times higher is a lot!

A: How much do you think being overweight increases the risk of death?

Q: Well, if 50% overweight means ten times the risk, maybe a factor of twenty?

A: Yeah nah. Less than double, according to that very same report. (PDF, p13)

Q: So where do they get such a strong association?

A: Well, what are the main risk factors for dying of Covid?

Q: Um. Age?

A: And?

Q: Heart disease? Diabetes?

A:

Q:

A:

Q: Having Covid?

A: Exactly.  So we’d need to look at the proportion of infected people dying (the case fatality rate), not the total number of deaths, and we’d ideally want to compare countries with similar age profiles. Instead, Newshub shows us a graph of deaths, basically like this

Q: Why are some of the dots black?

A: They are countries that were missing from the Johns Hopkins Covid data, and so were missing from the original graph, mostly small nations like Samoa and Tonga and Timor-Leste with very few cases

Q: And what’s the dot on the left that isn’t in the graph on Newshub?

A: Afghanistan. I don’t know why it’s not there.

Q: So what about for risk of dying if you get Covid?

A: Here’s what it looks like for case fatality rate

Q: That’s…surprisingly unimpressive. Well, except for that one country…

A: Yemen

Q: Things they don’t need right now, number #1

A:  Too true.

Q: So the massive correlation?

A: Well, overweight is common in the USA, the UK, Brazil, and various other large countries that have handled the pandemic badly. While I suppose you could argue that handling the pandemic well should go with handling other public health issues well, the empirical evidence would not really be in your favour on that one.  You could also listen to a slightly different approach to the data from David Spiegelhalter and Tim Harford on BBC’s “More or Less”

• I wrote about how many people we need to vaccinate and why it’s complicated, at the Spinoff
• And an expanded version of this post about the Pfizer vaccine and obesity, for ‘Statisticians React to the News’, a blog of the International Statistical Institute
• While it’s true that basically no deaths and hospitalisations have been seen in the vaccinated groups in the vaccine trials, there haven’t been very many seen in the control groups either. As Hilda Bastian explains in the Atlantic, the trials were designed to see differences in symptomatic Covid, not serious/fatal Covid, and there are uncertainties about differences between the vaccines and about whether they are extremely effective or just very  effective. “It’s tempting to believe that a simple, decisive message—even one that verges on hype—is what’s most needed at this crucial moment. But if the message could be wrong, that has consequences.”
• The RECOVERY trial in the UK keeps churning out information about effectiveness of treatments for Covid based on large numbers of hospitalised patients. A new casualty: colchicine, a gout drug that appears beneficial in non-hospitalised patients in a smaller Canadian study.  RECOVERY is now expanding internationally, starting with Nepal and Indonesia
• “But there’s something else interesting here. The fear-and-stress argument is introduced with an historical account about a medieval experiment conducted by medieval Persian philosopher Avicenna / Ibn Sīnā. The story is *total bullshit.* Avicenna did no such experiment.”   from ‘Calling Bullshit’
• In one of Terry Pratchett’s Discworld books, there’s a personal organiser that does handwriting recognition. You show it a page of text, and it says “Yes, that’s handwiting, I’d recognise it anywhere”.  Something a bit similar is suggested by Police Commissioner Andrew Coster’s claim “There is no use of police photos for facial recognition unless it is someone who is an unidentified suspect for an offence.”. If that were true, the facial recognition system would be able to examine a photo and say “Yeah nah, don’t recognise him but he looks like a suspect “ but nothing more useful.  A facial recognition system needs basic training on faces (which is often problematic), a set of faces with known names (which is often problematic) , and a set of faces to recognise (which… well you get the idea). It matches the third to the second, using clues from the first about general face patterns.  With just the third group of photos, nothing much will happen.

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 132 matches played, 88 of which were correctly predicted, a success rate of 66.7%.
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.

Team Ratings for Week 4

If you happen to check back on my predictions for Week 3 you will see a different margin for the Brumbies against the Rebels, though still a win for the Brumbies. I had that game as a home game for the Rebels. I think it might have been switched because of Covid. The return game on April 18 seems to have been switched also. Super Rugby has it as a home game for the Rebels while some other sites still have it as home for the Brumbies.

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 10 matches played, 7 of which were correctly predicted, a success rate of 70%.
Here are the predictions for last week’s games.

Predictions for Week 4

Here are the predictions for Week 4. 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 13

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 65 matches played, 38 of which were correctly predicted, a success rate of 58.5%.
Here are the predictions for last week’s games.

Predictions for Round 13

Here are the predictions for Round 13. 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 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 82 matches played, 55 of which were correctly predicted, a success rate of 67.1%.
Here are the predictions for last week’s games.

Predictions for Round 15

Here are the predictions for Round 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.