Stats Chat

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 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 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 12

I missed predicting Round 11 last week, because of two games being played in the week. Same again this week it seems so I will give predictions for Round 13 after the completion of the Round 12 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 26 matches played, 15 of which were correctly predicted, a success rate of 57.7%.
Here are the predictions for last week’s games.

Predictions for Round 12

Here are the predictions for Round 12. 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 more than 90% of LGBTQ adults in the US have had the Covid vaccine?

A: How could you even know that?

Q: From Twitter. And! Yahoo! News!

A: But…

Q: It makes sense, right? LGBTQ+ people are less likely to be on the anti-vaccine side of US culture wars, and there’s community experience with health activism

A: But there are queer and trans people in Alabama, not just in San Francisco. And a significant homeless population

Q: But that’s what the survey says

A: Two words: sampling frame

Q: Ok, what’s a sampling frame?

A: It’s the list you work from when you sample people: a list of phone numbers or houses or email addresses or workplaces or whatever. It defines the population you’re going to end up estimating

Q: So they’d just need a list of all the LGBTQ+ people in the US

A:

Q: Ok, yes, that would be scary. How did they really do it?

A: They had a list of some of the LGBTQ+ people in the US (press release, PDF report)

Q: Where did they get the list?

A: “Research participants were recruited through CMI’s proprietary LGBTQ research panel and through our partnerships with over 100 LGBTQ media, events, and organizations.”

Q: That sounds like it might not be very representative

A:  “Because CMI has little control over the sample or response of the widely-distributed LGBTQ Community Survey, we do not profess that the results are representative of the “entire LGBTQ community.””

Q: Exactly.  It might be useful for marketing, but it seems like it’s not going to be representative. They’ll miss some big groups of people

A: “Instead, readers of this report should view results as a market study on LGBTQ community members who interact with LGBTQ media and organizations. CMI views these results as most helpful to readers who want to reach the community through LGBTQ advertising, marketing, events, and sponsorship outreach. Results do not reflect community members who are more closeted or do not interact much with LGBTQ community organizations. More than likely, bisexual community members are also underrepresented in the results.”

Q: When you’re talking in italics like that, does it mean you’re quoting the report?

A: It does. Or the press release

Q: Sounds like they have all the right disclaimers

A: The disclaimers fell off on the way to Yahoo! News! and Twitter, though.

• Siouxsie Wiles in Stuff today with a piece about different study designs in medical research and the hierarchy of evidence. Nice to see this from a lab scientist!
• Censuses: the data releases from the 2020 US Census showing changes in population and in race/ethnic composition: Washington Post, NY Times, LA Times
• Censuses: Australia is holding its census at the moment, which is not going to be good for data on commuting, but will be good for data on the pandemic
• Censuses: Australia has a very good statistical standard for sex and gender questions, but is strangely not using it for the census.
• It appears that machine learning systems can distinguish self-reported racial identity from x-ray images. People can’t, and it’s weird that it’s even possible. Blog post, twitter thread, research preprint. I’m not sure I believe this, but the research seems to have been fairly careful.
• Jonathan Marshall is doing graphs of vaccination in NZ. These show the data rounded to the nearest sixth of the population — having all the wedges filled means at least 92%ish vaccinated.
  

Team Ratings for Round 22

These predictions are preliminary only, because game locations are mainly listed as TBA. The only games on the NRL site with an actual location are the home games for the Broncos and Cowboys. Yesterday the NRL even had the Warriors playing at home in Auckland, so uncertainty abounds. I have treated all the TBA listed games as being played on neutral grounds, except the Rabbitohs versus Titans which I have predicted as if it were a home game for the Titans.

I will update later in the week if things change.

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, 116 of which were correctly predicted, a success rate of 72.5%.
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 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 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 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 10

I got caught again this week with the Sharks versus Bulls game, which was originally listed to be a home game for the Bulls, but in fact was played in Durban. I think it was thus the Round 6 game. I have changed the prediction to reflect the reality of where the game was played so that my ratings are properly updated for future predictions.

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 21 matches played, 12 of which were correctly predicted, a success rate of 57.1%.
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 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, 109 of which were correctly predicted, a success rate of 71.7%.
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.

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 9

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 18 matches played, 9 of which were correctly predicted, a success rate of 50%.
Here are the predictions for last week’s games.

Predictions for Round 9

Here are the predictions for Round 9. 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.