Posts from September 2014 (43)

Team Ratings for Finals Week 1

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 192 matches played, 113 of which were correctly predicted, a success rate of 58.9%.

Here are the predictions for last week’s games.

Predictions for Finals Week 1

Here are the predictions for Finals 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 6

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 20 matches played, 15 of which were correctly predicted, a success rate of 75%.

Here are the predictions for last week’s games.

Predictions for Round 6

Here are the predictions for Round 6. 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 5

Here are the team ratings prior to Round 5, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

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 30 matches played, 18 of which were correctly predicted, a success rate of 60%.

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.

As we point out from time to time, single polls aren’t very accurate and you need sensible averaging.

There are at least three sets of averages for NZ:

1. Peter Green’s analyses, which get published at DimPost (larger parties, smaller parties). The full code is here.

2. Pundit’s poll of polls. They have a reasonably detailed description of their approach and it follows what Nate Silver did for the US elections.

3. Curiablog’s time and size weighted average. Methodology described here

The implementors of these cover a reasonable spectrum of NZ political affiliation. The results agree fairly closely except for one issue: Peter Green adds a correction to make the predictions go through the 2011 election results, which no-one else does.

According to Gavin White, there is a historical tendency for National to do a bit worse and NZ First to do a bit better in the election than in the polls, so you’d want to correct for this, but you could also argue that the effect was stronger than usual at the last election so this might overcorrect.

In addition to any actual changes in preferences over the next couple of weeks, there are three polling issues we don’t have a good handle on:

• Internet Mana is new, and you could make a plausible case that their supporters might be harder for the  pollers to get a good grip on (note: age and ethnicity aren’t enough here, the pollers do take account of those).
• There seems to have been a big increase in ‘undecided‘ responders to the polls, apparently from former Labour voters. To the extent that this is new, no-one really knows what they will do on the day.
• Polling for electorates is harder, especially when strategic voting is important, as in Epsom.

[Update: thanks to Bevan Weir in comments, there’s also a Radio NZ average. It’s a simple unweighted average with no smoothing, which isn’t ideal for estimation but has the virtue of simplicity]

• Interesting maps: a Moral Topography of Portland “The [1913] report found, specified per type of dwelling, only 22 of 80 apartments, merely 5 out of 59 hotels and no more than 71 out of 408 rooming and lodging houses to be ‘moral’.”  If you cynically expected that “immoral” didn’t refer to racial discrimination, rent-gouging, unhygienic conditions, or lack of fire escapes, you were right. (via consumerist.com)

• An interactive display of US lifetime earnings for various groups by education and gender. The underlying data are good, but there’s inevitably an assumption that the correlations with education are broadly a result of education (including social status and networking effects) rather than selection for existing differences.

• The Royal Statistical Society is launching a pro bono statistics scheme, in collaboration with the existing Statistics Without Borders and Datakind UK

Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.

Here’s how it works:

• Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday September 12 2014.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of September 6 – 12 2014 inclusive.
• Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.

Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.

(more…)

If you’d like to comment on or debate any of this week’s Stat of the Week nominations, please do so below!

Team Ratings for Round 26

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 184 matches played, 107 of which were correctly predicted, a success rate of 58.2%.

Here are the predictions for last week’s games.

Predictions for Round 26

Here are the predictions for Round 26. 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 4

Here are the team ratings prior to Round 4, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

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 22 matches played, 13 of which were correctly predicted, a success rate of 59.1%.

Here are the predictions for last week’s games.

Predictions for Round 4

Here are the predictions for Round 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 5

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 16 matches played, 14 of which were correctly predicted, a success rate of 87.5%.

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.