Posts filed under General (556)

October 1, 2014

NRL Predictions for the Grand Final

Team Ratings for the Grand Final

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.

Current Rating Rating at Season Start Difference
Rabbitohs 11.81 5.82 6.00
Cowboys 9.46 6.01 3.40
Roosters 9.27 12.35 -3.10
Storm 4.47 7.64 -3.20
Broncos 3.86 -4.69 8.50
Panthers 3.49 -2.48 6.00
Warriors 2.82 -0.72 3.50
Sea Eagles 2.78 9.10 -6.30
Bulldogs 1.38 2.46 -1.10
Knights -0.28 5.23 -5.50
Dragons -2.10 -7.57 5.50
Raiders -7.64 -8.99 1.40
Eels -8.12 -18.45 10.30
Titans -8.40 1.45 -9.90
Sharks -10.92 2.32 -13.20
Wests Tigers -13.68 -11.26 -2.40

 

Performance So Far

So far there have been 200 matches played, 117 of which were correctly predicted, a success rate of 58.5%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Rabbitohs vs. Roosters Sep 26 32 – 22 6.30 TRUE
2 Panthers vs. Bulldogs Sep 27 12 – 18 4.00 FALSE

 

Predictions for the Grand Final

Here are the predictions for the Grand Final. 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.

Game Date Winner Prediction
1 Rabbitohs vs. Bulldogs Oct 05 Rabbitohs 10.40

 

Currie Cup Predictions for Round 9

Team Ratings for Round 9

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.

Current Rating Rating at Season Start Difference
Western Province 6.92 3.43 3.50
Lions 4.30 0.07 4.20
Sharks 3.44 5.09 -1.60
Cheetahs -1.79 0.33 -2.10
Blue Bulls -1.98 -0.74 -1.20
Pumas -6.17 -10.00 3.80
Griquas -9.54 -7.49 -2.00
Kings -14.49 -10.00 -4.50

 

Performance So Far

So far there have been 32 matches played, 24 of which were correctly predicted, a success rate of 75%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Cheetahs vs. Blue Bulls Sep 26 23 – 31 7.00 FALSE
2 Griquas vs. Lions Sep 27 8 – 46 -5.10 TRUE
3 Pumas vs. Western Province Sep 26 23 – 37 -7.20 TRUE
4 Sharks vs. Kings Sep 27 53 – 24 22.00 TRUE

 

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.

Game Date Winner Prediction
1 Griquas vs. Kings Oct 04 Griquas 10.00
2 Pumas vs. Blue Bulls Oct 04 Pumas 0.80
3 Cheetahs vs. Western Province Oct 04 Western Province -3.70
4 Sharks vs. Lions Oct 04 Sharks 4.10

 

ITM Cup Predictions for Round 8

Team Ratings for Round 8

Here are the team ratings prior to Round 8, 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.

Current Rating Rating at Season Start Difference
Canterbury 16.54 18.09 -1.50
Tasman 9.46 5.78 3.70
Auckland 4.43 4.92 -0.50
Taranaki 3.85 -3.89 7.70
Hawke’s Bay 3.14 2.75 0.40
Counties Manukau 3.13 2.40 0.70
Otago -0.99 -1.45 0.50
Wellington -1.84 10.16 -12.00
Waikato -4.62 -1.20 -3.40
Northland -5.01 -8.22 3.20
Manawatu -6.33 -10.32 4.00
Southland -6.66 -5.85 -0.80
North Harbour -7.20 -9.77 2.60
Bay of Plenty -9.96 -5.47 -4.50

 

Performance So Far

So far there have been 54 matches played, 34 of which were correctly predicted, a success rate of 63%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 North Harbour vs. Canterbury Sep 24 29 – 24 -27.60 FALSE
2 Bay of Plenty vs. Northland Sep 25 27 – 30 -0.50 TRUE
3 Taranaki vs. Auckland Sep 26 35 – 22 1.60 TRUE
4 Waikato vs. Manawatu Sep 27 20 – 22 7.20 FALSE
5 Counties Manukau vs. Wellington Sep 27 55 – 7 2.80 TRUE
6 North Harbour vs. Hawke’s Bay Sep 27 28 – 25 -10.40 FALSE
7 Tasman vs. Otago Sep 28 32 – 24 15.70 TRUE
8 Canterbury vs. Southland Sep 28 26 – 28 34.30 FALSE

 

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.

Game Date Winner Prediction
1 Hawke’s Bay vs. Wellington Oct 01 Hawke’s Bay 9.00
2 Auckland vs. Waikato Oct 02 Auckland 13.00
3 Northland vs. North Harbour Oct 03 Northland 6.20
4 Southland vs. Counties Manukau Oct 04 Counties Manukau -5.80
5 Bay of Plenty vs. Otago Oct 04 Otago -5.00
6 Canterbury vs. Tasman Oct 04 Canterbury 11.10
7 Manawatu vs. Hawke’s Bay Oct 05 Hawke’s Bay -5.50
8 Wellington vs. Taranaki Oct 05 Taranaki -1.70

 

September 26, 2014

Thomas Lumley at random

This from the latest Thomas Lumley Listener column: “Statistics uses both real and theoretical randomness for a lot of things, from selecting phone numbers in polling and allocating treatments in clinical trials, to proving that a set of mathematical assumptions does or doesn’t let you distinguish correlation from causation.

“So what do we think “random” really means?”

Read the column here.

 

September 24, 2014

NRL Predictions for the Preliminary Finals

Team Ratings for the Preliminary Finals

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.

Current Rating Rating at Season Start Difference
Rabbitohs 11.42 5.82 5.60
Roosters 9.66 12.35 -2.70
Cowboys 9.46 6.01 3.40
Storm 4.47 7.64 -3.20
Panthers 4.45 -2.48 6.90
Broncos 3.86 -4.69 8.50
Warriors 2.82 -0.72 3.50
Sea Eagles 2.78 9.10 -6.30
Bulldogs 0.42 2.46 -2.00
Knights -0.28 5.23 -5.50
Dragons -2.10 -7.57 5.50
Raiders -7.64 -8.99 1.40
Eels -8.12 -18.45 10.30
Titans -8.40 1.45 -9.90
Sharks -10.92 2.32 -13.20
Wests Tigers -13.68 -11.26 -2.40

 

Performance So Far

So far there have been 198 matches played, 116 of which were correctly predicted, a success rate of 58.6%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Roosters vs. Cowboys Sep 19 31 – 30 5.70 TRUE
2 Sea Eagles vs. Bulldogs Sep 20 17 – 18 3.20 FALSE

 

Predictions for the Preliminary Finals

Here are the predictions for the Preliminary 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.

Game Date Winner Prediction
1 Rabbitohs vs. Roosters Sep 26 Rabbitohs 6.30
2 Panthers vs. Bulldogs Sep 27 Panthers 4.00

 

Currie Cup Predictions for Round 8

Team Ratings for Round 8

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.

Current Rating Rating at Season Start Difference
Western Province 6.47 3.43 3.00
Sharks 2.98 5.09 -2.10
Lions 2.44 0.07 2.40
Cheetahs -0.88 0.33 -1.20
Blue Bulls -2.90 -0.74 -2.20
Pumas -5.72 -10.00 4.30
Griquas -7.69 -7.49 -0.20
Kings -14.04 -10.00 -4.00

 

Performance So Far

So far there have been 28 matches played, 21 of which were correctly predicted, a success rate of 75%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Lions vs. Pumas Sep 19 29 – 15 13.00 TRUE
2 Western Province vs. Griquas Sep 20 36 – 12 18.40 TRUE
3 Blue Bulls vs. Sharks Sep 20 15 – 26 0.60 FALSE
4 Kings vs. Cheetahs Sep 20 22 – 37 -7.10 TRUE

 

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.

Game Date Winner Prediction
1 Cheetahs vs. Blue Bulls Sep 26 Cheetahs 7.00
2 Griquas vs. Lions Sep 27 Lions -5.10
3 Pumas vs. Western Province Sep 27 Western Province -7.20
4 Sharks vs. Kings Sep 27 Sharks 22.00

 

Revised ITM Cup Predictions for Round 7

Reviewing the ratings I noticed I have been giving Wellington a ridiculously high rating given their disastrous performance this year. I discovered a problem with my code which meant I have not been updating ratings properly. I have some different code for the ITM Cup because of the strange nature of the fixtures where teams can play more than one game a week.

Team Ratings for Round 7

Here are the team ratings prior to Round 7, 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.

Current Rating Rating at Season Start Difference
Canterbury 21.23 18.09 3.10
Tasman 10.08 5.78 4.30
Auckland 5.32 4.92 0.40
Hawke’s Bay 4.02 2.75 1.30
Taranaki 2.96 -3.89 6.90
Wellington 1.25 10.16 -8.90
Counties Manukau 0.04 2.40 -2.40
Otago -1.62 -1.45 -0.20
Waikato -3.89 -1.20 -2.70
Northland -5.24 -8.22 3.00
Manawatu -7.06 -10.32 3.30
Southland -9.05 -5.85 -3.20
Bay of Plenty -9.73 -5.47 -4.30
North Harbour -10.37 -9.77 -0.60

 

Performance So Far

So far there have been 46 matches played, 30 of which were correctly predicted, a success rate of 65.2%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Southland vs. Tasman Sep 17 14 – 38 -13.30 TRUE
2 Northland vs. Taranaki Sep 18 20 – 31 -1.40 TRUE
3 Counties Manukau vs. Canterbury Sep 19 20 – 28 -13.50 TRUE
4 Hawke’s Bay vs. Bay of Plenty Sep 20 36 – 17 10.20 TRUE
5 Auckland vs. North Harbour Sep 20 32 – 7 18.50 TRUE
6 Manawatu vs. Southland Sep 20 41 – 20 -0.20 FALSE
7 Otago vs. Waikato Sep 21 38 – 7 1.60 TRUE
8 Wellington vs. Tasman Sep 21 20 – 42 0.10 FALSE

 

Predictions for Round 7

Here are the predictions for Round 7. 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.

Game Date Winner Prediction
1 North Harbour vs. Canterbury Sep 24 Canterbury -27.60
2 Bay of Plenty vs. Northland Sep 25 Northland -0.50
3 Taranaki vs. Auckland Sep 26 Taranaki 1.60
4 Waikato vs. Manawatu Sep 27 Waikato 7.20
5 Counties Manukau vs. Wellington Sep 27 Counties Manukau 2.80
6 North Harbour vs. Hawke’s Bay Sep 27 Hawke’s Bay -10.40
7 Tasman vs. Otago Sep 28 Tasman 15.70
8 Canterbury vs. Southland Sep 28 Canterbury 34.30

 

September 22, 2014

So, we had an election

Turnout of enrolled voters was up 3 percentage points over 2011, but enrollment was down, so as a fraction of the eligible population, turnout was only up half a percentage point.

From the Herald’s interactive, the remarkably boring trends through the count

There are a few electorates that are, arguably, still uncertain, but by 9pm the main real uncertainty at the nationwide level was whether Hone Harawira would win Te Tai Tokerau, and that wasn’t going to affect who was in government.  By 10pm it was pretty clear Harawira was out (though he hadn’t conceded) and that Internet Mana had been, in his opponent’s memorable phrase, “all steam and no hangi.”

Jonathan Marshall (@jmarshallnz) has posted swings in each electorate, for the party vote and electorate vote. He also has an interactive Sainte-Laguë seat allocation calculator and has published the data (complete apart from special votes) in a convenient form for y’all to play with.

David Heffernan (@kiwipollguy) collected a bunch of poll, poll average, and pundit predictions, and writes about them here. The basic summary is that they weren’t very good, though there weren’t any totally loony ones, as there were for the last US Presidential election. Our pundits seem to be moderately well calibrated to reality, but there’s a lot of uncertainty in the system and the improvement from averaging seems pretty small.  The only systematic bias is that the Greens did a bit worse than expected.

Based on his criterion, which is squared prediction error scaled basically by party vote, two single polls — 3 News/Reid at the high end and Herald Digipoll at the low end — spanned almost the entire range of prediction error.

The variation between predictions isn’t actually much bigger than you’d expect by chance. The prediction errors have the mean you’d expect from a random sample of about 400 people, and apart from two outliers they have the right spread as well. On the graph, the red curve is a chi-squared distribution with 9 degrees of freedom, and the black curve is the distribution of the 23 estimates. The outliers are Wikipedia and the last 3 News/Reid Research poll.

elections-dist

About half the predictions were qualitatively wrong: they had National needing New Zealand First or the Conservatives for a majority. The Conservatives were clearly treated unfairly by the MMP threshold. If someone is going to be, I’m glad it’s them, but a party with more votes than the Māori Party, Internet Mana, ACT, United Future, and Legalise Cannabis put together should have a chance to prove their unsuitability in Parliament.

 

September 21, 2014

Briefly

Data collection edition

  • Too Much Information:  Clemson University, in South Carolina, was “requiring students and faculty to complete an online course through a third party website that asks invasive questions about sexual history.
  • Too Little Information: New Zealand insurers are not willing to cooperate with price-comparison websites of the sort that exist elsewhere in the world.  These have led to lower prices where they have been introduced, but the insurers say their real concern is that people won’t get the most appropriate cover. (Herald today, Stuff back in March)
  • Just Right (maybe):  Apple says that with the new iOS8 operating system it is unable to unlock phones and decrypt data, and so will be able to refuse government demands to do so. Of course, the government can still grab lots of metadata, and as John Gilmore points out, there’s nothing but Apple’s bare word to go on.
September 19, 2014

Scotland gives 110%