August 8, 2017

NRL Predictions for Round 23

Team Ratings for Round 23

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.

Current Rating Rating at Season Start Difference
Storm 10.95 8.49 2.50
Broncos 7.45 4.36 3.10
Raiders 4.68 9.94 -5.30
Cowboys 4.41 6.90 -2.50
Panthers 2.90 6.08 -3.20
Sharks 2.51 5.84 -3.30
Eels 1.74 -0.81 2.50
Roosters 0.86 -1.17 2.00
Sea Eagles 0.08 -2.98 3.10
Dragons -2.02 -7.74 5.70
Rabbitohs -2.29 -1.82 -0.50
Wests Tigers -4.63 -3.89 -0.70
Warriors -4.87 -6.02 1.10
Bulldogs -6.48 -1.34 -5.10
Titans -7.60 -0.98 -6.60
Knights -9.75 -16.94 7.20

 

Performance So Far

So far there have been 160 matches played, 96 of which were correctly predicted, a success rate of 60%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Bulldogs vs. Eels Aug 03 4 – 20 -2.60 TRUE
2 Dragons vs. Rabbitohs Aug 04 24 – 26 4.90 FALSE
3 Cowboys vs. Storm Aug 04 8 – 26 -0.30 TRUE
4 Knights vs. Warriors Aug 05 26 – 10 -4.00 FALSE
5 Titans vs. Broncos Aug 05 0 – 54 -4.20 TRUE
6 Sharks vs. Raiders Aug 05 12 – 30 4.90 FALSE
7 Sea Eagles vs. Roosters Aug 06 36 – 18 -0.10 FALSE
8 Panthers vs. Wests Tigers Aug 06 28 – 14 10.40 TRUE

 

Predictions for Round 23

Here are the predictions for Round 23. 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 Aug 10 Rabbitohs 7.70
2 Eels vs. Knights Aug 11 Eels 15.00
3 Broncos vs. Sharks Aug 11 Broncos 8.40
4 Dragons vs. Titans Aug 12 Dragons 9.10
5 Storm vs. Roosters Aug 12 Storm 13.60
6 Panthers vs. Cowboys Aug 12 Panthers 2.00
7 Warriors vs. Raiders Aug 13 Raiders -5.50
8 Wests Tigers vs. Sea Eagles Aug 13 Sea Eagles -1.20

 

Mitre 10 Cup Predictions for Round 1

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.

Current Rating Rating at Season Start Difference
Canterbury 14.78 14.78 0.00
Tasman 9.54 9.54 0.00
Taranaki 7.04 7.04 0.00
Auckland 6.11 6.11 0.00
Counties Manukau 5.70 5.70 0.00
Waikato -0.26 -0.26 0.00
Otago -0.34 -0.34 0.00
North Harbour -1.27 -1.27 0.00
Wellington -1.62 -1.62 0.00
Manawatu -3.59 -3.59 0.00
Bay of Plenty -3.98 -3.98 0.00
Hawke’s Bay -5.85 -5.85 0.00
Northland -12.37 -12.37 0.00
Southland -16.50 -16.50 0.00

 

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.

Game Date Winner Prediction
1 North Harbour vs. Otago Aug 17 North Harbour 3.10
2 Tasman vs. Canterbury Aug 18 Canterbury -1.20
3 Hawke’s Bay vs. Southland Aug 19 Hawke’s Bay 14.70
4 Taranaki vs. Waikato Aug 19 Taranaki 11.30
5 Counties Manukau vs. Auckland Aug 19 Counties Manukau 3.60
6 Northland vs. Bay of Plenty Aug 20 Bay of Plenty -4.40
7 Manawatu vs. Wellington Aug 20 Manawatu 2.00

 

Currie Cup Predictions for Round 4

Team Ratings for Round 4

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.

Current Rating Rating at Season Start Difference
Cheetahs 5.69 4.33 1.40
Lions 5.25 7.41 -2.20
Blue Bulls 2.94 2.32 0.60
Western Province 2.55 3.30 -0.70
Sharks 2.48 2.15 0.30
Pumas -10.24 -10.63 0.40
Griquas -11.42 -11.62 0.20

 

Performance So Far

So far there have been 9 matches played, 8 of which were correctly predicted, a success rate of 88.9%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Sharks vs. Griquas Aug 04 41 – 3 17.10 TRUE
2 Blue Bulls vs. Lions Aug 05 54 – 22 0.40 TRUE
3 Western Province vs. Pumas Aug 05 34 – 19 17.70 TRUE

 

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.

Game Date Winner Prediction
1 Blue Bulls vs. Sharks Aug 09 Blue Bulls 5.00
2 Pumas vs. Cheetahs Aug 09 Cheetahs -11.40
3 Griquas vs. Western Province Aug 09 Western Province -9.50

 

Breast cancer alcohol twitter

Twitter is not an ideal format for science communication, because of the 140-character limitations: it’s easy to inadvertently leave something out.  Here’s one I was referred to this morning (link, so you can see if it is retracted)

latta

Usually I’d think it was a bit unfair to go after this sort of thing on StatsChat.  The reason I’m making an exception here is the hashtag: this is a political statement by a person of mana.

There’s one gross inaccuracy (which I missed on first reading) and one sub-optimal presentation of risk.  To start off, though, there’s nothing wrong with the underlying number: unlike many of its ilk it isn’t an extrapolation from high levels of drinking and it isn’t obviously confounded, because moderate drinkers are otherwise in better health than non-drinkers on average.  The underlying number is that for each standard drink per day, the rate of breast cancer increases by a factor of about 1.1.

The gross inaccuracy is the lack of a per day qualifier, making the statement inaccurate by a factor of several thousand.  An average of one standard drink per day is not a huge amount, but it’s probably more than the average for women in NZ (given the  2007/08 New Zealand Alcohol and Drug Use Survey finding that about half of women drank alcohol less than weekly).

Relative rates are what the research produces, but people tend to think in absolute risks, despite the explicit “relative risk” in the tweet.  The rate of breast cancer in middle age (what the data are about) is fairly low. The lifetime risk for a 45 year old woman (if you don’t die of anything else before age 90) is about 12%.  A 10% increase in that is 13.2%, not 22%. It would take about 7 drinks per day to roughly double your risk (1.17=1.94)  — and you’d have other problems as well as breast cancer risk.

 

August 7, 2017

Millennials and their pink wine

From Stuff, under  the headline Millennials love rose so much they’ve warped the traditional wine market

Millennials dominate Kiwi rose drinking, according to the report. Seventeen per cent of the still wine drunk by under-24s is rose . At 25-35 years it is about 11 per cent and at 35-44 years it drops to 6 per cent. 

Even if that’s true, younger people are less likely to be drinking wine than older people. Here are two graphs of the probability that the most recent alcoholic drink was wine, for women on the left and men on the right, by age groups (source).  The blue is under-24, then 25-44, 45-64, and 65+.

women-winemen-wine

A slightly larger proportion of the wine drunk by millennials is pink, but that’s not the same as saying they drink a large proportion of all the pink wine.

 

Stat of the Week Competition: August 5 – 11 2017

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 August 11 2017.
  • Statistics can be bad, exemplary or fascinating.
  • The statistic must be in the NZ media during the period of August 5 – 11 2017 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…)

August 5, 2017

Just a temporary inconvenience

From Radio NZ

The book explores the widely held view that farm livestock are responsible for an enormous net production of new global warming gases.

“Once you take into account the entire cycle of the life of a cow, it’s actually impossible for the cow to omit even one extra atom of carbon to the atmosphere that wasn’t there already there, they are carbon neural in the end.” he says.

As you’d expect, there’s a sense in which this is completely true. It’s just not a sense that contradicts the standard views of methane and global warming.

What’s going on is easier to see if you consider carbon outputs from the other end of the cow.  Some of the carbon a cow takes in comes out as cowshit. This carbon doesn’t lie around for ever; it returns to the skies and the soil as part of the Great Circle of Life. Hakuna Matata. This doesn’t happen instantaneously, though. In the short term, you still need to wear sensible footwear or watch your step when you cross the field.

There’s an equilibrium between the production and decay of cowshit. When you increase the number of cows, the ambient cowshit level increases, and settles in at a new, higher equilibrium. When you decrease the number of cows, it decreases towards a new, lower equilibrium. The time this takes is governed by how long cowshit takes to decay, so it’s pretty fast.

In a similar, but more serious way, some of the carbon that goes into a cow comes out the front end as methane.  The methane doesn’t hang around in the air for ever; it turns back into carbon dioxide and water. As with cowshit, this doesn’t happen instantaneously.

There’s an equilibrium between the production and decay of methane. When you increase the number of cows, the ambient cow-derived methane level increases, and settles in at a new, higher equilibrium. When you decrease the number of cows, it decreases towards a new, lower equilibrium. The time this takes is governed by how long methane takes to decay: over each passing decade about half of it goes away.

Carbon emitted as methane, unlike carbon emitted in cowshit, is more than a local nuisance.  Per atom of carbon, methane has 24 times the greenhouse warming effect of CO2, and while it doesn’t last for ever, it lasts long enough to make an important contribution to climate change.  There’s more than twice as much methane in the atmosphere now as there was two centuries ago.

Cows are long-term carbon-neutral: that means reducing cow numbers (or finding ways to reduce their methane production) would, in mere decades, roll back the increases they’ve caused in an important greenhouse gas.

August 2, 2017

Briefly

  • Graphics: there’s a solar eclipse soon in the US. Washington Post‘s WonkBlog shows Google Trends search interest in iteclipse
  • Persuasive Cartography: 800 historical maps “intended primarily to influence opinions or beliefs – to send a message – rather than to communicate geographic information.”
  • Should there even be an app for this?”  and other tech questions from a workshop on design ethics. (Subquestion: should there be a prediction of this?)
  • “I never knew until very recently that the standard National Readership Survey socio-demographic classifications – ABC1, C2DE etc – deal with pensioners by classifying them all as working-class unless they are rich enough to be considered independently wealthy and therefore bucketed in with the As. ” Alex Harrowell on social class assessment and the politics of data
August 1, 2017

Super 18 Predictions for the Super Rugby Final

Team Ratings for the Super Rugby Final

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.

Current Rating Rating at Season Start Difference
Hurricanes 16.71 13.22 3.50
Crusaders 14.85 8.75 6.10
Lions 14.49 7.64 6.90
Highlanders 10.62 9.17 1.50
Chiefs 9.62 9.75 -0.10
Brumbies 1.81 3.83 -2.00
Stormers 1.38 1.51 -0.10
Sharks 0.72 0.42 0.30
Blues -0.22 -1.07 0.90
Waratahs -3.81 5.81 -9.60
Bulls -4.96 0.29 -5.20
Jaguares -5.03 -4.36 -0.70
Force -6.97 -9.45 2.50
Cheetahs -9.63 -7.36 -2.30
Reds -9.92 -10.28 0.40
Kings -12.08 -19.02 6.90
Rebels -15.29 -8.17 -7.10
Sunwolves -19.38 -17.76 -1.60

 

Performance So Far

So far there have been 141 matches played, 106 of which were correctly predicted, a success rate of 75.2%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Crusaders vs. Chiefs Jul 29 27 – 13 8.00 TRUE
2 Lions vs. Hurricanes Jul 29 44 – 29 -0.00 FALSE

 

Predictions for the Super Rugby Final

Here are the predictions for the Super Rugby 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 Lions vs. Crusaders Aug 05 Lions 3.60

 

NRL Predictions for Round 22

Team Ratings for Round 22

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.

Current Rating Rating at Season Start Difference
Storm 9.57 8.49 1.10
Cowboys 5.79 6.90 -1.10
Sharks 4.27 5.84 -1.60
Broncos 3.76 4.36 -0.60
Raiders 2.92 9.94 -7.00
Panthers 2.58 6.08 -3.50
Roosters 2.27 -1.17 3.40
Eels 0.68 -0.81 1.50
Sea Eagles -1.33 -2.98 1.60
Dragons -1.45 -7.74 6.30
Rabbitohs -2.85 -1.82 -1.00
Warriors -3.32 -6.02 2.70
Titans -3.91 -0.98 -2.90
Wests Tigers -4.30 -3.89 -0.40
Bulldogs -5.42 -1.34 -4.10
Knights -11.30 -16.94 5.60

 

Performance So Far

So far there have been 152 matches played, 92 of which were correctly predicted, a success rate of 60.5%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Panthers vs. Bulldogs Jul 27 16 – 8 12.30 TRUE
2 Warriors vs. Sharks Jul 28 12 – 26 -1.60 TRUE
3 Eels vs. Broncos Jul 28 28 – 14 -2.10 FALSE
4 Knights vs. Dragons Jul 29 21 – 14 -8.80 FALSE
5 Rabbitohs vs. Raiders Jul 29 18 – 32 -0.10 TRUE
6 Roosters vs. Cowboys Jul 29 22 – 16 -1.20 FALSE
7 Storm vs. Sea Eagles Jul 30 40 – 6 10.80 TRUE
8 Titans vs. Wests Tigers Jul 30 4 – 26 8.50 FALSE

 

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.

Game Date Winner Prediction
1 Bulldogs vs. Eels Aug 03 Eels -2.60
2 Dragons vs. Rabbitohs Aug 04 Dragons 4.90
3 Cowboys vs. Storm Aug 04 Storm -0.30
4 Knights vs. Warriors Aug 05 Warriors -4.00
5 Titans vs. Broncos Aug 05 Broncos -4.20
6 Sharks vs. Raiders Aug 05 Sharks 4.90
7 Sea Eagles vs. Roosters Aug 06 Roosters -0.10
8 Panthers vs. Wests Tigers Aug 06 Panthers 10.40