Posts from November 2020 (25)

November 3, 2020

Pro14 Predictions for Round 5

Team Ratings for Round 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.

Current Rating Rating at Season Start Difference
Leinster 17.70 16.52 1.20
Munster 9.27 9.90 -0.60
Ulster 5.68 4.58 1.10
Edinburgh 4.88 5.49 -0.60
Glasgow Warriors 4.57 5.66 -1.10
Scarlets 1.68 1.98 -0.30
Connacht 1.08 0.70 0.40
Cardiff Blues 0.60 0.08 0.50
Cheetahs -0.46 -0.46 0.00
Ospreys -2.48 -2.82 0.30
Treviso -3.87 -3.50 -0.40
Dragons -8.69 -7.85 -0.80
Southern Kings -14.92 -14.92 0.00
Zebre -15.02 -15.37 0.30

 

Performance So Far

So far there have been 23 matches played, 15 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 Dragons vs. Munster Nov 02 16 – 28 -11.30 TRUE
2 Scarlets vs. Edinburgh Nov 02 3 – 6 4.70 FALSE
3 Cardiff Blues vs. Ulster Nov 03 7 – 11 2.60 FALSE
4 Zebre vs. Ospreys Nov 03 23 – 17 -7.10 FALSE
5 Glasgow Warriors vs. Leinster Nov 03 19 – 32 -5.20 TRUE

 

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.

Game Date Winner Prediction
1 Treviso vs. Munster Nov 08 Munster -6.60
2 Dragons vs. Connacht Nov 08 Connacht -3.30
3 Ospreys vs. Leinster Nov 09 Leinster -13.70
4 Scarlets vs. Zebre Nov 09 Scarlets 23.20
5 Edinburgh vs. Cardiff Blues Nov 10 Edinburgh 10.80
6 Ulster vs. Glasgow Warriors Nov 10 Ulster 7.60

 

Do first home buyers cause housing shortages?

From a story by Eva Corlett at Radio NZ

Property Investors Federation’s executive officer Sharon Cullwick argued while property investors may not be helping the housing supply problem, they aren’t hindering it.

But she said first home buyers are, when it comes to purchasing rentals off the market.

“If a first home buyer purchases a property that was a rental property, then you’ll need another house to house the extra people living in that rental house.”

“So every time a first home buyer buys a house even though it’s great they are getting into the market – it actually makes the housing crisis worse,” she said.

This is obviously a convenient thing for the Property Investors Federation to believe, so it’s worth looking at the evidence.  It’s true that property investors, as investors, aren’t reducing the housing supply (just the housing for sale and perhaps its affordability).  But are first home buyers?

Clearly[citation needed]  rental houses don’t just disappear, like those mysterious shops selling magical artefacts, when the renters move out and buy a house.  For every rental house that we lose, an owner-occupied house is created; to first order, nothing changes.

The claim being made is more subtle. We know that owner-occupied homes have fewer people living in them, on average, than rented homes.   If that difference is directly caused by being owner-occupied, then having more home owners would cause a reduction in average household size. While it wouldn’t cause a decrease in housing supply, it would increase the gap between demand and supply.

We can assume for the sake of argument that this isn’t primarily due to different sorts of homes being rented vs owner-occupied and say that, on average, a given home will have more people (or, at least, more adults) living in it if it is being rented than if it is being occupied by the owner.  Even stipulating all that doesn’t actually settle the question.

What we’re talking about here is the process of household formation. In the traditional Hallmark/Disney version, people start off living with their parents, they proceed through a stage of living with friends (or at least with flatmates), and then end up living in couples who eventually have 2.3 kids.   The number of adults per household tends to decrease as you go from the flatting stage to the couple stage, and also there i traditionally a progression from renting to owning your home. Because these transitions both happen over broadly the same age range, there’s an automatic tendency for them to be correlated. At 20, people are more likely  to be both renting and living in large households than at 40.

Here, though, we have a stronger claim, that buying a house is, in Auckland, the immediate cause of smaller households, or the even stronger claim that this is necessarily true.  The strongest version is clearly wrong: it is quite possible for people to form small, stable adult households while living in rental accomodation or, conversely, to buy a house but still have flatmates to help pay the bills. Data on household sizes are not what you’d need to settle the intermediate claim. It could be true, but it could also be false.

But suppose, again for the sake of argument, that the Property Investors Federation was correct: that there is a genuine causal connection and that buying (rather than renting) real estate is an unavoidable step in household formation for many people. To the extent that buying a house is inextricably linked to household formation, blaming first-home buyers is as inappropriate as blaming babies or immigrants or people moving from the rest of NZ or people with home offices. The housing crisis is the problem: it’s impeding adult household formation, and preventing families with kids getting enough space, making it harder to work from home, and making it harder for people to move to Auckland from the rest of NZ or the rest of the world.

Auckland has a housing crisis because there aren’t enough homes. This has not largely been due to changes in ownership distribution: we used to have more young homeowners, not fewer. Rules and procedures designed to impede building new homes have been a bigger contributor.

November 2, 2020

Top 14 Predictions for Round 8

Team Ratings for Round 8

This is a new competition which I have had in mind for some time since it is one of the three top European competitions, the other two being the English Premiership and the Pro 14 (not solely European usually but happens to be this year so far).

I ran through the predictions for the first 7 rounds to get to this round but decided not to publish them. You will have to take it on trust that I didn’t fake it. I can report that the first couple of rounds were pretty dodgy, starting with only 50% correct. I expect to get a bit over 70% correct longer term in this competition based on my computations. I have data from the 2012-2013 season through to the incomplete 2019-2020 season which I used to create my initial ratings and to select parameters for the model.

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
Racing-Metro 92 6.46 6.21 0.20
Lyon Rugby 6.38 5.61 0.80
Stade Toulousain 5.14 4.80 0.30
La Rochelle 5.01 2.32 2.70
Clermont Auvergne 4.45 3.22 1.20
RC Toulonnais 3.24 3.56 -0.30
Bordeaux-Begles 2.62 2.83 -0.20
Montpellier 2.55 2.30 0.20
Stade Francais Paris -1.55 -3.22 1.70
Castres Olympique -2.11 -0.47 -1.60
Section Paloise -3.79 -4.48 0.70
Brive -4.17 -3.26 -0.90
Aviron Bayonnais -4.88 -4.13 -0.80
SU Agen -8.79 -4.72 -4.10

 

Performance So Far

So far there have been 41 matches played, 29 of which were correctly predicted, a success rate of 70.7%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Brive vs. Clermont Auvergne Oct 31 21 – 43 -1.80 TRUE
2 Castres Olympique vs. Racing-Metro 92 Oct 31 10 – 13 -3.10 TRUE
3 Bordeaux-Begles vs. SU Agen Oct 31 71 – 5 14.20 TRUE
4 Section Paloise vs. La Rochelle Nov 01 24 – 35 -2.60 TRUE
5 Stade Francais Paris vs. Stade Toulousain Nov 01 48 – 14 -3.30 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 RC Toulonnais vs. Brive Nov 06 RC Toulonnais 12.90
2 Stade Toulousain vs. Castres Olympique Nov 07 Stade Toulousain 12.80
3 Bordeaux-Begles vs. Aviron Bayonnais Nov 07 Bordeaux-Begles 13.00
4 Montpellier vs. Stade Francais Paris Nov 07 Montpellier 9.60
5 Racing-Metro 92 vs. Section Paloise Nov 07 Racing-Metro 92 15.70
6 SU Agen vs. Lyon Rugby Nov 08 Lyon Rugby -9.70
7 La Rochelle vs. Clermont Auvergne Nov 08 La Rochelle 6.10

 

Super Rugby Unlocked Predictions for Round 5

Team Ratings for Round 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.

Current Rating Rating at Season Start Difference
Sharks 2.54 4.01 -1.50
Bulls 1.33 -1.45 2.80
Stormers -1.36 1.00 -2.40
Lions -2.49 -4.82 2.30
Cheetahs -8.43 -10.00 1.60
Pumas -11.27 -10.00 -1.30
Griquas -11.58 -10.00 -1.60

 

Performance So Far

So far there have been 11 matches played, 8 of which were correctly predicted, a success rate of 72.7%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Lions vs. Griquas Oct 30 61 – 31 11.10 TRUE
2 Pumas vs. Sharks Oct 31 19 – 42 -7.10 TRUE
3 Bulls vs. Stormers Oct 31 39 – 6 3.40 TRUE

 

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.

Game Date Winner Prediction
1 Sharks vs. Cheetahs Nov 06 Sharks 15.50
2 Griquas vs. Stormers Nov 07 Stormers -5.70
3 Lions vs. Bulls Nov 07 Lions 0.70

 

Mitre 10 Cup Predictions for Round 9

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.

Current Rating Rating at Season Start Difference
Tasman 14.88 15.13 -0.20
Auckland 9.71 6.75 3.00
Wellington 6.61 6.47 0.10
Bay of Plenty 5.65 8.21 -2.60
North Harbour 4.62 2.87 1.70
Canterbury 4.38 8.40 -4.00
Waikato 3.13 1.31 1.80
Hawke’s Bay 1.60 0.91 0.70
Otago -1.06 -4.03 3.00
Taranaki -3.90 -4.42 0.50
Northland -9.02 -8.71 -0.30
Counties Manukau -10.56 -8.18 -2.40
Southland -11.86 -14.04 2.20
Manawatu -14.06 -10.57 -3.50

 

Performance So Far

So far there have been 56 matches played, 37 of which were correctly predicted, a success rate of 66.1%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Canterbury vs. Otago Oct 30 16 – 23 10.70 FALSE
2 Wellington vs. Tasman Oct 31 3 – 19 -3.60 TRUE
3 Northland vs. North Harbour Oct 31 8 – 24 -9.70 TRUE
4 Auckland vs. Waikato Oct 31 31 – 10 7.80 TRUE
5 Bay of Plenty vs. Hawke’s Bay Nov 01 22 – 17 7.60 TRUE
6 Manawatu vs. Southland Nov 01 24 – 12 -1.00 FALSE
7 Taranaki vs. Counties Manukau Nov 01 27 – 31 11.70 FALSE

 

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 Southland vs. Otago Nov 06 Otago -7.80
2 Auckland vs. Northland Nov 07 Auckland 21.70
3 North Harbour vs. Counties Manukau Nov 07 North Harbour 18.20
4 Tasman vs. Canterbury Nov 07 Tasman 13.50
5 Hawke’s Bay vs. Wellington Nov 08 Wellington -2.00
6 Waikato vs. Bay of Plenty Nov 08 Waikato 0.50
7 Manawatu vs. Taranaki Nov 08 Taranaki -7.20