Seamus Hogan

Feeling Chuffed - The Dismal Science

Sep 20, 2014

It was a great day for the ECON department at Canterbury on Wednesday. Our very own Rachel Webb, successfully defended her doctoral thesis, The Health Economics of Macrosomia. Rachel has been a part of the Department for many years, having previou...

Are ODI Scores Increasing? UPDATED - The Dismal Science

Sep 13, 2014

I had a conversation with a sports blogger, John Rogers, on Twitter last week. John Rogers had tweeted a link to a blog post he had written on why the WASP projection being used in BSkyB's coverage of limited overs cricket this English summer is necess...

Why not a teal coalition? - The Dismal Science

Sep 11, 2014

After the Green's described themselves as more pro-market than National last week, I tweeted:

Norman is over-stating a bit, but a Green-National coalition does have some appeal if it merged the best of both. http://t.co/uFEc1kyNkK
— Seamus Hogan (@seamus_hogan) August 27, 2014
Will Taylor replied that he and Matt feel that NZ needs a real blue-green party.
@seamus_hogan as @TVHE and I often discuss,NZ needs a real blue-green party.
— Will Taylor (@WillTaylorNZ) August 27, 2014
I think they were thinking of a new party. But I don't see why it would not be feasible for the current Green party to enter into a governing coalition with National after the election this year. If National get enough seats to govern alone, the minor parties will have no bargaining power (although, I still think the Greens should try to form a coalition, for the reasons below). But if National falls short of that mark, they would likely be very open to a partnership with a single, stable, reasonably-non-crazy minor party. The Greens would just need to decide what are the one or two key issues that are really important to them and that are not unthinkable for a pragmatic centre-right party--e.g. 1. clean waterways and a serious policy on carbon emissions, and 2 funding for child-poverty initiatives--and then agree to throw away some of the minor stuff like their positions on monetary policy. The long-term advantages to the Greens would be enormous:

  • The alternative is likely to be not being in government at all, or being in government with a coalition with Mana, Internet, NZ First, and Labour, which is probably a brush a principled party would not want to get tarred with.
  • It would make credible for a long-time that the Greens are prepared to work with either major party to further environmental issues, and so give them much more bargaining power with Labour after future elections.
  • Any move on environmental policy achieved in a coalition with National, even if not as strong as could be agreed to by Labour, would be sustainable beyond the next election and could be strengthened then. In contrast, a strong ETS negotiated with Labour might not survive beyond the 2017 election. 
  • Where their policies are more market oriented than National's (pricing water appropriately for dairy farmers, not discouraging high-density living in Auckland), having the push come from the Greens would enable National to implement those policies without fear of a backlash from the left. 
I am deadly serious about this. Why not? 


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How unfair is the Super 15 schedule? - The Dismal Science

Jul 26, 2014

In advance of the semi-final between the Crusaders and the Sharks this evening, it is timely to look at the fairness of the Super 15 schedule. The Crusaders are playing at home, a massive advantage that they earned by virtue of finishing one point ahead of the Sharks in the regular season. But was that a fair reflection of the two teams? 

The Super 15 rugby competition is a bit unusual in its unbalance. There are five teams from each of three countries. Each team plays the other four teams in its country twice, home and away; it plays four of the five teams from each of the other two countries once, two games at home and two away; and it doesn’t play the remaining two teams at all. This leads to three reasons why a schedule may favour some teams over others: First, teams from stronger countries have to play more games against each other making it harder for the best teams from those countries to finish ahead of the best teams from weaker countries; second, a team is favoured if the two teams it doesn’t have to play are relatively weak strong; and third, for the best teams, there is an advantage to playing the stronger teams from other countries at home to get the benefit of home-field advantage, and play away against weaker teams who can be expected to lose in any location. 

Mark Reason recently had an article in the Dominion Post suggesting that these factors led the Crusaders (who finished the regular season in second place overall) to have been favoured in this year’s competition and to have penalised the Hurricanes (who finished seventh and out of the playoffs) . His logic seemed impeccable to me; certainly it seemed that the Crusaders benefited from the luck of the draw this year relative to recent years when they had to play the best South African teams in South Africa.


I am currently doing some research constructing rankings for international cricket, and thought it would be fun to use the same method to infer how teams would have finished in the Super 15 had they had a balanced schedule. Kirdan Lees has beaten me to it, in a welcome new blog: Sport Loves Data. Kirdan has reevaluated the ranking of the 15 teams, taking into account the imbalance in the schedule, and has posted his results here. Given that Kirdan’s method is very different from mine, I decided to see how the two methods would compare. The table below gives the actual points table, and my revised points table adjusted for schedule unfairness. (The TL;DR explanation of my method is detailed at the bottom of this post.)

Team

Actual

Predicted

Waratahs

58

58.5

Crusaders

51

50.1

Sharks

50

52.4

Brumbies

45

45.0

Chiefs

44

42.6

Highlanders

42

37.7

Hurricanes

41

40.7

Western Force

40

40.2

Bulls

38

38.3

Blues

37

38.1

Stormers

32

33.4

Lions

31

33.8

Reds

28

24.5

Cheetahs

24

23.9

Rebels

21

23.1


Kirdan's method gives rankings rather than points, so the following table shows just the assumed finishing position: 

Team

Actual

Predicted

Kirdan

Waratahs

1

1

1

Crusaders

2

3

2

Sharks

3

2

4

Brumbies

4

4

3

Chiefs

5

5

6

Highlanders

6

10

7

Hurricanes

7

6

5

Western Force

8

7

11=

Bulls

9

8

9

Blues

10

9

10

Stormers

11

12

8

Lions

12

11

11=

Reds

13

13

14

Cheetahs

14

14

13

Rebels

15

15

15


The interesting thing is that my and Mark Reason’s intuition about how much the Crusaders were favoured this year turns out to have been overblown, although the method does result in my having the Crusader’s ranked just behind the Sharks rather than slightly ahead. And yes, the Hurricanes would have qualified for the playoffs as one of the top six teams using my or Kirdan's rankings, but using my method the reason is not that the method pushed them up but rather that the big mover was the Highlanders, who appear to have been hugely favoured by the schedule this year. 


Postscript: Kirdan has another post looking at home field advantage in the Super 15. My probit regression method, would require a lot more data to analyse team-specific home field advantage, but in a model which assumes that the advantage is constant across teams, the result is that home-field matters so much in the Super 15 that, in a match between two teams of equal ability, the one playing at home has a 75% chance of winning. It is no surprise that the Super rugby competition has almost always been won by the team that finished first in the regular season, and who therefore are not only likely the strongest team, but also earn home-field advantage throughout the playoffs. 


TL;DR Explanation of Method: 
  • There are two separate LHS variables, each estimated by an ordered probit regression: table points scored by home team, table points scored by away team. Each can take the values 0, 1, 2, 3, 4, 5. 
  • My database only included the scores, not the bonus points scored. The actual points earned by each team for winning, tying, or losing by 7 points or less, can be inferred from the scores, but not bonus points for scoring 4 tries or more. I proxied this by assigning a bonus point if the team scored 30 points or more. The method proceeds as follows: 
  1. Generate a dummy for each of the 15 teams that equals 1 if that team was the home team, and -1 if it was the away team.
  2. Run two ordered probits, one for points scored by the home team, and one for points scored by the away team, in each case run on the 15 dummies (one dropped) and a constant. 
  3. Predict the probability of scoring 0,1,2,3,4,5 points for each of the 210 possible matchups (each team playing each other home or away), and found the expected points for each.
  4. Then sum these to get the total points in a balanced competition where every team plays every other twice, home and away.
  5. Finally, normalise these by a linear transformation to get the same mean and s.d. as the actual super 15 points table.
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