Super 18 Predictions for Round 12
Team Ratings for Round 12
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 | 17.39 | 13.22 | 4.20 |
| Crusaders | 13.87 | 8.75 | 5.10 |
| Highlanders | 9.17 | 9.17 | 0.00 |
| Chiefs | 8.54 | 9.75 | -1.20 |
| Lions | 8.36 | 7.64 | 0.70 |
| Blues | 3.47 | -1.07 | 4.50 |
| Brumbies | 2.02 | 3.83 | -1.80 |
| Sharks | 1.40 | 0.42 | 1.00 |
| Stormers | 0.63 | 1.51 | -0.90 |
| Waratahs | -0.91 | 5.81 | -6.70 |
| Jaguares | -2.84 | -4.36 | 1.50 |
| Bulls | -4.48 | 0.29 | -4.80 |
| Force | -8.96 | -9.45 | 0.50 |
| Cheetahs | -9.47 | -7.36 | -2.10 |
| Reds | -10.60 | -10.28 | -0.30 |
| Kings | -13.37 | -19.02 | 5.70 |
| Rebels | -14.52 | -8.17 | -6.40 |
| Sunwolves | -16.80 | -17.76 | 1.00 |
Performance So Far
So far there have been 87 matches played, 67 of which were correctly predicted, a success rate of 77%.
Here are the predictions for last week’s games.
| Game | Date | Score | Prediction | Correct | |
|---|---|---|---|---|---|
| 1 | Hurricanes vs. Stormers | May 05 | 41 – 22 | 21.00 | TRUE |
| 2 | Cheetahs vs. Highlanders | May 05 | 41 – 45 | -16.10 | TRUE |
| 3 | Rebels vs. Lions | May 06 | 10 – 47 | -16.40 | TRUE |
| 4 | Chiefs vs. Reds | May 06 | 46 – 17 | 22.30 | TRUE |
| 5 | Waratahs vs. Blues | May 06 | 33 – 40 | 0.50 | FALSE |
| 6 | Sharks vs. Force | May 06 | 37 – 12 | 12.90 | TRUE |
| 7 | Bulls vs. Crusaders | May 06 | 24 – 62 | -11.10 | TRUE |
| 8 | Jaguares vs. Sunwolves | May 06 | 46 – 39 | 19.50 | TRUE |
Predictions for Round 12
Here are the predictions for Round 12. 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 | Blues vs. Cheetahs | May 12 | Blues | 16.90 |
| 2 | Brumbies vs. Lions | May 12 | Lions | -2.30 |
| 3 | Crusaders vs. Hurricanes | May 13 | Hurricanes | -3.50 |
| 4 | Rebels vs. Reds | May 13 | Reds | -0.40 |
| 5 | Bulls vs. Highlanders | May 13 | Highlanders | -9.70 |
| 6 | Kings vs. Sharks | May 13 | Sharks | -11.30 |
| 7 | Jaguares vs. Force | May 13 | Jaguares | 10.10 |
David Scott obtained a BA and PhD from the Australian National University and then commenced his university teaching career at La Trobe University in 1972. He has taught at La Trobe University, the University of Sheffield, Bond University and Colorado State University, joining the University of Auckland, based at Tamaki Campus, in mid-1995. He has been Head of Department at La Trobe University, Acting Dean and Associate Dean (Academic) at Bond University, and Associate Director of the Centre for Quality Management and Data Analysis at Bond University with responsibility for Short Courses. He was Head of the Department of Statistics in 2000, and is a past President of the New Zealand Statistical Assocation. See all posts by David Scott »
How about predicting the EPL footbsll league,
cheers
8 years ago
I would need to use a different method. The scores in football (soccer) are mainly small integer values, whereas the method I use has an implicit assumption of a near continuous distribution for the score differences. The score differences are of course still integers but because the number of different values that the score differences take is reasonably large, the violation of the continuous distribution assumption is not so great that the method fails.
There are statisticians predicting the EPL. One such is http://www.pickforwin.com. I went to a talk by one of the developers of the method used on that site.
8 years ago