Our
tipping systems
Below
is an explanation from Professor Ray Stefani
of how his system works in predicting Super
12 (now Super 14) and Guiness (formerly Zurich) Cup
Rugby Union results, with some analysis from
past seasons, followed by an explanation from Stefan
Yelas of the system he uses to predict the other
international Rugby Union fixtures and a table showing
his success during the 2003 World Cup.
Go
straight to Stefan's
page
Go
straight to Ray's Guiness
Cup web page
Go
straight to Ray's Super
12 web page
Super
12 and Guiness Cup Rugby Union Prediction
How
It Works Professor Ray Stefani
I
have adapted a system that I have been improving over
the last 30 years, after more than 20,000 predictions
in a variety of sports, to making predictions for
Super 12 rugby. In 2004 I added Zurich (now Guiness)
Cup for the first time.
Here
is some information about the system I've been using
for Super 12s.
I
start with an offensive, defensive and total rating
for each team from the previous season and then adjust
that rating using season data. Each offensive
rating is adjusted, based on
Points scored by the team
Opponent defensive rating
Home advantage
Each
defensive rating is adjusted depending on
Points scored against the team
Opponent offensive rating
Home advantage
Total
rating depends on offensive rating minus defensive
rating.
*
* *
To
predict score difference for the next game,
I use
Weighted
difference of total ratings
Home advantage
To
predict the home team score I use
Score
difference
Home team offensive rating
Away team defensive rating
Home advantage
To
predict the away team score I use
Score
difference
Away team offensive rating
Home team defensive rating
Home advantage
To
predict total score I add the home team score
to the away team score.
*
* *
I
also predict the probability that each team will
win, using
Score difference
Score error standard deviation
Normal distribution
*
* *
I
show fair decimal odds for each game. Fair
decimal odds are found by taking 1/probability. For
example, if the probability of a home win is 0.5,
the fair decimal odds are 1/0.5 or 2.0 (a bet of $1
will return $2, the original $1 and a profit of $1).
If the odds of a win are 0.25, the fair decimal odds
are 1.0/0.25 or 4.0.
The
fair decimal odds can be used for money line betting.
Score difference can be used for handicap betting.
Total score can be used for over/under betting and
actual score can be used for actual score betting.
*
* *
Challenges
of Rugby Union
Currently
thee are four teams from South Africa (Bulls,
Cats, Sharks and Stormers), five teams from New
Zealand (Blues, Chiefs, Crusaders, Highlanders
and Hurricanes) and three teams from Australia
(Brumbies, Reds and Waratahs). I use two separate
home advantages, one for domestic competition and
one for international competition.
Here
is a summary of overall scoring and home advantage.
The total score tends to be higher for international
competition as does the home advantage (due to travel
fatigue, as one of several factors).
Scoring
and Home Advantage (Five Seasons, 1999-2003)
|
Competition
|
Points
|
Home
Advantage
|
|
Domestic
|
48.2
|
4.2
|
|
International
|
54.9
|
7.4
|
|
All
|
52.9
|
6.4
|
Accuracy
of Picking the Winner
If
you refer to my website
you'll find that for 13,209 predictions in sports
having few draws (ties) I picked the winner 70% of
the time. I applied my prediction method to the 2001
to 2003 seasons of Rugby Union and achieved a similar
level of accuracy.
2001
- 2003 Rugby Union seasons
Accuracy of Picking the Winner
|
Season
|
Games
|
Right
|
Wrong
|
Accuracy
|
|
2001
|
69
|
50
|
19
|
0.725
|
|
2002
|
69
|
47
|
22
|
0.681
|
|
2003
|
69
|
44
|
25
|
0.638
|
|
Total
|
207
|
141
|
66
|
0.681
|
Accuracy
of Picking the Probability
Below
you'll find probability data for picking the favorite
for the 2001 to 2003 seasons of Rugby Union. Of course,
if you want the non-favorite probabilities, just take
one minus probabilities for the favorite. I show each
probability range, the number of games, the predicted
probability and the actual accuracy (how often the
favorite won). There is close agreement. As more games
are played, the predicted and actual figures should
come even closer together.
2001-2003
Accuracy of Predicted Probabilities for the Favorite
|
Range
|
Games
|
Predicted
Prob
|
Actual
|
|
0.50
to 0.59
|
64
|
0.546
|
0.532
|
|
0.60
to 0.69
|
65
|
0.655
|
0.692
|
|
0.70
to 0.79
|
38
|
0.746
|
0.737
|
|
0.50
to 0.59
|
32
|
0.843
|
0.812
|
|
0.50
to 0.59
|
8
|
0.938
|
1.000
|
|
All
|
207
|
0.679
|
0.681
|
Accuracy
of Predicting the Score
Below
are data for the 2001 to 2003 seasons relating to
the picking the total score and actual score
for the home and away teams. As you can see, the average
errors are quite small. Each error equals the predicted
score minus the actual score.
2001
to 2003 Accuracy of the Predicted Score
|
Games
|
Points
|
Home
Error
|
Away
Error
|
Total
Error
|
|
207
|
54.7
|
0.46
|
0.06
|
0.52
|
The
analysis above and more can be viewed on Ray's website.
click
here
Now
updated to include 2004 results!
For
further analysis of how Ray's system works using soccer
as an example
click
here
Continue
for analysis on Stefan Yelas' system
Rugby
Union index page 
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