We base the difficulty of a kick on the following factors – and the factors must have been proved based on past data and using the right statistical techniques:

• distance of the kick

• angle of the kick

• altitude

• side of field and foot used

• score difference (to indicate pressure)

• home/away

• 1st half/2nd half

Based on past goal kick data, distance and angle carry by far the most weight and are the two variables used in our current model..

The model is based on many past kicks of professional goal kickers, and the model objectively derives the factors that predict the probability of kick success. A kicker is basically judged against his peers taking past history into account. The model is re-calibrated regularly as additional goal kick data is captured – the model therefore reflects the latest performance of professional goal kickers.

Then our goal kicker ranking table:

The ranking table makes the success probabilities compared to the actual performances come alive.

We use the success probabilities of the kicks a kicker is faced with to determine how well or poorly he performed over a game, tournament or season.

If one knows the success probability of the kicks a kicker was faced with, one knows the number of kicks he would be EXPECTED to make based on the past performance of his peers:

• if his ACTUAL number of successful kicks is better than EXPECTED, he performed better than his peers and will be rated at better than 5 out of 10

• if he ACTUALLY performed as EXPECTED, his rating will be 5 out of 10

• he’ll be rated at below 5 out of 10 if he ACTUALLY performed poorer than EXPECTED

Kickers are then ranked based on their rating.

More about our newest statistic: Value Added

Value Added indicates the value added on the scoreboard by the goal kicker relative to other professional goal kickers. It is the number of points the kicker scored more than expected given the difficulty of his kicks. The higher the kicker’s Value Added the better the performance. A kicker with a negative Value Added actually lost his team points due to poor kicking relative to other professional goal kickers and given the difficulty of his kicks.

Now we can answer the question – what was the impact of goal kicking on the score difference?

Example

In all his 2013 International games, Leigh Halfpenny GAINED 27 points for Wales (see Internationals (2013) ranking table) – he scored 27 more points compared to the number of points an average goal kicker would have scored given the kicks he was faced with.

Click here to see more information about the research behind our rankings