AFL Lab

What is expected score?

Expected score is a metric used in a number of different sports to evaluate quality of scoring opportunities. At a high level, the metric uses relevant historical data (i.e.

Is goalkicking just dumb luck?

This is a very important question. To determine if a player is a good or bad goalkicker requires a proper statistical analysis. Such an analysis would effectively determine the chance that a completely average goalkicker would perform as good (or as bad) as the subject. We can never be completely certain if this is true, we can only protest vs. reasonable doubt. What “reasonable doubt” is as a value is up for debate.

Where to from here?

There’s a lot more slicing and dicing that can be done with this data, and I hope to explore more in time. What we can see from a few basic results is that goalkicking is a skill in that some players are significantly better than average over long periods. Most players cannot be shown to be significantly better or worse than average over a long period.

Hasn’t this been done before?

Yes, it has! The methodology I use is heavily influenced by Robert’s. I’m not doing anything particularly new here, I am just optimising this for live calculations using the best publicly available data, and automatically posting it to a Twitter account.

What data is available?

The data I have is near-live location data of all scoring shots, the player, the time, and the resulting score. From this I can determine the shot distance and angle (measured to the centreline). Save for manually recording additional data from the broadcast, that’s it. Post-game, when all the statistics are published, it’s possible to differentiate the shot context.