Scoring Anomalies – Round 23

I hope you have found SyntheticCoach’s insights useful this year. I’m hoping to make some improvements to the system over the off-season; hopefully, it will be even more insightful next year. Although it owes its original existence to Scoring Anomalies, personally, I am excited by its prospects as a more general research tool – watch this space over the pre-season next year.

This is the last official edition of Scoring Anomalies for the year, but I’ll still be around throughout the Finals series, and SyntheticCoach isn’t going anywhere. We normally have a general discussion thread for each week of the Finals; assuming the AFL provides the relevant data for the finals series, I’ll be able to generate scores. So, if there are any scores over the finals series that seem off to you, let me know, and I will happily run the numbers for you.

With that out of the way, Dane wanted to know if James Sicily’s score of 124 was slightly inflated.

SyntheticCoach: 114 (125)

James Sicily (Hawthorn)
• Effective kicks: 12 => 48
• Effective handballs: 2 => 3.0
• Clangers: 0 => 0
• • of which frees-against: 0
• Ground-ball gets: 4 => 18.0
• Bounces: 0 => 0
• Goals: 1 => 8
• Behinds: 0 => 0
• Marks: 8 => 16
• • of which contested: 1 => 4
• • of which intercepts: 2 => 4
• Tackles: 3 => 12
• Frees-for: 0 => 0
• Hitouts-to-advantage: 0 => 0
• Goal assists: 0 => 0.0
• Spoils: 6 => 12
• Other one-percenters: 0 => 0.0
Total: 125

Blindspots:
• SyntheticCoach knows nothing about when the game was on the line, let alone who did what when it was. This can have a massive effect on scaling.

His linear-scaled score was slightly lower than his real score, although his raw, un-scaled score was very close to the final thing. The breakdown doesn’t really tell us much in this case… in all likelihood, I would probably say that the slight spread between his real and Synthetic scores comes from scaling.

Pete also felt that Matt Crouch (134 points) was short-changed on the weekend.

SyntheticCoach: 120 (146)

Matt Crouch (Adelaide Crows)
• Effective kicks: 17 => 68
• Effective handballs: 21 => 31.5
• Clangers: 6 => -24
• • of which frees-against: 3
• Ground-ball gets: 6 => 27.0
• Bounces: 0 => 0
• Goals: 1 => 8
• Behinds: 0 => 0
• Marks: 7 => 14
• • of which contested: 0 => 0
• • of which intercepts: 1 => 2
• Tackles: 3 => 12
• Frees-for: 1 => 4
• Hitouts-to-advantage: 0 => 0
• Goal assists: 1 => 3.5
• Spoils: 0 => 0
• Other one-percenters: 0 => 0.0
Total: 146

Blindspots:
• Gathers from hitouts are worth 2 points each. Player had 8 clearances – perhaps some came from that source?
• Player had 26 uncontested possessions that did not come from a mark. Perhaps some came from handball-recieves (1.5 points each)?
• SyntheticCoach knows nothing about when the game was on the line, let alone who did what when it was. This can have a massive effect on scaling.

When you factor in the potential points from gathers-from-hitouts and handball-receives, his score does probably look a bit low. That said, the Crows were well beaten on the weekend, so that probably counted against him come scaling time.

In the same game, Harry also wanted to know about Rory Sloane’s score (106).

SyntheticCoach: 101 (123.5)

Rory Sloane (Adelaide Crows)
• Effective kicks: 7 => 28
• Effective handballs: 18 => 27.0
• Clangers: 3 => -12
• • of which frees-against: 0
• Ground-ball gets: 10 => 45.0
• Bounces: 0 => 0
• Goals: 0 => 0
• Behinds: 0 => 0
• Marks: 4 => 8
• • of which contested: 0 => 0
• • of which intercepts: 1 => 2
• Tackles: 6 => 24
• Frees-for: 0 => 0
• Hitouts-to-advantage: 0 => 0
• Goal assists: 0 => 0.0
• Spoils: 0 => 0
• Other one-percenters: 1 => 1.5
Total: 123.5

Blindspots:
• Gathers from hitouts are worth 2 points each. Player had 13 clearances – perhaps some came from that source?
• SyntheticCoach knows nothing about when the game was on the line, let alone who did what when it was. This can have a massive effect on scaling.

As is often the case, the blindspots make things a bit tricky. At face value, his score looks about right, compared with his synthetic score. But when you look at the potential points from gathers-from-hitouts, you can’t help but wonder if he has lost out somewhat. Once again, though, the Crows were well beaten, and this would not have helped his cause when it came to scaling.

Finally, I can’t help but think that Patrick Should-Have-Been-All-Australian-Captain Cripps (148 points) was slightly short-changed on the weekend:

SyntheticCoach: 168 (175)

Patrick Cripps (Carlton)
• Effective kicks: 12 => 48
• Effective handballs: 8 => 12.0
• Clangers: 5 => -20
• • of which frees-against: 2
• Ground-ball gets: 15 => 67.5
• Bounces: 0 => 0
• Goals: 1 => 8
• Behinds: 0 => 0
• Marks: 2 => 4
• • of which contested: 0 => 0
• • of which intercepts: 2 => 4
• Tackles: 8 => 32
• Frees-for: 4 => 16
• Hitouts-to-advantage: 0 => 0
• Goal assists: 1 => 3.5
• Spoils: 0 => 0
• Other one-percenters: 0 => 0.0
Total: 175

Blindspots:
• Gathers from hitouts are worth 2 points each. Player had 13 clearances – perhaps some came from that source?
• Player had 11 uncontested possessions that did not come from a mark. Perhaps some came from handball-recieves (1.5 points each)?
• SyntheticCoach knows nothing about when the game was on the line, let alone who did what when it was. This can have a massive effect on scaling.

Of course, he was rather quiet in the first quarter, when the Cats put together a substantial lead, so scaling might be a factor here. Then again, those stats speak for themselves. I’ll let people draw their own conclusions.

Were there any scores that seemed off to you on the weekend? Let me know in the comments, and I’ll let you know what SyntheticCoach has to say about it.

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