Expected score stats, analysis, Champion Data numbers, what is expected score, goals, ladder, goalkicking luck

There’s the ladder that everyone else looks at, and then there’s the ladder the real stats gurus keep one eye on.

We all know how influential goalkicking can be, but the fact is, sometimes teams get lucky or unlucky in front of the big sticks. A bad or good night in front of goal can easily swing a result, which is one of the reasons purely looking at a team’s win-loss record doesn’t tell you everything about them.

To go deeper, we have stats like Champion Data’s Expected Score – which soccer fans will recognize as being similar to their sport’s Expected Goals (xG).

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Putting it simply, it tells you what each team should have scored. We’re not trying to rewrite history; we’re just trying to remove as much luck from the equation as possible, and get down to the facts.

This is how it works, and what it means for the 2022 AFL season so far.


Every shot on goal is analysed, based on where on the ground it was taken and how much pressure the player was under.

The expected accuracy of the shot is determined based on the results from that location and pressure level over the last decade of AFL matches.

For example, a set shot from 30 meters out on a 45-degree angle has an expected accuracy of 50 per cent. So a team would be expected to score three points (reflecting the 50-50 chance of a goal).

If they kick the goal, their expected score would be 3, but their actual score would be 6.

If they kick a behind instead, their expected score would still be 3, with their actual score being 1.

Over the course of a game these incidents add up to create an expected score for the match.

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As another example, a snap in general play from 40 meters out on the boundary has an expected score of 0.6 points (10 per cent accuracy).

The expected score of each shot does not take into account the individual player’s records, nor the team’s records. It always uses the league-wide standard.


Clearly, you can’t just turn behinds into goals and say the game would’ve played out the same way. But from an analytic perspective, it’s important to know when a team over- or under-performed.

Remarkably, in just the last three rounds we’ve seen 12 matches where the result would’ve gone the other way if both teams had kicked to a league-average level.

Games where the winner lost on expected score, 2022 AFL season

Round 2: Carlton 102 vs Western Bulldogs 90

Expected score: Western Bulldogs 85 def Carlton 69

Round 2: Sydney 107 v Geelong 77

Expected score: Geelong 86 v Sydney 80

Round 2: Brisbane 97 vs Essendon 75

Expected score: Essendon 85 vs Brisbane 78

Round 2: Melbourne 82 vs Gold Coast 69

Expected score: Gold Coast 77 vs Melbourne 75

Round 3: Adelaide 96 v Port Adelaide 92

Expected score: Port Adelaide 96 vs Adelaide 78

Round 3: Geelong 104 vs Collingwood 91

Expected score: Collingwood 98 vs Geelong 87

Round 4: Sydney 86 def North Melbourne 75

Expected score: North Melbourne 79 vs Sydney 75

Round 4: West Coast 87 vs Collingwood 74

Expected score: Collingwood 95 vs West Coast 60

Round 4: Essendon 103 vs Adelaide 99

Expected score: Adelaide 101 vs Essendon 90

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The Western Bulldogs’ games have been particularly impacted by goalkicking.

In the first two rounds, they actually scored more than expected – three goals more against Melbourne, and a goal more against Carlton – before their accuracy abandoned them against Sydney and Richmond.

The fact they’ve been up-and-down will be frustrating Luke Beveridge, but at the same time, it’s proof they don’t need to throw out the entire gameplan.

Of the 2021 finalists, Melbourne and the Bulldogs were the least accurate sides in front of goal; sustainable success is more about creating opportunities so you can take advantage of enough to win, than being ridiculously efficient.

If they keep creating chances, the Dogs will recover from their 1-3 start just fine.

Other notable results, 2022 AFL season

Round 1: Gold Coast 107 vs West Coast 80

Expected score: Gold Coast 122 vs West Coast 59

Round 2: Hawthorn 120 def Port Adelaide 56

Expected score: Hawthorn 94 vs Port Adelaide 75

Round 3: Western Bulldogs 71 vs Sydney 60

Expected score: Western Bulldogs 96 vs Sydney 55

Round 4: Richmond 99 vs Western Bulldogs 61

Expected score: Richmond 80 def Western Bulldogs 78

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Collingwood would be the only unbeaten team if all results had gone to the expected goalkicking script, as they ‘should’ have beaten both Geelong and West Coast.

It’s a massive tick for Craig McRae’s side that they’re creating as many chances as they are, and going forward, if they continue to do it they should see scoreboard reward.

Meanwhile Gold Coast’s solid 2-2 start to the season might be even better than it looks. The Suns should’ve thumped the Eagles in Round 1 by over 10 goals, rather than winning by five goals, and actually beat first Melbourne on expected score.

If you’re looking for a case to believe in the Suns, this certainly helps build it.

At the other end of the scale, Sydney has won two games it ‘shouldn’t’ have (against Geelong and North Melbourne) thanks to some excellent goalkicking, while the Swans were also much closer to beating the Bulldogs than they ‘should’ve ‘ been.

Perhaps we shouldn’t have been so surprised when the Swans struggled against North. After all, their expected score numbers showed they were overperforming, and they continued to do so against the Roos. They may not be quite as good as they looked in the opening two rounds.

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Below is the full Expected Score Ladder, and the gap between Sydney’s real percentage (a healthy 115.9%) and expected percentage (a poor 87.4%) is particularly telling.


1. Collingwood (4-0, 129.2%) [Reality: 8th, 2-2, 109.9%]

2. Melbourne (3-1, 147.6%) [Reality: 1st, 4-0, 140.7%]

3. St Kilda (3-1, 129.6%) [Reality: 4th, 3-1, 130.3%]

4. Fremantle (3-1, 127.8%) [Reality: 3rd, 3-1, 132.3%]

5. Gold Coast Suns (3-1, 122.8%) [Reality: 9th, 2-2, 105.9%]

6. Geelong (3-1, 121.5%) [Reality: 5th, 3-1, 117.4%]

7. Brisbane Lions (2-2, 132.7%) [Reality: 2nd, 3-1, 148.2%]

8. Western Bulldogs (2-2, 102.7%) [Reality: 14th, 1-3, 81.8%]

9. Hawthorn (2-2, 101.8%) [Reality: 11th, 2-2, 104.2%]

10. Carlton (2-2, 9.9%) [Reality: 7th, 3-1, 102.4%]

11.Richmond (2-2, 91.6%) [Reality: 10th, 2-2, 104.5%]

12. North Melbourne (2-2, 73.3%) [Reality: 17th, 1-3, 67.3%]

13. Sydney Swans (1-3, 87.4%) [Reality: 6th, 3-1, 115.9%]

14. GWS Giants (1-3, 87.4%) [Reality: 13th, 1-3, 82.5%]

15. Adelaide Crows (1-3, 86.5%) [Reality: 12th, 1-3, 88.6%]

16. Port Adelaide (1-3, 82.8%) [Reality: 18th, 0-4, 69.5%]

17. Essendon (1-3, 78.2%) [Reality: 16th, 1-3, 73.9%]

18. West Coast Eagles (0-4, 60.1%) [Reality: 15th, 1-3, 76.5%]


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