WheeloRatings

Votes Matches Polled 1 2 3 4 5 6 7 8 9 10 11 12 13 Christian Petracca 62 10 5 • 7 9 1 1 10 • 10 • 8 10 1 Clayton Oliver 40 9 2 1 9 8 • 2 7 7 2 2 Jack Viney 23 3 • • • • 6 • • 7 • • • 10 Jake Lever 16 3 9 2 • • • • • • • • 5 • Steven May 16 3 • • • • • • 1 • • 8 7 Max Gawn 15 5 5 • 3 • 3 • • 2 • 2 Brodie Grundy 12 2 • • 6 6 • • • • • • • • • Kysaiah Pickett 12 2 9 • • • 3 • • • • • • Ed Langdon 10 2 • • 6 • • • • • • • • 4 • Angus Brayshaw 7 2 • • • • • • 5 • • • 2 • • Kade Chandler 6 2 • • 1 • • • 5 • • • • • • Trent Rivers 6 1 • • • • • • • • 6 • • • • Christian Salem 4 1 • • • 4 Michael Hibberd 4 1 • • 4 • • • • • Lachie Hunter 3 2 • • 1 • • • • • • 2 • • Bayley Fritsch 2 1 • • • • • • • • • • • 2 Tom McDonald 2 1 • • 2 • • •

These figures are published in the Herald Sun for all players for all matches, but given the requirement to manually transcribe them I only post the highest for Melbourne each week. I can provide others on request.

I'm going to try to automate these posts as much as possible, so I should be able to quite easily incorporate the opponents' HO to advantage each week with no ongoing effort.

I can get the Pies hit outs to advantage. Would you like Melbourne's opponents' HO to advantage each week from now on? There are a few sources for expected scores - the figures I quoted are from the Herald Sun which are provided by Champion Data. They would be the most reliable as they capture the pressure on the player at the time of the kick. The AFLxScore and crow_data_sci twitter profiles both calculate Expected Scores based on the information available to them, which only use a proxy for pressure as the pressure information is not available to them. For example, you can use the fact that a player won a contested possession as a proxy for the amount of pressure they were under, but it won't accurately reflect the pressure they were under when they kicked the ball, only when they gained possession. A player could get an uncontested possession, then run into traffic and kick for goal under pressure. CD would rate this as a more difficult kick than AFLxScore.

Your post is missing the link to the expected scores.

Melbourne v Collingwood Pressure Q1: 176 - 180 Q2: 174 - 172 Q3: 201 - 206 Q4: 186 - 177 Tot: 183 - 186 Most Pressure Points (Weighed sum of pressure acts. Physical pressure acts are worth 3.75 points, closing acts are worth 2.25 points, chasing acts are 1.5 points and corralling are 1.2. https://www.championdata.com/glossary/afl/) Petracca: 74 Viney: 65 Neal-Bullen: 59 Pickett: 43 Sparrow: 40 Chandler: 40 Langdon: 40 van Rooyen: 37 Brayshaw: 33 Time in forward half 58% - 42% Here are my calculations (not official) for time in forward half for each quarter: Q1: 55% - 45% Q2: 50% - 50% Q3: 66% - 34% Q4: 63% - 37% Expected Scores 84 - 64

Melbourne v Collingwood https://www.wheeloratings.com/afl_match_stats.html?ID=20231308 Note: first number below is Melbourne, higher value is bold. Pressure Not available until tomorrow. Q1: ? - ? Q2: ? - ? Q3: ? - ? Q4: ? - ? Tot: ? - ? Most Pressure Points (Weighed sum of pressure acts. Physical pressure acts are worth 3.75 points, closing acts are worth 2.25 points, chasing acts are 1.5 points and corralling are 1.2. https://www.championdata.com/glossary/afl/) Not available until tomorrow. Time in forward half Not available until tomorrow. Here are my calculations (not official) for time in forward half for each quarter: Q1: 55% - 45% Q2: 50% - 50% Q3: 66% - 34% Q4: 63% - 37% Score sources Centre bounce 2.0.12 - 0.0.0 Ball up 0.4.4 - 1.1.7 Throw in 0.0.0 - 1.0.6 Turnover 6.14.50 - 7.7.49 Kick-in 0.0.0 - 0.0.0 Shots at goal Set position 7.10.52 - 3.4.22 General play 1.4.10 - 6.2.38 Expected Scores Not available until tomorrow. Centre Bounce Attendances CBAs CBA % 2023 % 2022 % Christian Petracca 17 81 64.5 74.6 Jack Viney 16 76 67.2 74.6 Angus Brayshaw 14 67 13.5 16.0 Tom Sparrow 12 57 47.4 32.2 Max Gawn 11 52 45.4 65.5 Brodie Grundy 10 48 58.6 83.7 James Jordon 2 10 19.5 0.2 Trent Rivers 2 10 4.5 0.0 Kysaiah Pickett 0 0 13.9 1.3 Jacob van Rooyen 0 0 5.8 Alex Neal-Bullen 0 0 3.9 3.5 Clayton Oliver 82.8 86.5 James Harmes 28.7 14.6 Tom McDonald 5.4 0.0 Harrison Petty 1.3 0.0 Josh Schache 0.0 13.8 Ruck Contests Ruck Contests RC % 2023 % 2022 % Brodie Grundy 42 50 51.5 77.4 Max Gawn 37 44 42.8 57.8 Jacob van Rooyen 5 6 9.0 Christian Petracca 0 0 0.1 0.1 Tom McDonald 8.9 7.0 Josh Schache 6.7 13.4 Ben Brown 3.8 3.6 Harrison Petty 3.1 0.0 Clayton Oliver 0.0 0.0 Hit outs Ruck Contests Hitouts To Adv. To Adv. % (2023) To Adv. % (2022) Brodie Grundy 42 26 5 33.2 30.2 Max Gawn 37 17 6 31.0 33.6 Jacob van Rooyen 5 3 0 16.0 Tom McDonald 25.0 33.3 Harrison Petty 22.2 Ben Brown 0.0 14.3 Josh Schache 33.3 https://www.wheeloratings.com/afl_stats.html

Votes Matches Polled 1 2 3 4 5 6 7 8 9 10 11 12 Christian Petracca 61 9 5 • 7 9 1 1 10 • 10 • 8 10 Clayton Oliver 40 9 2 1 9 8 • 2 7 7 2 2 Jake Lever 16 3 9 2 • • • • • • • • 5 Jack Viney 13 2 • • • • 6 • • 7 • • • Max Gawn 13 4 5 • 3 • 3 • • 2 • Brodie Grundy 12 2 • • 6 6 • • • • • • • • Kysaiah Pickett 12 2 9 • • • 3 • • • • • Ed Langdon 10 2 • • 6 • • • • • • • • 4 Steven May 9 2 • • • • • • 1 • • 8 Angus Brayshaw 7 2 • • • • • • 5 • • • 2 • Kade Chandler 6 2 • • 1 • • • 5 • • • • • Trent Rivers 6 1 • • • • • • • • 6 • • • Michael Hibberd 4 1 • • 4 • • • • Lachie Hunter 3 2 • • 1 • • • • • • 2 • Tom McDonald 2 1 • • 2 • • •

The aggregate of several Squiggle models is very similar, at least in terms of the gap between Melbourne (4th) and Western Bulldogs (5th). https://squiggle.com.au/ladder/

Here are the round-by-round hitouts to advantage for 2022. Average 1 2 3 4 5 6 7 8 9 10 11 12 13 15 16 17 18 19 20 21 22 23 24 25 Max Gawn 9.1 8 6 3 13 5 11 12 7 7 10 6 11 8 11 3 15 10 6 13 6 14 15 Luke Jackson 3.2 3 5 2 1 0 2 4 1 2 0 2 3 4 4 4 3 3 4 7 12 2 2 Sam Weideman 1.3 0 0 0 0 4 0 4 4 1 0 Tom McDonald 0.6 0 1 0 0 2 0 0 1 1 Ben Brown 0.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1

I can provide the game-by-game hit outs to advantage for 2022 if you would like to incorporate them into your 2022 ratings.

The home advantage is probably the biggest factor overall actually, but mainly for matches played between teams from different states. That sounds like a reasonable theory. I haven't analysed the different paths through the finals in the simulation results, but one thing it won't take into consideration is 1st playing a battle-hardened 2nd/3rd in the prelim. The simulations just see it as 1st being the home team against a likely lower-rated opponent so would win more often than not. Brisbane and Port's premiership chances are definitely negatively affected by having to play the GF at the MCG, but Brisbane is affected more.

Firstly, a team's rating is the sum of the its attacking rating and its defensive rating. The attacking rating is based on whether teams score above or below average and the defensive metric is based on whether teams concede above or below average. However, instead of using a team's actual score, I calculate an "adjusted" score using a weighted average of their actual score and the score they would have kicked had they kicked at an expected accuracy. This is to account for the luck factor in goalkicking. The attacking and defensive ratings are updated following each match based on these "adjusted" scores compared to the expected scores. If a team's adjusted score is higher than expected, their attack rating increases (and vice versa). If their opponent's adjusted score is higher than expected, their defensive rating decreases (and vice versa). The expected scores take into account the teams pre-game ratings and any venue advantage. I have a page on my site which provides some more detail, noting that I have never actually got around to finalising it: https://www.wheeloratings.com/afl_methodology.html In addition, teams carry over ~65% of their rating from the previous season as there's a general regression to the mean from one season to the next.

Yes, absolutely, I'm more than happy for you to use it!

It's largely due to Melbourne being ranked #1 on team ratings by my model. Believe it or not, I actually have Melbourne favourites against Collingwood on King's Birthday, so a Collingwood v Melbourne final would be close to 50/50, or even Melbourne favourites. That's all based on the fact my model currently rates Melbourne 6.2 points higher than Collingwood, which I don't personally agree with, just to be clear. Collingwood's rating actually decreased from rounds 7 to 10 as their opponents were particular inaccurate (Adelaide 7.16, Sydney 6.12, GWS 7.13, and Carlton 7.15) and then didn't beat North by as much as expected. Even though I have Melbourne ranked fourth on the aggregate ladder, they're still more likely to finish second or third than fourth if you look at the ladder distribution. Melbourne's strong percentage definitely helps. I should note that my model doesn't look at the historical record of teams finishing fourth, it simply looks at the individual finals match up for the given simulation. FYI, here are the premiership probabilities for all teams finishing in a particular ladder position this year, with fourth being much higher than historical results with the current final 8 system: 1: 31% 2: 24% 3: 17% 4: 14% 5: 5% 6: 4% 7: 3% 8: 2%

I'll respond to your other post. @old55 is correct that the simulations use the Team Ratings as a basis, and my model has Melbourne currently ranked #1. I agree that it doesn't necessarily seem correct, but in my defence (or my model's defence), the aggregate of a number of models on https://squiggle.com.au/power-rankings/ also sees Melbourne ranked #1 and Collingwood #4. The model simulates the remainder of the season 50,000 times, including simulating the finals based on the outcomes for a particular simulated season. Basically, for a given simulation, I simulate the remainder of the home and away season and then simulate the final series based on the final ladder positions of that particular simulation. I do that 50,000 times and aggregate the results. Melbourne's premiership favouritism is largely due to them being ranked #1.

Yes definitely, I can add that into the standard stats that I include each week - it's not too much work. If I forget, just remind me! 😊

@Demon Dynasty @binman A large factor in the drop off in our goals / inside 50 is our accuracy. Shots / inside 50 has been quite consistent between rounds 5 and 12 but our accuracy has really dropped off. Round Inside 50s Shots Shots / Inside 50 Goals Goals / Inside 50 Accuracy 1 60 30 50.0 17 28.3 56.7 2 54 21 38.9 13 24.1 61.9 3 60 33 55.0 21 35.0 63.6 4 58 33 56.9 19 32.8 57.6 5 55 24 43.6 11 20.0 45.8 6 53 25 47.2 15 28.3 60.0 7 64 30 46.9 22 34.4 73.3 8 61 26 42.6 13 21.3 50.0 9 66 29 43.9 15 22.7 51.7 10 48 23 47.9 11 22.9 47.8 11 58 26 44.8 10 17.2 38.5 12 59 28 47.5 8 13.6 28.6

Yes I do have the hitouts to advantage by player. Hitouts, Melbourne v Carlton Ruck Contests Hitouts To Adv. To Adv. % (2023) To Adv. % (2022) Max Gawn 38 20 9 30.6 33.6 Brodie Grundy 34 11 7 34.6 30.2 Jacob van Rooyen 7 2 1 18.2 Tom McDonald 25.0 33.3 Harrison Petty 22.2 Ben Brown 0.0 14.3 Josh Schache 33.3 Hitouts to advantage by round Average 1 2 3 4 5 6 7 8 9 10 11 12 Brodie Grundy 7.5 4 5 10 13 12 5 9 7 8 4 6 7 Max Gawn 6.1 7 0 5 6 6 4 9 9 9 Jacob van Rooyen 0.4 1 1 1 0 0 0 0 0 0 1 Tom McDonald 0.3 1 0 1 0 0 0 Harrison Petty 0.2 0 0 1 1 0 0 0 0 Ben Brown 0.0 0 0 0 Christian Petracca 0.0 0 0 0 0 0 0 0 0 0 0 0 0 Josh Schache 0.0 0

The pressure rating is the average pressure applied to the opponent's disposals only, so when Melbourne hold onto the ball it doesn't actually affect Melbourne's pressure rating. But I do agree that the pressure rating can be misleading.

Melbourne v Carlton https://www.wheeloratings.com/afl_match_stats.html?ID=20231201 Note: first number below is Melbourne, higher value is bold. Pressure Q1: 179 - 195 Q2: 172 - 161 Q3: 179 - 166 Q4: 148 - 153 Tot: 170 - 170 Most Pressure Points (Weighed sum of pressure acts. Physical pressure acts are worth 3.75 points, closing acts are worth 2.25 points, chasing acts are 1.5 points and corralling are 1.2. https://www.championdata.com/glossary/afl/) Petracca: 53 Neal-Bullen: 52 Viney: 46 Sparrow: 45 Chandler: 33 Pickett: 33 Brayshaw: 28 Hunter: 26 Time in forward half 58% - 42% Here are my calculations (not official) for time in forward half for each quarter: Q1: 52% - 48% Q2: 56% - 44% Q3: 65% - 35% Q4: 57% - 43% Score sources Centre bounce 0.2.2 - 2.1.13 Ball up 2.3.15 - 2.1.13 Throw in 2.0.12 - 0.1.1 Turnover 4.7.31 - 2.5.17 Kick-in 0.1.1 - 0.0.0 Shots at goal Set position 5.10.40 - 6.5.41 General play 3.3.21 - 0.1.1 Expected Scores 81 - 45 Centre Bounce Attendances @old55 CBAs CBA % 2023 % 2022 % Jack Viney 15 83 66.6 74.6 Tom Sparrow 15 83 46.8 32.2 Christian Petracca 10 56 63.5 74.6 Brodie Grundy 9 50 59.3 83.7 Max Gawn 9 50 44.8 65.5 Angus Brayshaw 7 39 10.2 16.0 James Harmes 6 33 28.7 14.6 Trent Rivers 1 6 4.2 0.0 Kysaiah Pickett 0 0 15.0 1.3 Jacob van Rooyen 0 0 6.2 Alex Neal-Bullen 0 0 4.2 3.5 Clayton Oliver 82.8 86.5 James Jordon 20.3 0.2 Tom McDonald 5.4 0.0 Harrison Petty 1.3 0.0 Ruck Contests Ruck Contests RC % 2023 % 2022 % Max Gawn 38 48 42.7 57.8 Brodie Grundy 34 43 51.6 77.4 Jacob van Rooyen 7 9 9.3 Christian Petracca 0 0 0.1 0.1 Tom McDonald 8.9 7.0 Josh Schache 6.7 13.4 Ben Brown 3.8 3.6 Harrison Petty 3.1 0.0 https://www.wheeloratings.com/afl_stats.html

I obtain the pressure ratings, pressure points, and official time in forward half stats from the Herald Sun with a subscription. It's a manual transcription process so I just do that for DL. The unofficial time in forward half is calculated from a separate data set that I have access to. I haven't loaded these onto the site either, but I can more easily run these for all teams as it is at least in a database (which goes back to 2021). I'm looking at using this data set for other things, like clearances by zone.

Votes Matches Polled Christian Petracca 51 8 Clayton Oliver 40 9 Jack Viney 13 2 Max Gawn 13 4 Brodie Grundy 12 2 Kysaiah Pickett 12 2 Jake Lever 11 2 Angus Brayshaw 7 2 Ed Langdon 6 1 Kade Chandler 6 2 Trent Rivers 6 1 Michael Hibberd 4 1 Lachie Hunter 3 2 Tom McDonald 2 1 Steven May 1 1 https://www.wheeloratings.com/afl_stats.html

Melbourne v Fremantle https://www.wheeloratings.com/afl_match_stats.html?ID=20231103 Note: first number below is Melbourne, higher value is bold. Pressure Q1: 200 - 177 Q2: 164 - 198 Q3: 178 - 200 Q4: 197 - 215 Tot: 185 - 198 Most Pressure Points (Weighed sum of pressure acts. Physical pressure acts are worth 3.75 points, closing acts are worth 2.25 points, chasing acts are 1.5 points and corralling are 1.2. https://www.championdata.com/glossary/afl/) Harmes: 61 Viney: 59 Sparrow: 58 Petracca: 53 Neal-Bullen: 45 Salem: 41 May: 40 Rivers: 34 McVee: 32 Chandler: 32 Time in forward half 56% - 44% Here are my calculations (not official) for time in forward half for each quarter: Q1: 60% - 40% Q2: 48% - 52% Q3: 46% - 54% Q4: 67% - 33% Score sources Centre bounce 3.1.19 - 2.1.13 Ball up 2.1.13 - 3.1.19 Throw in 0.2.2 - 2.1.13 Turnover 5.7.37 - 4.4.28 Kick-in 0.1.1 - 1.0.6 Shots at goal Set position 4.7.31 - 9.3.57 General play 6.3.39 - 3.3.21 Expected Scores 84 - 66

Melbourne v Port Adelaide https://www.wheeloratings.com/afl_match_stats.html?ID=20231001 Note: first number below is Melbourne, higher value is bold. Pressure Q1: 182 - 203 Q2: 200 - 203 Q3: 189 - 198 Q4: 205 - 219 Tot: 194 - 205 Most Pressure Points (Weighed sum of pressure acts. Physical pressure acts are worth 3.75 points, closing acts are worth 2.25 points, chasing acts are 1.5 points and corralling are 1.2. https://www.championdata.com/glossary/afl/) Oliver: 85 Petracca: 65 Viney: 63 Neal-Bullen: 55 Pickett: 50 Brayshaw: 49 Chandler: 40 Salem: 36 Rivers: 32 McVee: 32 Spargo: 31 McDonald: 30 Time in forward half 39% - 61% Here are my calculations for time in forward half for each quarter, which were not too far off the figures Channel 7 put up on the screen during the third quarter. Q1: 45% - 55% Q2: 33% - 67% Q3: 51% - 49% Q4: 32% - 68% Based on my calculations, the second and fourth quarters ranked as two of Melbourne's three worst quarters of the year for time in forward half: 31.6%, Q4 v Port Adelaide 31.8%, Q1 v Brisbane 32.7%, Q2 v Port Adelaide 34.4%, Q1 v West Coast 39.9%, Q1 v Essendon 40.4%, Q2 v Essendon Score sources Centre bounce 2.1.13 - 0.0.0 Ball up 0.1.1 - 3.4.22 Throw in 3.0.18 - 2.1.13 Turnover 6.8.44 - 6.8.44 Kick-in 0.0.0 - 0.1.1 Shots at goal Set position 8.2.50 - 7.9.51 General play 3.5.23 - 4.4.28 Expected Scores 74 - 97