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Interested in @binman's question around whether our drop off in accuracy is indicative of a league-wide drop off due to weather and fatigue / loading, so I looked at all team's scoring compated to expectation (using Champion Data's calculation srouced from the Herald Sun) by round this season and calculated the average difference per round (see below data visualisation).

League-wide, the average (grey line) looks to hover around the expected difference of 0 as you would expect, but it varies with some early rounds (3 and 4) being lower than average with the 'worst' round being round 11. In saying that, round 12 and 13 were actually better than expected and this was when we performed most poorly other than round 16.

In terms of Melbourne's performance (red dots) in poor weather / rain, I can recall round 5 vs Ess, round 9 vs Port, round 15 vs Gee and round 16 vs GWS. The first two we scored above expectation, the last two well below. It's difficult to assess the fatigue / loading aspect for us, but there looks to be something in this if we assume we load around our bye in round 14. It will be interesting to see how the rest of the season unfolds from here as you wouldn't expect there to be loading from here, although fatigue / rain / wind / cold may be a factor. And sometimes, it could just be luck :)

image.thumb.png.bb82d854f6843892ed1ae7275eddc7f9.png

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1 hour ago, Deelightful Dee said:

Hi Demon faithful. First time poster, long time reader.

Yes, RIchmond was the last time we won when expected to lose - see below for this year's actual vs expected results

image.thumb.png.393ac3cdd003b65cd0e5efecab31dd72.png

Great stuff @Deelightful Dee, more please :)

So it's two wins we should have had: Fremantle and GWS vs two losses we should have had: Richmond and St.Kilda.

We've had some matches where we should have won by more: Carlton and Collingwood, but more games where we won by more than expected: Sydney, West Coast, North and Hawthorn.  We were also fortunate against Port to be so close.

Probably overall our W-L and % reflects our performance so far.

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On 7/6/2023 at 8:18 AM, WheeloRatings said:


The circles in the left half of the following field map are Melbourne's shots from general play. Melbourne's only set shot within 30 metres was Melksham's on the tight angle.

 

 

Thanks for this @WheeloRatings.  I've been away so have been on my mobile and now back on desktop so can have a better look.

Can you please give me the key green/grey/purple and diamond/circle.

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I like to use Player Ratings to try to capture player performance in one number as it takes into account where and how the ball was won and the result of the player's action (acknowledging that this still rarely tells the full story).

As you can see below, usually when we win (results of games in top left), our average player rating is higher (bottom left).

By looking at the individual player ratings and comparing them to their last 40 games' average, we can also see who has performed above and below what we might typically expect (right side graphs). Top right shows highest to lowest performance over/under expectations, whilst bottom right gives some perspective as to where the over/under performers have come from, i.e. our top/mid/bottom tier players.

So for last round against St Kilda, I think it was clear that May had a spectacular game, but the top right shows that Jordan and Sparrow were also well above average which is probably down to the full time mid role they both played compared to what they previously have. On the other side of the equation, it was clear that Kossie struggled, but Salem and Grundy in particular actually were even lower than Kossie in terms of their usual output.

image.thumb.png.db33f9505d5d2aafdff7edcfe21f284b.png

From an overall team perspective, I also think it's interesting that we do tend to have a lull in performance during the middle part of the year (supporting @binman's loading theory).

In 2021, it was for 10 games from rounds 10 to 19 where we lost 5 games and drew 1, before flicking the switch vs Gold Coast in Round 20 and progressively improving towards the oustanding performances in the prelim and GF.

In 2022, the 6 games from rounds 11 to 17 were below par other than the round 15 Bris mauling. We then stablised for the rest of the season, but the drop off in the finals was clear.

This year looks similar. The 5 games from rounds 10 to 16 were well below our season average, but we've seen an improvement in the last two weeks. If we can continue the upward trajectory, we could end up timing our run ideally for a shot at finals similar to 2021!

image.thumb.png.8b0b6ae6956c2a2c9d5382c4f6c2441a.png

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19 hours ago, Deelightful Dee said:

Hi Demon faithful. First time poster, long time reader.

Yes, RIchmond was the last time we won when expected to lose - see below for this year's actual vs expected results

image.thumb.png.393ac3cdd003b65cd0e5efecab31dd72.png

Brilliant stuff DD - welcome aboard. 

That's really interesting on a few levels.

One is that our accuracy in the early rounds meant our winning margin was significantly higher than the expected score in several cases, in particular the Swans and Roos wins (we won both by 5 plus goal more than the expected score). 

My understanding is weather is not one of the (many) data points specifically factored in to arrive at the expected score. All of those games were played in perfect conditions.

But from the ESPN podcast wheelo suggested (ta - really interesting though i could have done without revisiting 186!) my understanding is the historical data they use goes back to 2013, so weather should in theory be factored in in totality (ie the aggregated data of the 1000s of games played), if that makes sense.

But i doubt the point in the season the game is played in is factored in.

My contention is that in footy now, teams are at their fittest in the first say 8-9 rounds, drop off say rounds 11- 18 and on the back of increased loads through those middle rounds HOPEFULLY the fitness (as defined by running power - aerobic and pace) gets back to the in the early season levels.

Another way of looking at that pattern is players are are their least fatigued rounds 1-8, most fatigued rounds 11-18 and if their program has worked and they don't have too many injuries, fatigue levels from rounds 18-19 are similar to rounds 1-8. I suspect this has only become a league wide phenomena in the last 1-2 seasons so it is not yet apparent in the modelling to arrive at expected score.

Taking our example, less fatigue means much faster ball movement and less fatigue related skill errors (handball, ball handling, hitting targets by foot and accuracy for goal).

Which correlates to higher scores because the fast ball movement means we run in waves and create more free options, one on ones and space inside 50 AND we turn it over less frequently so fewer scoring chains break down. And because our skills are less impacted by fatigue we can take more risks with our kicking, for example more changing lanes and use of the corridor.   

I texted a question for Daniel Hoyne from Champion data's slot on SEN asking what data could be used to get a sense of the relative fitness for each team. I meant publicly available data, but his answer was the GPS numbers, which CD doesn't have access to and is completely locked up by the clubs. 

The expected scores might be one data point to at least explore that issue - at least in terms of assessing say one teams fatigue levels over the course of the season.

Looking at the chart, there seems to be less anomalous results in the middle part of the season than the first third of the season. I'll be interested to see if we see an uptick in higher real scores than expected scores for the dees as the season progresses. if we do, that might be an indicator our fitness levels are retuning to optinal levelks. 

(on the above, my gut feeling is last season we would have not had as many anomalous results in the first third of the season, but still above water to so to speak, and then a similar drop of in the middle part of the year. But i doubt there was an uptick for higher real scores than expected scores for the dees because we clearly never got back to the fitness levels of the first third of the season). 

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17 hours ago, Deelightful Dee said:

I like to use Player Ratings to try to capture player performance in one number as it takes into account where and how the ball was won and the result of the player's action (acknowledging that this still rarely tells the full story).

As you can see below, usually when we win (results of games in top left), our average player rating is higher (bottom left).

By looking at the individual player ratings and comparing them to their last 40 games' average, we can also see who has performed above and below what we might typically expect (right side graphs). Top right shows highest to lowest performance over/under expectations, whilst bottom right gives some perspective as to where the over/under performers have come from, i.e. our top/mid/bottom tier players.

So for last round against St Kilda, I think it was clear that May had a spectacular game, but the top right shows that Jordan and Sparrow were also well above average which is probably down to the full time mid role they both played compared to what they previously have. On the other side of the equation, it was clear that Kossie struggled, but Salem and Grundy in particular actually were even lower than Kossie in terms of their usual output.

image.thumb.png.db33f9505d5d2aafdff7edcfe21f284b.png

From an overall team perspective, I also think it's interesting that we do tend to have a lull in performance during the middle part of the year (supporting @binman's loading theory).

In 2021, it was for 10 games from rounds 10 to 19 where we lost 5 games and drew 1, before flicking the switch vs Gold Coast in Round 20 and progressively improving towards the oustanding performances in the prelim and GF.

In 2022, the 6 games from rounds 11 to 17 were below par other than the round 15 Bris mauling. We then stablised for the rest of the season, but the drop off in the finals was clear.

This year looks similar. The 5 games from rounds 10 to 16 were well below our season average, but we've seen an improvement in the last two weeks. If we can continue the upward trajectory, we could end up timing our run ideally for a shot at finals similar to 2021!

image.thumb.png.8b0b6ae6956c2a2c9d5382c4f6c2441a.png

Again, fascinating on a number of levels

The pattern of aggregated player across the 2021, 2022  and this season certainly supports my hypothesis that the arc of a season can be thought of as three acts or phases. And that those phases are related to fatigue (ie logic suggests the performance of players is strongly correlated with fatigue).

It is interesting you should post this data actually.

In 2021, around this middle part of the season i was trying to make the case that loading, and therefore fatigue was a significant factor in our drop off in form. One of the things i pointed to as evidence was exactly this (well not exactly, i did not have the brilliant charts) - a significant drop off in the collective player rankings (there was some article about this - like always pointing the symptom not the diagnosis - that's to say making the argument that our drop off in form was because our players ratings had fell away BUT not trying to explore why that might be the case. Cause and effect and all that).  

I also recall using that same data to support my argument for how critical nibbler was (and remains for that matter) to the team.

In that middle phase of the season, the ONLY two best 22 dees players whose player ratings didn't drop below their average were Nibbler and Hunt.

I say critical because our game is based around all team defense, which is 100% reliant on ALL players working super hard to block outlets, cover oppo players, spread and get up and down the ground all match. Fatigue makes that very difficult, hence we get opened up more. And lose games we otherwise would win. So any player who can continue to cover the ground close to their optimal level is gold. 

I suspect nibblers ratings didn't drop below his average last year or this year either, or if it did, only marginally. Terrific evidence of nibblers incredible fitness, leadership and work ethic. 

This season we have clearly tried to use tempo again (which we didn't really last year after about round 12)  - and also a higher zone press (which is new)- to mitigate the impact of fatigue on our all team defence.  The last quarter against the saints was the perfect example of this strategy. 

Edited by binman
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22 hours ago, Deelightful Dee said:

I like to use Player Ratings to try to capture player performance in one number as it takes into account where and how the ball was won and the result of the player's action (acknowledging that this still rarely tells the full story).

As you can see below, usually when we win (results of games in top left), our average player rating is higher (bottom left).

By looking at the individual player ratings and comparing them to their last 40 games' average, we can also see who has performed above and below what we might typically expect (right side graphs). Top right shows highest to lowest performance over/under expectations, whilst bottom right gives some perspective as to where the over/under performers have come from, i.e. our top/mid/bottom tier players.

So for last round against St Kilda, I think it was clear that May had a spectacular game, but the top right shows that Jordan and Sparrow were also well above average which is probably down to the full time mid role they both played compared to what they previously have. On the other side of the equation, it was clear that Kossie struggled, but Salem and Grundy in particular actually were even lower than Kossie in terms of their usual output.

image.thumb.png.db33f9505d5d2aafdff7edcfe21f284b.png

From an overall team perspective, I also think it's interesting that we do tend to have a lull in performance during the middle part of the year (supporting @binman's loading theory).

In 2021, it was for 10 games from rounds 10 to 19 where we lost 5 games and drew 1, before flicking the switch vs Gold Coast in Round 20 and progressively improving towards the oustanding performances in the prelim and GF.

In 2022, the 6 games from rounds 11 to 17 were below par other than the round 15 Bris mauling. We then stablised for the rest of the season, but the drop off in the finals was clear.

This year looks similar. The 5 games from rounds 10 to 16 were well below our season average, but we've seen an improvement in the last two weeks. If we can continue the upward trajectory, we could end up timing our run ideally for a shot at finals similar to 2021!

image.thumb.png.8b0b6ae6956c2a2c9d5382c4f6c2441a.png

These sort of posts are amazing. Thanks for doing the work.

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On 7/12/2023 at 2:08 PM, Deelightful Dee said:

Hi Demon faithful. First time poster, long time reader.

Yes, RIchmond was the last time we won when expected to lose - see below for this year's actual vs expected results

image.thumb.png.393ac3cdd003b65cd0e5efecab31dd72.png

My feeling was that we tend to lose more games we are expected to win and we don't win many games we are expected to lose. But this doesn't really support either, so it's great to see some objective data to show it's just my MFSS kicking in. 

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On 7/13/2023 at 10:57 AM, binman said:

Again, fascinating on a number of levels

The pattern of aggregated player across the 2021, 2022  and this season certainly supports my hypothesis that the arc of a season can be thought of as three acts or phases. And that those phases are related to fatigue (ie logic suggests the performance of players is strongly correlated with fatigue).

It is interesting you should post this data actually.

In 2021, around this middle part of the season i was trying to make the case that loading, and therefore fatigue was a significant factor in our drop off in form. One of the things i pointed to as evidence was exactly this (well not exactly, i did not have the brilliant charts) - a significant drop off in the collective player rankings (there was some article about this - like always pointing the symptom not the diagnosis - that's to say making the argument that our drop off in form was because our players ratings had fell away BUT not trying to explore why that might be the case. Cause and effect and all that).  

I also recall using that same data to support my argument for how critical nibbler was (and remains for that matter) to the team.

In that middle phase of the season, the ONLY two best 22 dees players whose player ratings didn't drop below their average were Nibbler and Hunt.

I say critical because our game is based around all team defense, which is 100% reliant on ALL players working super hard to block outlets, cover oppo players, spread and get up and down the ground all match. Fatigue makes that very difficult, hence we get opened up more. And lose games we otherwise would win. So any player who can continue to cover the ground close to their optimal level is gold. 

I suspect nibblers ratings didn't drop below his average last year or this year either, or if it did, only marginally. Terrific evidence of nibblers incredible fitness, leadership and work ethic. 

This season we have clearly tried to use tempo again (which we didn't really last year after about round 12)  - and also a higher zone press (which is new)- to mitigate the impact of fatigue on our all team defence.  The last quarter against the saints was the perfect example of this strategy. 

In reference to your thoughts on ANB @binman, he's had a pretty solid year, averaging 9.1 ratings point per game, 15th best for the team. Not quite up to his best year of 10.7 (7th in team) in 2018 and 10.2 (10th) in 2021

He's only had 3 games that dipped quite a bit under that average, but overall, the data supports your hypothesis.

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image.thumb.png.cbc0b2ed0da9420c3d3ca62a4b31c3e5.png

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Whilst talking about expected scores, @crow_data_sci from Twitter, recently posted expected score data covering the 2021 to 2023 season up to round 16. So I thought I'd take a look to determine a different / better perspective of accuracy, given that missing a goal from a hard shot vs an easy shot results in the same accuracy measure generally used in the AFL media. Looking at the actual (result) score less the expected score (xScore) shows that Bowey is our most accurate shot at goal, whilst JVR has started his career strongly in this regard. Fritter is the best of those with plenty of shots, whilst Trac, Gawn and, somewhat surprisingly to me, ANB are down the other end of the table.

image.png.805fd78dbf5651cd2d3da1ee9c6c6723.png

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A stats based previous of our to 4 clash tonight: There are many similarities in how both teams play: strong contest & time in forward half are strengths. Lions are the best clearance differential team, but Dees are 2nd over the last 4 games. If Dees can keep up in clearances, a win is within reach!

image.thumb.png.0596e409a407ba5f960058cd84e9b2cd.png

image.thumb.png.8be265440af0f1c86aa9710fc01ea215.png

image.thumb.png.eadad6237ad2a13f316532076a3d5f70.png

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Melbourne v Brisbane (Round 18, 2023)

https://www.wheeloratings.com/afl_match_stats.html?ID=20231806

Key Team Stats

Stats highlighted purple were won by Melbourne.

Stat For Against Diff
Disposal Efficiency 71.3 73.1 -1.8
Kicking Efficiency 59.4 67.8 -8.4
Metres Gained 6095 5907 +188
Inside 50s 51 56 -5
Shots At Goal 26 28 -2
Shots Per Inside 50 51.0 50.0 +1.0
Contested Possessions 146 125 +21
Ground Ball Gets 82 86 -4
Intercepts 66 72 -6
Intercept Marks 17 18 -1
Centre Clearances 17 12 +5
Stoppage Clearances 28 20 +8
Contested Marks 14 13 +1
Marks Inside 50 12 17 -5
Hitouts 47 34 +13
Hitouts To Advantage 22 8 +14
Tackles 56 53 +3
Tackles Inside 50 14 10 +4
Def One On One Loss % 26.9 9.1 +17.8

Pressure

Team pressure

Quarter For Against
1 169 158
2 150 164
3 181 207
4 174 192
Match 168 180

Source: Herald Sun

Most Pressure Points

Note: pressure points are the 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/ )

Player Pressure
Acts
Pressure
Points
Season
Average*
Jack Viney 23 54 54.1
Kysaiah Pickett 21 43 43.0
Max Gawn 12 36 22.9
Christian Petracca 15 35 48.1
Alex Neal-Bullen 20 35 48.0
Tom Sparrow 17 32 42.6
Taj Woewodin 14 28 25.5
Lachie Hunter 13 28 23.9
Trent Rivers 11 28 23.7
Angus Brayshaw 15 27 30.3
Jake Lever 12 26 15.2
Steven May 10 26 15.0
James Jordon 13 24 20.3
Ed Langdon 8 19 27.2
Christian Salem 8 18 29.0
Ben Brown 8 15 12.2
Jake Melksham 5 14 14.6
Charlie Spargo 8 13 24.9
Jacob van Rooyen 8 13 23.8
Jake Bowey 7 11 20.4
Harrison Petty 7 10 19.4
Judd McVee 6 9 18.2
Joel Smith 3 7 21.0

* Pressure points for rounds 4 and 6 have not been able to be sourced from the Herald Sun. Pressure points for these matches have been estimated from the number of pressure acts for each player.

Source: Herald Sun

Time in Forward Half

Quarter For Against
1 47% 53%
2 50% 50%
3 40% 60%
4 64% 36%
Match 50% 50%

Source: Match total sourced from the Herald Sun; quarter values are my own calculations.

Score Sources

Summary

Score sources highlighted purple were won by Melbourne.

Category For Against Diff
G B T G B T
Kick-in 0 0 0 0 0 0 +0
Centre Bounce 1 2 8 0 1 1 +7
Stoppage (Other) 7 4 46 6 0 36 +10
Turnover 8 3 51 10 7 67 -16
Category For Against
Match Season Match Season
Kick-in 0 2.6 0 2.4
Centre Bounce 8 10.7 1 6.7
Stoppage (Other) 46 23.2 36 21.6
Turnover 51 53.5 67 41.2

Chain start region

Note: region is from the scoring team's perspective. Against season average represents average points conceded by Melbourne across the season, not average points scored by Brisbane.

Category Region For Against
Match Season Match Season
Kick-in D50 0 2.6 0 2.4
Centre Bounce Centre 8 10.7 1 6.7
Stoppage (Other) D50 7 0.8 6 2.2
Stoppage (Other) Centre 1 2.9 0 1.2
Stoppage (Other) Wing 18 11.3 18 6.9
Stoppage (Other) F50 20 8.2 12 11.3
Turnover D50 6 10.2 19 6.1
Turnover Centre 0 7.9 7 5.9
Turnover Wing 32 28.6 34 21.2
Turnover F50 13 6.6 7 8.0
Region For Against
Match Season Match Season
D50 13 13.6 25 10.6
Centre 9 21.5 8 13.8
Wing 50 39.9 52 28.1
F50 33 14.9 19 19.3

Points from defensive half

For Against
Match Season Match Season
28 34.2 50 24.2

Shots at goal

Team Shots G B T Acc.
Set Position
Melbourne 15 8 4 52 53.3
Brisbane 15 9 5 59 60.0
General Play
Melbourne 11 8 2 50 72.7
Brisbane 13 7 2 44 53.8

Centre Bounce Attendances

  CBAs CBA % 2023 % 2022 %
Max Gawn 32 91 52.5 65.5
Angus Brayshaw 28 80 25.6 16.0
Jack Viney 26 74 68.9 74.6
James Jordon 20 57 26.2 0.2
Christian Petracca 15 43 63.6 74.6
Tom Sparrow 11 31 46.6 32.2
Kysaiah Pickett 5 14 11.7 1.3
Jacob van Rooyen 3 9 5.7  
Trent Rivers 0 0 4.2 0.0
Alex Neal-Bullen 0 0 3.1 3.5
Harrison Petty 0 0 0.9 0.0
Clayton Oliver     82.8 86.5
Brodie Grundy     55.7 83.7
James Harmes     27.8 14.6
Tom McDonald     5.4 0.0
Josh Schache     0.0 13.8

Ruck Contests and Hitouts

Ruck Contests

  Ruck
Contests
RC % 2023 % 2022 %
Max Gawn 83 84 47.9 57.8
Jacob van Rooyen 15 15 10.0  
Ben Brown 1 1 2.6 3.6
Harrison Petty 0 0 2.0 0.0
Steven May 0 0 0.1 0.0
Alex Neal-Bullen 0 0 0.1 0.0
Christian Petracca 0 0 0.1 0.1
Brodie Grundy     49.5 77.4
Tom McDonald     8.9 7.0
Josh Schache     6.7 13.4
Clayton Oliver     0.0 0.0

Hitouts

  Ruck
Contests
Hitouts To
Adv.
To Adv. %
(2023)
To Adv. %
(2022)
Max Gawn 83 39 17 32.3 33.6
Jacob van Rooyen 15 7 5 27.0  
Ben Brown 1 1 0 0.0 14.3
Harrison Petty 0 0 0 22.2  
Alex Neal-Bullen 0 0 0 0.0  
Brodie Grundy       30.8 30.2
Tom McDonald       25.0 33.3
Josh Schache         33.3

Opposition hitouts

  Ruck
Contests
Hitouts To
Adv.
Oscar McInerney 86 33 8
Joe Daniher 13 1 0
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20 hours ago, Deelightful Dee said:

A stats based previous of our to 4 clash tonight: There are many similarities in how both teams play: strong contest & time in forward half are strengths. Lions are the best clearance differential team, but Dees are 2nd over the last 4 games. If Dees can keep up in clearances, a win is within reach!

image.thumb.png.0596e409a407ba5f960058cd84e9b2cd.png

image.thumb.png.8be265440af0f1c86aa9710fc01ea215.png

image.thumb.png.eadad6237ad2a13f316532076a3d5f70.png

Again, thank you.

Fascinating reading. 

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4 minutes ago, WheeloRatings said:

You didn't miss it, I forgot to include that. We lost expected scores 76-90.

We were 21 points down on expected score at 3 quarter time - I saw it written on the board they take out to the huddle

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Round 18, 2023 MCG - Demons vs Lions

All hail King Maxy!

Statistically we may have just witnessed Max's greatest performance.  124% up on his season's average!

His highest player rating ever recorded since i started keeping records in 2018.  His next best was against the Swans in Rnd 12, 2022 with a 6.225

Note that the Swans rating does not take into account hit outs to advantage as i was not including that in 2022.  Even so, doubt he would have had 17 to advantage as he did last night.

To put that in to some perspective the combined average hit outs to advantage (average) of Max and Grundy prior to last night was 13.  JVR not bad either with 5 to advantage as a chop out forward ruck!  McInerney gathering 8 as the main ruckman for the Lions. 

Taking a look at some of Max's off-the-charts performance....

21 effectives @ 72.4% (roughly the AFL average), 3 contested marks, 2 one percenters, 10 clearances (the most on the night and one more than the Lion's best...Neale with 9), 1 rebound, 3 inside 50s, 7 tackles (only one behind Viney who had 8 with the most on the night), 6 score involvements, 8 intercepts (the most for us), 17 hit outs to advantage, 457 meters gained, 1 goal and a respectable 4 turnovers.

Tracc another amazing job.  Gus, Viney, Bowey and Hunter all eclipsing their usual output along with McVee, Kozzy and Melksham.

Demons

Scoring Efficiency  
Disposals Per Goal  22.69
% In50s Goal 31.40
Conversion %

64.00

Lions

Scoring Efficiency

 
Disposals Per Goal  20.94
% In50s Goal 28.60
Conversion %

66.70

Player Rating Rank Season Rating to Prior Rnd % Change vs Season Rating
Max Gawn 7.000 1 3.113 124.86
C Petracca 4.850 2 4.681 3.61
A Brayshaw 4.850 2 3.763 28.89
Jack Viney 4.675 4 3.663 27.63
J Bowey 3.575 5 3.070 16.45
L Hunter 3.275 6 2.987 9.64
T Rivers 3.250 7 3.648 -10.91
J McVee 2.625 8 2.248 16.77
S May 2.525 9 3.284 -23.11
Ed Langdon 2.500 10 3.168 -21.09
K Pickett 2.450 11 2.189 11.92
J Jordon 2.200 12 3.995 -44.93
Jake Lever 2.000 13 3.110 -35.69
J Melksham 1.950 14 1.429 36.46
T Sparrow 1.825 15 3.025 -39.67
C Salem 1.825 15 3.386 -46.10
C Spargo 1.700 17 1.904 -10.71
T Woewodin 1.700 17 1.750 -2.86
J V Rooyen 1.600 19 2.183 -26.71
Ben Brown 1.375 20 2.095 -34.37
A N-Bullen 1.275 21 2.556 -50.12
Joel Smith > 32% 1.150 22 1.541 -25.37
H Petty < 52% 1.100 23 2.594 -57.59
Team Rating 60.18   71.45 -15.78
Top 6 28.23   26.15 7.93
Bottom 6 8.80   9.29 -5.27

 

< Subbed out / TOG %

> Subbed in / TOG %

Stats courtesy of footwire.com & wheeloratings.com

Edited by Demon Dynasty
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@WheeloRatings @binman - what’s your analysis of the ‘pressure ratings’ - from the naked eye, they don’t really marry up.

neither  team operating at AFL standard level in the 1st?

Brisbanes pressure rating higher in the 4th?

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Team & Player Ratings to Rnd 18, 2023 vs H&A Season 2022

Player 2023 Rating 2023 Rank 2022 Rating % Change vs 2022 2022 Rank Change in Rank vs 2022
C Oliver 5.285 1 5.320 -0.66 1 0
C Petracca 4.691 2 4.456 5.27 2 0
A Brayshaw 3.826 3 3.839 -0.34 5 2
J Jordon > 3.775 4 3.164 19.31 9 5
Jack Viney 3.727 5 3.971 -6.14 3 -2
T Rivers < 3.625 6 2.423 49.61 18 12
Max Gawn 3.412 7 3.643 -6.34 8 1
Steven May 3.233 8 3.971 -18.58 3 -5
C Salem 3.191 9 3.363 -5.11 7 -2
B Grundy 3.159 10 - - - -
Ed Langdon 3.127 11 3.109 0.58 11 0
Jake Bowey < 3.105 12 2.856 8.72 13 1
Jake Lever 3.041 13 2.703 12.50 14 1
L Hunter 3.005 14 - - - -
A Tomlinson 2.965 15 2.079 42.62 22 7
T Sparrow 2.950 16 2.665 10.69 16 0
J Harmes > 2.804 17 3.082 -9.02 12 -5
M Hibberd < 2.589 18 2.613 -0.92 17 -1
H Petty < 2.571 19 2.392 7.48 19 0
A N-Bullen 2.481 20 2.688 -7.70 15 -5
K Chandler < 2.360 21 - - - -
Judd McVee 2.271 22 - - - -
B Fritsch 2.230 23 1.936 15.19 27 4
K Pickett 2.207 24 2.118 4.20 21 -3
J V Rooyen 2.138 25 - - - -
T McDonald 2.054 26 1.967 4.42 26 0
Ben Brown < 1.975 27 1.762 12.09 29 2
C Spargo < 1.886 28 1.981 -4.80 24 -4
T Woewodin 1.725 29 - - - -
Joel Smith > 1.541 30 2.239 -31.17 20 -10
J Melksham > 1.536 31 1.947 -21.11 25 -6
J Schache * 1.375 32 - - - -
B Laurie < > * 1.300 33 - - - -
D Turner < * 1.075 34 - - - -
Team Rating 71.19   69.48 2.47    

* Played less than two full matches (in total)

< Subbed Out at least once or more (player rating could be comprised somewhat)

> Subbed In at least once or more (player rating could be comprised somewhat)

Stats courtesy of footwire.com & wheeloratings.com

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16 hours ago, Engorged Onion said:

@WheeloRatings @binman - what’s your analysis of the ‘pressure ratings’ - from the naked eye, they don’t really marry up.

neither  team operating at AFL standard level in the 1st?

Brisbanes pressure rating higher in the 4th?

That's an interesting question, one I've been pondering since i saw that data yesterday and was also reflecting on after the blues game. Was planning on raising on the podcast (we discussed this a bit after the blues game).

My initial thoughts is that i think a factor in the low pressure numbers in this game, and the blues game, relates to how both of those teams played - and how we responded to their method.

Comparing the Lions game with the Pies King's Birthday game, both games felt high pressure watching, but perhaps on Friday night more in the sense that it was a tense, enthralling contest between two genuine contenders that finished in high drama?

But what were the differences in how the Pies and the Lions (and the blues) played and how we responded. And how might that impact the pressure numbers.  

These were the pressure numbers from the Pies game:

Q1: 176 - 180
Q2: 174 - 172
Q3: 201 - 206
Q4: 186 - 177
Tot: 183 - 186

The big difference in the way the two games were played is the Pies played their game against us and ran at us they way they like to do - chaining handballs until they find an outside kicker in space to take on a high risk kick to the corridor.  

We responded to that method by denying them time and space by:

  • having our defensive zone set high to create density 
  • take the corridor away from them and force them down the line
  • really getting up in their grill as the Pies went forward with frontal pressure (ie dees players ahead of the ball peeling of their man and running at the ball carrier)
  • Sweating on their mids and flankers sitting on the outside waiting for the ball to be fed out

From wheelo def, pressure points for players are the weighed sum of pressure acts. I assume the same true is of the team's pressure ratings (i also assume the teams' ratings is the players ratings aggregated?) 

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.

The way we responded to the Pies method by denying them time and space ticks all the above boxes in terms of how pressure points are accumulated.

But against the Lions and the Blues we didn't press up nearly as aggressively or apply the same level of pressure frontal pressure. And out zone wasn't set as high. 

The Lions came with a plan to use the width of the G to move our defensive zone around, i think to pull Lever and may apart to minimize their intercepting ability and to expose them one on one.

To that end, they switched more than any team against us since perhaps the first half of last season.  We let them do so, and never really pressed up. The blues did something similar, but more i think because they couldn't get through our zone going in straight line.

And now that i think about it, the saints also did something similar and tried to control possession of the ball - and the pressure numbers were low in that match too.

So, with the ball getting switched side to side, fewer opportunities to aggregate pressure points because there is less corralling, closing acts and chasing acts. And less contests. 

And added to that we went fast in the first and last quarters, with the ball in motion and lots of wave running that creates space around the and ahead of the ball. Very much how the Pies love to play. But unlike us against the Pies, the Lions didn't really look to deny us space, for example by pressing up or frontal pressure  - which meant fewer pressure acts like corralling, closing acts and chasing.

So, to your question about my analysis of the ‘pressure ratings’, i think they are really useful indicator as evidenced by the fact clubs use them during games (which surprised me), but like any stat only tell part of the tale. 

I've been looking at them all season, and my overall impression is, as a rule they pass the eye test in the sense they reflect my sense of the pressure in the game.

That was not necessarily the case in the blues and Lions games - or for that matter the Saints games - in the sense those games didn't feel low pressure as such.

That said the pressure numbers in those games do point to the strategies of switching and denying us the ball (though its not then really possible, unless you have intently watch the games, to compare say the lions game with a run in the mill actual low pressure game). 

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