2019 team rankings according to Champion Data

[RUNVS]

Ok thanks. Is there anyone out there attempting to track stats that combine an element of “value judgement” by a human? So in this case a stat like “productive disposal”.

It isn't an exact stat, though I think it should be, but I find that metres gained divided by disposals is a good way to judge players that get cheap stats.

I did this a few years ago but

Heeney - 328m (20.6 disposals)
Parker - 307m (25.3 disposals)
Kennedy - 305m (28.8 disposals)
Mills - 295m (17.3 disposals)
Rampe - 285m (16.6 disposals)
Jack - 281m (17.7 disposals)
Hannebery - 280m (24.7 dispoals)
McVeigh - 266m (18.5 dispoals)
Rohan - 255m (9.6 disposals)
Grundy - 253m (16.8 disposals)
Towers - 224m (14.7 disposals)
Papley - 233m (15.6 disposals)
Cunningham - 207m (14.2 disposals)
Melican - 197m (11.9 disposals)
Hewett - 162m (18.7 disposals)

So in other words per disposal, these are were the Swans most damaging players

Metres for every disposals

Rohan - 25.8m
Franklin - 25.7m
Newman - 19.2m
Jones - 17.9m
Rampe - 17.2m
Mills - 17.1m
Lloyd - 16.7m
Melican - 16.6m
Heeney - 15.9m
Jack - 15.9m
Towers - 15.2m
Grundy - 15.1m
Papley - 14.9m
Cunningham - 14.6m
McVeigh - 14.4m
Parker - 12.1m
Hannebery - 11.3m
Kennedy - 10.6m
Hewett - 8.7m

 

[Coaster2012]

Not that we all took CD seriously anyway, but this has to be the nail in the coffin. Anytime from now on, when anyone brings up CD in their arguments, we can just reference these statistics.

 

[LightTower4]

The only stat that matters is how many goals and behinds are scored.
Every year they come up with a new metric. What's it going to be in 2019? Ball kicked lace in versus lace out?

 

[Footypie32]

Not that we all took CD seriously anyway, but this has to be the nail in the coffin. Anytime from now on, when anyone brings up CD in their arguments, we can just reference these statistics.

I don't think this should effect CDs credibility. Rather, I think it shows the limitations of statistics. Especially in AFL.

 

[Daniltchenko You Beauty]

To be fair, aside from West Coast (who nobody rated pre-season this year), this is a pretty reasonable 2019 ladder prediction for mine.

1. Melbourne
2. Adelaide
3. Richmond
4. Essendon
5. Collingwood
6. Geelong
7. GWS Giants
8. North Melbourne
9. Hawthorn
10. Brisbane
11. West Coast
12. Port Adelaide
13. Sydney
14. St Kilda
15. Western Bulldogs
16. Carlton
17. Fremantle
18. Gold Coast

 

[Joao]

We are worse than Carlton! Clearly CD is bollocks...

Should enter CD in the annual BF ladder prediction and see how it does. The ladder looks mostly plausible (obvs not the Freo part ) so wouldn't be surprised to see it do comparably well. It at least doesn't have any team bias (even if it has plenty of role bias).

 

[Sttew]

So West Coast win the flag and are rated 11th?

Didnt realise Robert Walls works at Champion Data.

The data is based on the past 2 years, not just 2018

 

[RUNVS]

Here is a random question, and one not good enough for its own thread but I think is interesting, but if you were to make a best 22 based on one stat, and one stat alone, which stat would you pick?

By that I mean lets say you pick marks, that means you select a best 22 based on the player who takes the most marks for each position, so the ruckman who took the most marks on average, or the half back who took the most marks.

For me I would probably go with metres gained. Sure you would find some flawed players in the team, but I think it would be quite a damaging team when attacking, even if it might be a little defensively limited.

 

[Joao]

Here is a random question, and one not good enough for its own thread but I think is interesting, but if you were to make a best 22 based on one stat, and one stat alone, which stat would you pick?

By that I mean lets say you pick marks, that means you select a best 22 based on the player who takes the most marks for each position, so the ruckman who took the most marks on average, or the half back who took the most marks.

For me I would probably go with metres gained. Sure you would find some flawed players in the team, but I think it would be quite a damaging team when attacking, even if it might be a little defensively limited.

Hmmm, interesting question. I think there are going to be massive holes in whichever stat you pick but can't help but think contested possessions is a good place to start. You got to have the ball before you can gain meters and most meterage players are outside types.

Either that or maybe pressure acts.

 

[AmericanAFL]

It isn't an exact stat, though I think it should be, but I find that metres gained divided by disposals is a good way to judge players that get cheap stats.

I did this a few years ago but

Heeney - 328m (20.6 disposals)
Parker - 307m (25.3 disposals)
Kennedy - 305m (28.8 disposals)
Mills - 295m (17.3 disposals)
Rampe - 285m (16.6 disposals)
Jack - 281m (17.7 disposals)
Hannebery - 280m (24.7 dispoals)
McVeigh - 266m (18.5 dispoals)
Rohan - 255m (9.6 disposals)
Grundy - 253m (16.8 disposals)
Towers - 224m (14.7 disposals)
Papley - 233m (15.6 disposals)
Cunningham - 207m (14.2 disposals)
Melican - 197m (11.9 disposals)
Hewett - 162m (18.7 disposals)

So in other words per disposal, these are were the Swans most damaging players

Metres for every disposals

Rohan - 25.8m
Franklin - 25.7m
Newman - 19.2m
Jones - 17.9m
Rampe - 17.2m
Mills - 17.1m
Lloyd - 16.7m
Melican - 16.6m
Heeney - 15.9m
Jack - 15.9m
Towers - 15.2m
Grundy - 15.1m
Papley - 14.9m
Cunningham - 14.6m
McVeigh - 14.4m
Parker - 12.1m
Hannebery - 11.3m
Kennedy - 10.6m
Hewett - 8.7m

Are metres a widely available stat?

 

[RUNVS]

Are metres a widely available stat?

THey are if you know where to look.

Here shows the top 100 players in the league for metres gained

https://www.footywire.com/afl/footy/ft_player_rankings?year=2018&rt=LA&st=MG

and if you go on "advanced stats" for any player on footywire you will find their metres gained figure

eg

https://www.footywire.com/afl/footy/pp-fremantle-dockers--nathan-wilson?advv=Y

under "MG"

 

[Coach_Required]

The data is based on the past 2 years, not just 2018

There's always one poster who doesnt get the joke

 

[blitzer]

Here is a random question, and one not good enough for its own thread but I think is interesting, but if you were to make a best 22 based on one stat, and one stat alone, which stat would you pick?

By that I mean lets say you pick marks, that means you select a best 22 based on the player who takes the most marks for each position, so the ruckman who took the most marks on average, or the half back who took the most marks.

For me I would probably go with metres gained. Sure you would find some flawed players in the team, but I think it would be quite a damaging team when attacking, even if it might be a little defensively limited.

I dunno how it would go but score involvements would be pretty exciting. Probably means you'll have a fairly offensively geared defense but that's not so bad. You'd probably end up with key defenders like McGovern and Hurley I'm guessing.

 

[RUNVS]

I dunno how it would go but score involvements would be pretty exciting. Probably means you'll have a fairly offensively geared defense but that's not so bad. You'd probably end up with key defenders like McGovern and Hurley I'm guessing.

Score Launches you would get Lachie Henderson and Aaron Fransis and Goal Assists you would get Tom McDonald and Daniel McStay (though if you count Tom as a forward then the next choice would be Daniel McStay and Brody Mihocek).

 

[Sttew]

There's always one poster who doesnt get the joke

Didn't have my sarcasm meter on. My bad

 

[The Bomb]

https://www.foxsports.com.au/afl/ex...3/news-story/d1ae71a8b8ca64ea9391b31d71536506

Francis averaged 13.2 disposals and 6.4 marks in the Bombers’ last five games of the season, lighting up matches with his incredible ability to intercept and take a hanger.

Indeed, his performances were so stellar Champion Data has rated Francis as the best relative rated player in the AFL, leading the likes of Collingwood ruckman Brodie Grundy (+74%) and Brownlow Medallist Patrick Dangerfield (+72%).

 

[Jade]

https://www.foxsports.com.au/afl/ex...3/news-story/d1ae71a8b8ca64ea9391b31d71536506

Francis averaged 13.2 disposals and 6.4 marks in the Bombers’ last five games of the season, lighting up matches with his incredible ability to intercept and take a hanger.

Indeed, his performances were so stellar Champion Data has rated Francis as the best relative rated player in the AFL, leading the likes of Collingwood ruckman Brodie Grundy (+74%) and Brownlow Medallist Patrick Dangerfield (+72%).

Hardly a surprise. His talent has never been in question, only his application.

We'll see how he goes in 2019.

 

[Tony_Clifton]

It is actually pretty interesting how they work out their player ratings. Nevermind that they take the last forty games into account but how they figure out how much value to assign to each involvement in the play.

Someone posited earlier that a tackle and free kick in the forward fifty is worth more than one in the midfield. CD take this into account.

Basically what happens is they use machine learning to figure out the difference in expectations for the next score before and after an event.

Here is an example. Sidebottom has the ball in the middle of the ground. Expected next score is Collingwood. Its in the middle so instead of being +6, the machine learning gives it, say +1.2 based on historical averages. Sidebottom is tackled by Shuey resulting in a free kick to WestCoast. Now west Coast is +1.5. The net difference of shueys tackle is 2.7 (1.2 +1.5).

Tom Barrass has the ball in the goal square (expected next score wce 0.2), he is subsequently tackled by Stephenson resulting in a free kick on the line. This results in an expected next score of +6 coll. Stephenson play generates 6.2.

I hope this helps.
For more information please refer to https://researchbank.swinburne.edu.au/items/248ec147-72d7-448c-a19d-49f01d90b12f/1/

This is a link to Karl Jackson's thesis.

 

[Tony_Clifton]

Reminds me of the quote
" Statistics are used much as a drunk uses a lamppost: for support not illumination'

The media and punters are using the ranking to support their opinion that CD are ludicrously incorrect and statistics are stupid. Might we be better by trying to learn something from this. How does CD create these rankings? It surely wasnt stated behind the paywall. Given how they were created is there something to glean from unusual rankings like Brisbane and WC?

In this thread almost all the posters have been the drunk. And who can blame them when youve got BT and the duck on the tv catering to the lowest common denominator

 

[nameless]

The data is based on the past 2 years, not just 2018

Well based on the last 50 games (which is about 2 seasons worth of data) West Coast have the 2nd best win %, Brisbane have the 3rd worst.

To be honest, apart from that howler the list isn't terrible.

 

[Tony_Clifton]

Thought you guys might find this interesting.

Check out @AFLPlayerRating’s Tweet:

 

[Blues_Man]

2018

1. Sydney Swans – Five elite players (Lance Franklin, Dan Hannebery, Tom Papley, Josh Kennedy and Dane Rampe).
Note: The Swans also have a stunning 12 above average players.

2. Port Adelaide – Six elite players – (Robbie Gray, Paddy Ryder, Justin Westhoff, Charlie Dixon, Chad Wingard and Travis Boak).
Note: The Power has 10 above average players, with Jack Watts and Steven Motlop in that category. New recruit Tom Rockliff was rated average last year, largely because of injury.

3. Adelaide – Six elite players (Brodie Smith, Rory Sloane, Rory Laird, Eddie Betts, Tom Lynch and Taylor Walker).
Note: The Crows have five above average players.

4. GWS – Four elite players (Zac Williams, Toby Greene, Jeremy Cameron and Lachie Whitfield).
Note: The Giants have 10 above average players.

5. Melbourne – Four elite players (Jake Lever, Christian Petracca, Jayden Hunt and Tom McDonald).
Note: The Demons have eight above average players including Clayton Oliver, Max Gawn, Jack Viney and Nathan Jones.

6. Geelong – Four elite players (Patrick Dangerfield, Gary Ablett, Sam Menegola and Daniel Menzel).
Note: The Cats have seven above average players.

7. Western Bulldogs – One elite player (Jason Johannisen).
Note: The Dogs have nine above average players and 12 average players.

8. Richmond – Three elite players (Shane Edwards, Dustin Martin and Alex Rance).
Note: The Tigers have nine above average players.

9. Hawthorn – Three elite players (Ben McEvoy, Luke Bruest and Cyril Rioli).
Note: The Hawks have seven above average players.

10. Collingwood – Three elite players (Jeremy Howe, Scott Pendlebury and Jack Crisp).

11. Essendon – Two elite players (Anthony McDonald-Tipungwuti and Michael Hurley).
Note: The Bombers have nine above average players.

12. West Coast – Six elite players (Jeremy McGovern, Elliot Yeo, Shannon Hurn, Josh Kennedy, Luke Shuey and Nic Naitanui).
Note: The Eagles have two above average players. Andrew Gaff is listed as an average player.

13. North Melbourne – One elite player (Todd Goldstein).
Note: The Kangaroos have six above average players.

14. St Kilda – One elite player (Jack Sinclair).
Note: The Saints have seven above average players.

15. Gold Coast – Two elite players (Aaron Hall and Tom Lynch).
Note: The Suns have four above average players.

16. Brisbane Lions – Two elite players (Daniel Rich and Dayne Zorko).
Note: The Lions have four above average players, including Luke Hodge.

17. Fremantle – One elite player (Nat Fyfe).
Note: The Dockers have five above average players.

18. Carlton – One elite player (Sam Docherty).

https://www.sen.com.au/news/2018/01/31/champion-data-ranks-your-club's-list-for-2018/

wow ..this is ignorance on full display

 

[Blues_Man]

CD's stats and algorithms have far more credibility than the IPCCs flawed climate model predictions, which are never correct, yet I bet most of you lemmings worship the climate change hoax.

The irony.

Is that you Donald ?

 

[Jade]

Is that you Donald ?

Grammar is too good for Derp Donald.

 

[Tony_Clifton]

wow ..this is ignorance on full display

"Champion Data have released their list of how many elite players your club has entering the 2018 season. Classified as the top 10 percent of players in their position over the past two seasons"
Does this help?