Analysis The rebuild of Carlton and Brisbane and their future prospects

[SickQwon]

What absolute dribble.

There is no such thing as more accurate, the specific data set and what your are actually trying to convey will dictate which of mode, median or mean provides any value.

What value does median provide in this context?

StKilda’s 11th most experienced player had played 68 games and their 12th most experienced player 72, so a ‘median’ of 70.

Compared to Carlton’s 11th most experienced had played 49 and 12th most experienced 52, for a median of 50.5

But what does that tell you? What if the Saints had 10 guys with under 15 games??

Apart from detailing how many games the 11th most experienced player on the ground had played for each team what is median telling you?

It was the Saints that had a glut of really inexperienced players, 8 under 25 to just 4, the total games played by the respective inexperienced 11 was just 285 for StKilda compared to 305 from Carton’s least inexperienced 11.

StKilda were playing more raw kids.
Median doesn’t afford any special additional value.

Saints had the more raw kids, Saints also didn’t have the experienced veterans that the Blues had, but the Saints had 8 guys in the 50-100 games zone compared to just 6 for Carlton.

It's "drivel" by the way. My advice to you is to start off with a dictionary and then move onto maths. Didn't bother reading the rest of your comment.

 

[Hollow Knight]

It's "drivel" by the way. My advice to you is to start off with a dictionary and then move onto maths. Didn't bother reading the rest of your comment.

He’s right though, median is a really curious choice.

 

[Fadge]

He’s right though, median is a really curious choice.

Why is it curious?

If it aids their delusion, of course they're going to use it.

 

[btdg]

He’s right though, median is a really curious choice.

Why is median a curious choice? If you want to know a snapshot of the age and experience profile of a team it is clearly better than the mean:
- unlike the mean, it avoids being skewed by outliers, and is preferable given the data is not normally distributed
- it provides a useful reference point; half the players are older and half are younger. That's a tangible thing that has practical use. Similarly, it gives a decent snapshot of 'if you lined these teams up player for player, which team has more older / experienced players'.

You could always add info to it, of course, like the quartiles. Eg:
- For Carlton, the age quartiles were 21yr 60 days - 26 131 days; the experience quartiles were 30 games - 91 games
- For St Kilda, the age quartiles were 23yr 161 days - 25 yrs; the experience quartiles were 18 games - 95 games
Now, combined with medians, it suggests that Carlton were younger across most of the team, but their older players were older. St Kilda had more very inexperienced players, but the core of the team was more experienced.

Of course, you don't get bonus points for having a younger and less experienced team. You only get points for winning.

 

[doppleganger]

It's "drivel" by the way. My advice to you is to start off with a dictionary and then move onto maths. Didn't bother reading the rest of your comment.

I don’t really care whether it is dribble or drivel, your comment was crap.

There is no such thing as a ‘more accurate’ measure of central tendency.

The three standard measures all give different interpretations of a middle value and which is more appropriate is determined by the specific data set.

 

[doppleganger]

Why is median a curious choice? If you want to know a snapshot of the age and experience profile of a team it is clearly better than the mean:
- unlike the mean, it avoids being skewed by outliers, and is preferable given the data is not normally distributed
- it provides a useful reference point; half the players are older and half are younger. That's a tangible thing that has practical use. Similarly, it gives a decent snapshot of 'if you lined these teams up player for player, which team has more older / experienced players'.

It doesn’t do that at all.

All it does is compare whether the avg of the 11th and 12th most experienced / oldest players (the only consideration for median).

If you line up Saints v Blues player for player, the Saints were less experienced for the majority. That is what Marcel’s post fecking showed!!

From Mackenzie down, the 9 most inexperienced players were always the StKilda players (or equal).

In the middle Acres to Billings, the Saints were more experienced.

Then the senior end, again the Saints were less experienced.

Can even readjust the Blues senior ‘outliers’ and make them 175 games to equate for the Saints most experienced player and the Saints still come out less experienced.

But yeah, the Saints 11th and 12th most experienced players (Steele & Gresham) are more experienced than the Carlton equivalent player (Silvagni & SPS)....that is all the median is providing!

 

[vicpride]

Yeah, im not arguing against that. I im just saying.
Simpson isn't even an outlier despite how old he is so technically shouldn't be removed either. However, I think perspective needs to stated because average age doesn't paint the whole picture


Kennedy, Goddard, Lang and Fasolo all feature in the bests in our NB side, some reguarly. Its good to have decent depth even if they cost nothing. Kennedy earnt his spot against the Saints for example. Wanna talk about the ones that have been fantastic for us too?

You surely are joking, what relevance is depth if you they can't contribute to your season. The best for northern blues oh what a low bar you set. Pitiful recruiting any way you wanna slice it having seven players not make up your side in a team that has one win for the season. Who's been a fantastic recruit from another club? Thomas, McGovern have been shocking for the money they've stole. Lobee? Four year deal you guys took on. Shocking stuff all round

Sent from my SM-J810Y using Tapatalk

 

[LoungeLizard]

so if we have team A: 10x players at 28 and 12x players at 22= ave age of 24.7 median age=22
team B: 10x players at 24 and 12x players at 23= ave age of 23.5 median age =23

Team A is younger yeah?

Another way to look at it.
Team A: 10x players at 28 and 12x players at 19=median age of 19
Team B: 10x players at 24 and 12x players at 19=median age of 19

Oh look, they're the same age.

 

[Grand Uncle Horace]

When Carlton folk recourse to maths to find some solace in what is yet another ignominious year, it really just brings on the chortles.

The real maths interest is the desparate count of Jack Silvagni's game numbers. Can they get him to 100?

This thread was always a nonsense. Despite the pillaging, the Br'ions development is light years ahead.

 

[doppleganger]

so if we have team A: 10x players at 28 and 12x players at 22= ave age of 24.7 median age=22
team B: 10x players at 24 and 12x players at 23= ave age of 23.5 median age =23

Team A is younger yeah?

Another way to look at it.
Team A: 10x players at 28 and 12x players at 19=median age of 19
Team B: 10x players at 24 and 12x players at 19=median age of 19

Oh look, they're the same age.

Yep, as the Carlton wordsmiths have informed us - Median is a more accurate measure of central tendency than mean. Mean data is rejected by every scientist and engineer.

Absolute LOL!

 

[btdg]

so if we have team A: 10x players at 28 and 12x players at 22= ave age of 24.7 median age=22
team B: 10x players at 24 and 12x players at 23= ave age of 23.5 median age =23

Team A is younger yeah?

Another way to look at it.
Team A: 10x players at 28 and 12x players at 19=median age of 19
Team B: 10x players at 24 and 12x players at 19=median age of 19

Oh look, they're the same age.

Yes, those certainly are some unusual cases. I'm not sure they prove anything though.

It all depends on what information you are trying to get. The mean is useless for this type of data set. the median is not perfect, but contains SOME relevant info.

The 'mean' in a normal distribution is a 'representative' number - a single number that can give a snapshot of the dataset. In non-normal distributions, however, that is easily distorted. For example, in the case above, team A: the average age of 24.7 is not representative of anything. There are zero players on that team aged 24 and zero aged 25 (actually zero within 2 years either side of the supposedly representative number). 24.7 tells us absolutely nothing about what that team looks like. For the second team, we are closer to a normal distribution, of course, so the mean is actually fairly representative.

The median, on the other hand, gives a very consistent measurement in all circumstances. In every case, half the players are younger and half are older.
So what can we say as a result of the median? For team A, we can say that half the players in the team are 22 or younger and half are older. For team b, we can say half the players are under age 23, half are older. Those statements are accurate; whereas the mean for team A is not.

Now, is team A, or team B 'younger'? I don't even know that that means. How can a team be 'younger' than another? And in football terms, who cares? I brought medians into this thread, and stated quite unequivocably that you don't get bonus points for being younger. The number one thing that matters in football is winning.

However, if you are talking about development, there might be some use for this type of info, in that players tend to peak around age 23/24, and stay at their peak until about age 29, at which point they dip slightly until retirement. So, if 23/24 is the magic number, then we have a better question: which team is likely to develop further and which is closer to being at their peak?

If we go by the mean, we can't answer this question. The mean for team A suggests very little improvement, given a mean of 24.7 (above our magic number) . The mean for team B of 23.5 suggests a little bit of improvement left, but not much.

Now compare medians. The median for team A tells us that half the team is 22 or younger. That implies more than half the team is likely to improve, and that those players are probably 2 years or so from peaking; much more meaningful than the mean for that purpose. Similarly, the median for team B is 23, which suggests half the team still has some improvement left, but they have more players about to hit their peak than team A, and are therefore a bit 'closer' overall.

Thus, if I were in a thread about the development prospects of two teams, A and B, I'd prefer the median to the mean as a snapshot measurement of the two and their progress.

If I presented information that showed that the median for team A had dropped each year for the past 4, and was now at just 22, whereas team B had risen year after year and was now at around 24, I might conclude that team B is closer to peaking, while team A is probably a few years behind and not likely to be as competitive right now. If I pointed out that a median for 22 was the lowest I had found outside of expansion teams, indicating that team A was as far off its peak as any team I can think of... that might also be relevant too?

That was the whole point of raising that info - the median contains snapshot info relevant to this particular thread about Carlton and Brisbane.

It doesn't change how terribly Carlton are playing right now. It's possible to be both playing very bad football (even relative to age) AND still developing, right? It's not an excuse. You can be a mature team playing terribly (Melbourne) or a developing team playing well (St Kilda early in the season). And it doesn't say anything about likely future prospects except to say that there is improvement to come. But it is relevant to a thread about development, surely.

 

[LoungeLizard]

Yes, those certainly are some unusual cases. I'm not sure they prove anything though.

It all depends on what information you are trying to get. The mean is useless for this type of data set. the median is not perfect, but contains SOME relevant info.

The 'mean' in a normal distribution is a 'representative' number - a single number that can give a snapshot of the dataset. In non-normal distributions, however, that is easily distorted. For example, in the case above, team A: the average age of 24.7 is not representative of anything. There are zero players on that team aged 24 and zero aged 25 (actually zero within 2 years either side of the supposedly representative number). 24.7 tells us absolutely nothing about what that team looks like. For the second team, we are closer to a normal distribution, of course, so the mean is actually fairly representative.

The median, on the other hand, gives a very consistent measurement in all circumstances. In every case, half the players are younger and half are older.
So what can we say as a result of the median? For team A, we can say that half the players in the team are 22 or younger and half are older. For team b, we can say half the players are under age 23, half are older. Those statements are accurate; whereas the mean for team A is not.

Now, is team A, or team B 'younger'? I don't even know that that means. How can a team be 'younger' than another? And in football terms, who cares? I brought medians into this thread, and stated quite unequivocably that you don't get bonus points for being younger. The number one thing that matters in football is winning.

However, if you are talking about development, there might be some use for this type of info, in that players tend to peak around age 23/24, and stay at their peak until about age 29, at which point they dip slightly until retirement. So, if 23/24 is the magic number, then we have a better question: which team is likely to develop further and which is closer to being at their peak?

If we go by the mean, we can't answer this question. The mean for team A suggests very little improvement, given a mean of 24.7 (above our magic number) . The mean for team B of 23.5 suggests a little bit of improvement left, but not much.

Now compare medians. The median for team A tells us that half the team is 22 or younger. That implies more than half the team is likely to improve, and that those players are probably 2 years or so from peaking; much more meaningful than the mean for that purpose. Similarly, the median for team B is 23, which suggests half the team still has some improvement left, but they have more players about to hit their peak than team A, and are therefore a bit 'closer' overall.

Thus, if I were in a thread about the development prospects of two teams, A and B, I'd prefer the median to the mean as a snapshot measurement of the two and their progress.

If I presented information that showed that the median for team A had dropped each year for the past 4, and was now at just 22, whereas team B had risen year after year and was now at around 24, I might conclude that team B is closer to peaking, while team A is probably a few years behind and not likely to be as competitive right now. If I pointed out that a median for 22 was the lowest I had found outside of expansion teams, indicating that team A was as far off its peak as any team I can think of... that might also be relevant too?

That was the whole point of raising that info - the median contains snapshot info relevant to this particular thread about Carlton and Brisbane.

It doesn't change how terribly Carlton are playing right now. It's possible to be both playing very bad football (even relative to age) AND still developing, right? It's not an excuse. You can be a mature team playing terribly (Melbourne) or a developing team playing well (St Kilda early in the season). And it doesn't say anything about likely future prospects except to say that there is improvement to come. But it is relevant to a thread about development, surely.

It tells you jack.
My examples are a point to show how skewed it can be.

Experience is what matters, a 23 year old who has played 100 games, is most likely going to be better value than a 23 year old who has played 50 games or less.

Your view they are the same.

 

[btdg]

It tells you jack.
My examples are a point to show how skewed it can be.

Experience is what matters, a 23 year old who has played 100 games, is most likely going to be better value than a 23 year old who has played 50 games or less.

Your view they are the same.

No, the point is that the median is NOT skewed. Regardless of the data, half the numbers will be above, and half below. Whether that information is interesting or relevant is up for debate (in this case I think it is, and I've made my case for it), but the median won't be skewed by non-normal data. That's the whole point.

Age does matter quite a bit - very few players are physically at their peak at age 19-20 (I can really only think of a few small forwards whose biggest weapon is pace). However, its not the only thing, and you'll note that in my original post on Carlton and Brisbane I cited both age and experience. For reference - Carlton's median of approx 40 games is substantially less than Brisbane's (around 70).

Again, that median for Carlton is very low; I was able to find a few similar comparisons (eg: Melb at their lowest point); but no teams at full strength who were substantially lower other than expansion teams. So again, that implies that Carlton have quite a bit of development left as they get more experience, while Brisbane are a bit closer to their peak - which was the point of this thread.

The St Kilda comparison posted by someone else is interesting, because St Kilda have quite a few unusual players in their team, who have come from state leagues and are therefore aged 23 but with less than 10 games experience. I think they'll be an interesting test case on whether experience or age matters more - seeing how those blokes develop will be interesting. Geelong have had guys like Tim Kelly and Tom Stewart come in and definitely get better with experience. Whether that holds up for St Kilda will be interesting to watch. Given Carlton now have Gibbons and DeLuca who fit that bill, I'm hoping there's room for improvement there too!

 

[LoungeLizard]

No, the point is that the median is NOT skewed. Regardless of the data, half the numbers will be above, and half below. Whether that information is interesting or relevant is up for debate (in this case I think it is, and I've made my case for it), but the median won't be skewed by non-normal data. That's the whole point.

Age does matter quite a bit - very few players are physically at their peak at age 19-20 (I can really only think of a few small forwards whose biggest weapon is pace). However, its not the only thing, and you'll note that in my original post on Carlton and Brisbane I cited both age and experience. For reference - Carlton's median of approx 40 games is substantially less than Brisbane's (around 70).

Again, that median for Carlton is very low; I was able to find a few similar comparisons (eg: Melb at their lowest point); but no teams at full strength who were substantially lower other than expansion teams. So again, that implies that Carlton have quite a bit of development left as they get more experience, while Brisbane are a bit closer to their peak - which was the point of this thread.

The St Kilda comparison posted by someone else is interesting, because St Kilda have quite a few unusual players in their team, who have come from state leagues and are therefore aged 23 but with less than 10 games experience. I think they'll be an interesting test case on whether experience or age matters more - seeing how those blokes develop will be interesting. Geelong have had guys like Tim Kelly and Tom Stewart come in and definitely get better with experience. Whether that holds up for St Kilda will be interesting to watch. Given Carlton now have Gibbons and DeLuca who fit that bill, I'm hoping there's room for improvement there too!

Yeah 1/2 are above and below, but have a look and my 2nd point above, which team would you take?

It's skewed.


Experience doesn't just come from playing AFL, kids playing against men get experience.

 

[Viceregal]

Oh good this thread has morphed into a debate about the pros and cons of various statistical measurement tools … somehow this thread seems to find new (and uninteresting) ways to get off topic (yet sadly I keep it on my watch list for some reason I may need to get professional psychological assistance with)...

 

[Fadge]

No, the point is that the median is NOT skewed. Regardless of the data, half the numbers will be above, and half below. Whether that information is interesting or relevant is up for debate (in this case I think it is, and I've made my case for it), but the median won't be skewed by non-normal data. That's the whole point.

Age does matter quite a bit - very few players are physically at their peak at age 19-20 (I can really only think of a few small forwards whose biggest weapon is pace). However, its not the only thing, and you'll note that in my original post on Carlton and Brisbane I cited both age and experience. For reference - Carlton's median of approx 40 games is substantially less than Brisbane's (around 70).

Again, that median for Carlton is very low; I was able to find a few similar comparisons (eg: Melb at their lowest point); but no teams at full strength who were substantially lower other than expansion teams. So again, that implies that Carlton have quite a bit of development left as they get more experience, while Brisbane are a bit closer to their peak - which was the point of this thread.

The St Kilda comparison posted by someone else is interesting, because St Kilda have quite a few unusual players in their team, who have come from state leagues and are therefore aged 23 but with less than 10 games experience. I think they'll be an interesting test case on whether experience or age matters more - seeing how those blokes develop will be interesting. Geelong have had guys like Tim Kelly and Tom Stewart come in and definitely get better with experience. Whether that holds up for St Kilda will be interesting to watch. Given Carlton now have Gibbons and DeLuca who fit that bill, I'm hoping there's room for improvement there too!

I don't particularly care for whether mean or median is a better statistical measurement.

The only statistic I care for is 4 wins from their past 41 games.

That tells me everything I need to know about how Carlton are tracking at the moment.

 

[Malifice]

What absolute dribble.



Saints had the more raw kids

No they didn't. Carlton played 12 players aged 18-22 (including 3 teenagers). The Saints played 4 players aged 18-22 (and no teenagers).

The Saints had conditioned senior bodies. We were a squad comprised of mostly kids drafted in the past 3 years.

That's why median age and games matter. Kade Simpson and Daisy Thomas leading a squad of teenagers is not the same as a team of mostly 23-28 year olds.

If you cant see why, you dont understand football.

 

[buttermuffs]

Neither mean or median is a be all or end all when comparing teams or seeing how experienced they are. It’s good to have a measure that isn’t skewed by outliers such as Simpson or Murphy; however, it’s also important to include them as having experienced players on your side makes an impact on how a team performs.


On iPhone using BigFooty.com mobile app

 

[btdg]

Neither mean or median is a be all or end all when comparing teams or seeing how experienced they are. It’s good to have a measure that isn’t skewed by outliers such as Simpson or Murphy; however, it’s also important to include them as having experienced players on your side makes an impact on how a team performs.


On iPhone using BigFooty.com mobile app

Of course its not everything, and ultimately, putting together a winning squad is what matters, however you do it. There's no bonus points for being younger.

I originally posted the medians to make what I thought was an interesting point, though: over the past 4 years, Brisbane have increased their median age and experience each year (give or take a few small ups and downs). Carlton's median age/experience has gone down each year, and this year is so low it stands out in historical terms.

Could be interpreted in a number of ways, including that Carlton have been stupid in stripping their list back to such a young level (and leaving the young kids ripe for another poor season), while Brisbane have been successful in building around young players. Or that Carlton are a couple of years behind and probably shouldn't expect to really jump up the ladder for another 2 years (which seems crazy - but that's where the numbers are at).

 

[TheShardMan]

If i were a carlton fan id be worried that a 1st year player has come straight in and become their 2nd best player. I dont see many of their young so called stars stepping up at all. Who has progressed? Sps? Weitering? Plowman? Dow? Obrien? Marchbank? Kennedy? Setterfield? Fischer? Curnow? So many others. Mckay has improved this year but im really struggling to find any others.

 

[vicpride]

If i were a carlton fan id be worried that a 1st year player has come straight in and become their 2nd best player. I dont see many of their young so called stars stepping up at all. Who has progressed? Sps? Weitering? Plowman? Dow? Obrien? Marchbank? Kennedy? Setterfield? Fischer? Curnow? So many others. Mckay has improved this year but im really struggling to find any others.

This right here is the argument that is being forgotten. You're spot on Curnow, SPS,
Weitering, are not coming on. They'll all be decent AFL players but Elite? they'd wanna get a move on.

Sent from my SM-J810Y using Tapatalk

 

[btdg]

If i were a carlton fan id be worried that a 1st year player has come straight in and become their 2nd best player. I dont see many of their young so called stars stepping up at all. Who has progressed? Sps? Weitering? Plowman? Dow? Obrien? Marchbank? Kennedy? Setterfield? Fischer? Curnow? So many others. Mckay has improved this year but im really struggling to find any others.

Progression is slower than we think...

Some simple comparisons, though, using what I would consider key stats for each player:

SPS: 2017 - 14 disposals, 0.5 goals, 4.2 tackles. 2018 - 16 disposals, 0,2 goals, 4.1 tackles. 2019 - 20 disposals, 0.3 goals, 4.4 tackles
He's improved incrementally each year, and had one dominant / breakout game this year. Going ok.


Weitering: 2016 - 14.5 disposals, 3.5 1%ers, 5.5 intercepts. 2017 - 13.7 disposals, 3.6 1%ers, 4.3 intercepts. 2018 (only 14 games) - 13.5 disposals, 4.9 1%ers, 4.3 intercepts. 2019 - 14 disposals, 6.8 1%ers, 7.7 intercepts
Struggled in year 2 and 3 after being played forward, and then with injury last year. This year, big jump in defensive stats and is 12th in the league in intercept possessions - having a really good year (although poor the last 3 weeks).

Plowman: 2016 - 12 disposals, 5 one-percenters, 3.7 intercepts. 2017 - 14.3 disposals, 4.1 one-percenters, 5.3 intercepts. 2018 (injury affected) - 11.9 disposals, 5.7 one-percenters, 4.5 intercepts. 2019 - 16.2 disposals, 4.7 one-percenters, 6.6 intercepts
Dipped last year, but otherwise consistent improvement. 2019 is his best year for disposals and intercepts.

Dow: 2018: 14.2 disposals, 3.2 tackles, 67% DE. 2019: 17.1 disposals, 2.7 tackles, 64% DE.
Has improved his output, tackling has dropped, and disposal still an issue. From observation, his disposal has been improving over the course of this season, but yet to show through in the stats

O'Brien: 2018: 13.9 disposals, 1.4 tackles, 0.1 goals. 2019: 10.3 disposals, 1.2 tackles, 0.5 goals.
Has moved up the ground more. Can't find the football, but has at least hit the scoreboard. Hasn't improved overall

Marchbank: Was better across the board (all relevant stats categories) in 2017. Can't be bothered typing it out, but he was good then, had a terrible run with injury last year, and has been less good this year. Hasn't improved

Kennedy/Setterfield - both haven't played enough games to track. Setterfield - there's no baseline and he is coming off an ACL. Hard to judge. Kennedy - only 1 game this year and it was on Sunday. Not improving as we would like, though.

Fisher - 2017: 11.8 disposals, 2.9 tackles, 0.2 goals. 2018: 19.2 disposals, 3.5 tackles, 0.5 goals. 2019: 20.9 disposals, 3.3 tackles 0.5 goals
Made a big jump last year, and probably slightly better this year.

Charlie Curnow - Made a big jump last year, his numbers this year are back to 2017 levels. Has been out of form and injured this year.

Some others:
Harry McKay: Made a big jump last year. Believe it or not, his disposal, goal, tackle and mark numbers are basically identical to 2018. Has taken a lot of contested marks but I'm suspicious about those stats (I think he gets paid 'CM' for marks that other players don't due to technique when marking on the lead). Probably fair to say incremental improvement is occurring, though.
Jack Silvagni: In 2019 has career highs in goals, disposals, marks and tackles. Has got better each year (still only 21)
David Cuningham: In 2019 has career highs in goals, disposals, and a big jump in some peripheral stats like I50s. Consistent in tackles. Just turned 22, and this year's numbers are despite some bad injury luck (a ruptured Kidney).

So overall:
Improving ok - Weitering, SPS, Plowman, Dow, Fisher, Silvagni, Cuningham, McKay
Have improved, but out of form/bad year: Charlie Curnow,
Not good, but not necessarily bad: Kennedy, Setterfield, and a couple of others not mentioned due to injury (De Koning,
Not improving as hoped: Marchbank, O'Brien,

Every one of those players except Plowman is still under 23. The only worry I'd have is Marchbank - who looked a few years ago like being a star, and now seems just an ordinary defender. Probably 2/3 of those young blokes are tracking well though, another couple having injury issues, and a couple not going as hoped. Seems about right to me. The problem is that the team has got younger each year, so more is expected of players who haven't hit their primes yet.

 

[La Dispute]

I swear Harry McKay is just too big for any 190cm defender covering him on transition, which is why he gets so many contested marks down the line.

Helps having 3 big key forwards in the team, to create the contests to advantage. (Or at least it helps McKay, the jury is out on whether it’s helping us)

 

[Kreuuuzeurns]

This right here is the argument that is being forgotten. You're spot on Curnow, SPS,
Weitering, are not coming on. They'll all be decent AFL players but Elite? they'd wanna get a move on.

Sent from my SM-J810Y using Tapatalk

How many 4th year KPP are elite? Andrews is probably an outlier there, credit to the lions. Weitering is coming on perfectly fine IMO and has been one of our better performers this year (with no Newman, Simpson, Docherty and Jones for big chunks of the season). Curnow has been a worry this year but 10 games ago he was well on his way. I notice you didn’t mention McKay who is tracking perfectly.

And again with the mids, SPS and Dow in particular are not elite yet but what 20 year olds are? McCluggage looks brilliant but he has Neale, Robinson, Zorko and Lyons along side him.

People forget how young these guys are and what they are being asked to do. Maybe that’s a knock on SOS’ recruiting but I’m still of the belief that by 2021/22 whoever has our list will be in a great position.

 

[Tushay]

It doesn’t do that at all.

All it does is compare whether the avg of the 11th and 12th most experienced / oldest players (the only consideration for median).

If you line up Saints v Blues player for player, the Saints were less experienced for the majority. That is what Marcel’s post fecking showed!!

From Mackenzie down, the 9 most inexperienced players were always the StKilda players (or equal).

In the middle Acres to Billings, the Saints were more experienced.

Then the senior end, again the Saints were less experienced.

Can even readjust the Blues senior ‘outliers’ and make them 175 games to equate for the Saints most experienced player and the Saints still come out less experienced.

But yeah, the Saints 11th and 12th most experienced players (Steele & Gresham) are more experienced than the Carlton equivalent player (Silvagni & SPS)....that is all the median is providing!

Good teams are built on the 23-29 demographic, with a good spread either side. The median is much more relevant than the average.