AFL Rd 13 2024 Post Game Celebrations - Carlton vs Essendon

[kruddler]

Try this little exercise Kruds.

Go back over the last 50 years and look at our season goal tallies

I suspect what the 'extended data' will give you is a wide range of scores,

They'll be affected by

Our ability at the time
Pesonnel available
Coaches
Game plans
The way the games is played.
Rule changes.... and a host of other factors.

Each of these variables also affect the statistics of teams and individuals.
You often see a team change tack mid season and a weakness in the first half of the season becomes a strength in the second half..or at least not the same issue.

Watch Melbourne in the second half of the year....
With Petracca missing some may step up and increase their individual stats, others will find an extra burden and attention and their stats may actually drop...and that's just the effect of one player.

Football stats are more likely to have a very limited life span as variables affect the way the game is played.

Not suggesting otherwise lods. But that is the point. Looking at the data over a large period of time will show you these changes. As it will not just be club to club that is varying but league averages as a whole. Year to year, decade to decade.

The thing is though it will all be relative.  In the 70s all the teams were scoring more than any of the teams now. But there will be an average (afl/vfl wide) over that period and looking at the teams above that vs the teams below that will tell you a story of relative strengths to each other.

You can also analyse that to see how much better a team is vs the average at the time and that would be comparable to today.

In simplistic terms, looking at how many wins a team has will vary year to year with teams output but also amount of games in a season.
So instead look at % of game they have won.
A 18-2 team is the same as a 9-1 team, 90% win record. That eliminates the season length variable.
There are other tricks to use as well.

All data will fit on a bell curve with 99%(?) Of data fitting within 3 STD deviations of the mean. The further away from that the rarer it is....the outliers.

You compare year to year based off of that.
You could do it over a decade or 3 weeks or whatever time period you want.
But you 100% can compare and in an unbiased way.

I don't want to get bogged down in a maths lecture, suffice to say, low numbers does not make it negligible.