BuzzerBeater Forums

Summary Data
As i said, 45 full and complete fully definable records were able to be used for the correlation.

But i was still able to get other things out from all the other data, which had some 150+ Box scores, and around 100 player stats.

(http://i980.photobucket.com/albums/ae282/regann0/Star-sal...)
OK so here we have just a listing of each Star rating, the end average salary of the player and the ACTUAL potential averages. (note - i should do a Star rating - salary range table. remind me would you!). I think the interesting part of this table, is the high average potential of a 4-star player.

(http://i980.photobucket.com/albums/ae282/regann0/Star-ave...)
This next picture shows the box score averages. In general, the higher the star player, the more points, rebounds, etc he will get. This basic summary is something i did early on to justify spending more time on the project, because if the star rating-box score averages showed an increasing trend, that would suggest that player stats would trend as well.

(http://i980.photobucket.com/albums/ae282/regann0/PlayerSt...)
This last picture is just an average of the end player stats i received. pretty even, except for ID and SB tend to be lower than the rest, suggesting that on average, the players have less inside defensive skills as a draftee.

Correlation

Notes about Correlation

So when I started to get some of the correlation values, I was surprised at how varied and low they were with some things. But then I remembered that, just because it’s a low relationship, doesn't mean its wrong right?

So I needed some kind of baseline, some kind of comparison correlation to see what the actual game says is correlated data. So I did a very small sample of my team's stats and last years player averages.
Now. I know this isnt 100% right, because I did training and it depends on quite a few things like gameshape, tactics etc.... - I just needed a guide really.

So I basically came up with the following guide for the Correlation Coefficient values that I felt meant something and these are what ive used in the draftee's to highlight relationships.

0 - 0.2 Pretty much no relationship
0.2 - 0.5 A decent relationship, but obviously nothing set in stone.
0.5 - 0.7 OK now we are talking about a consistent relationship
0.7 - 1.0 OUT OF THIS WORLD!

OK so this is just the basic Correlation matrix. every single box score item vs every single stat

Obviously SB and Minutes played have no correlation, but its all there. Ive bolded the items I think are relevent as per the above guideline.

(http://i980.photobucket.com/albums/ae282/regann0/Correlat...)

Note - ive just noticed that the picture is coming through really small, ill split it into two and re-post later on.

Per36min Correlation

So I starting thinking that stats for a guy who played 20 mins vs 40 mins is unfair, and i need normalised data. So i made the box scores into 'per 36 mins' values and ran the correlations again on that data. Here is the results.

(http://i980.photobucket.com/albums/ae282/regann0/Correlat...)

Again, small picture, will update later.

Interpretation

So, ive made my own conclusions which I would like to share as some discussion starters.
Taking a Myth-busters approach.

The following statement :

Box scores don't mean anything

I personally think ive busted this myth. Box scores DO mean something...... its not concrete, its not 100%, but they do mean something. Remembering that the highest value any stat will have is Respectable, its a scale of 7 numbers. And maybe not every element of the box score means something, but certainly looking at some of those correlations, I will be taking the box score into account with future decisions.

Assists
Really high correlation. obvious. No need for further discussion. EXCEPT FOR......

Turnovers
So we have this high correlation between passing and assists, yet why not a high correlation between Passing and turnovers?

OK thats all im going to talk about now because im tired :) DISCUSS PEOPLE!

Last edited by Coach Regan at 4/12/2014 11:15:58 AM

its just a shame i cant +1 more than one of your posts per 12hrs. Such a great post to wake up and read!

Ill add that the high stls to OD correlation is exciting to see, since OD is such an important skill to get.

its just a shame i cant +1 more than one of your posts per 12hrs. Such a great post to wake up and read!

Ill add that the high stls to OD correlation is exciting to see, since OD is such an important skill to get.

Could agree more. Great work coach.

Looks all pretty interesting. Have you considered running correlations for a few statistic combinations, like:
Assist to turnover ratio (may be a better indication of passing)
FG% and 3P% (May be an indication of shooting - though since you get higher correlations for FGA than FGM, perhaps not).
Percentage of shots attempted which are 3 point attempts (Could be a good indicator of JR).

One other thing you could consider is maybe running the correlations over groups of players, rather than the whole field. For example, there is a correlation between ID and rebounds, which make sense, because you would expect high ID players to be bigs with more of a chance to get rebounds. Maybe this correlation would disappear if you just ran the correlations for PF/Cs only (if this makes any sense!)

Yes, no, yes yes, no, sometimes and maybe.

when i ran the 3PT% and FT% in excel, i kept getting divide by 0 errors, so I parked that stat, but yes you are right with regards to these things, it is on my list to do.

Assis to turnover ratio - hadn't thought of that, and its easy to do, so ill add that to my list.

I can run the correlations based on the player position. That's also easy to do. and it would be interesting to see if the players classified as C/PF's have a higher correlation for things like ID and RB.

I can also run the basic stats broken down by position as well, but i don't want to go into too much. I think once the data is released into the free world, people can run their own things. :)

+1 Good job mate, taking a keen interest in your findings as I keep a close eye on box scores come draft time. Sorry I couldn't contribute this season but I didn't spend any points... Keep up the good work.

This is amazing work and must have taken a ton of effort. Reading all those tiny boxes makes my eyes bleed and I am sure you have a much better understanding of the data so what I would look for is something like...

Box Scores
FG%
relationship to JS = High
relationship to JR = Medium
relationship to DR = Medium
relationship to IS = Low
relationship to HA = Low
relationship to anything else = None

Turnovers
relationship to HA = High
relationship to PA = Medium
relationship to DR = Low
relationship to JS = Low
relationship to everything else = None

Blocks
relationship to SB = High
relationship to ID = Medium
relationship to IS = Low
relationship to OD = Low
relationship to RE = Low
relationship to everything else = None