Hoops

NBL Player Cluster Analysis

Few people are working with basketball data in Australia and this work should be praised at every opportunity.

"Could a smart coach use this analysis to determine changing needs in the league? Ie look at which clusters are more strongly represented in the more successful teams."

Here's your ideal team to aim for. :P

Wildcats 2018/19

Ball dominant studs: nil
The Gunner: Cotton, Terrico
Defensive Ball Handler: Martin
Backup Gaurd: Dech
3pt Specialist: Steindl
Verstile Floor Spacer: Wagstaff, Norton
3 & D: Hire?, Vague
Q Forward: Brandt, Kay
Defence First Big: nil
Offence First Big: nil
Traditional Big: nil
High Usage Big: Jervis

Could a smart coach use this analysis to determine changing needs in the league? Ie look at which clusters are more strongly represented in the more successful teams.

"Hey guys, thanks for the feedback"

Awesome work Andrew, it would be interesting to see if players who change club change their "cluster" group. Conger had very different roles with Hawks and 36ers, with Hawks really exploiting his strengths and 36ers using him more in a "role". Shawn Long could alter clusters slightly by moving to United, but presume he would stay similar with just less volume. Gliddon from Taipans to Bullets, Creek from 36ers to Phoenix, etc etc. Interesting stuff.

Surely for all this to make it viable, time on the court has to be taken.

Andrew - great work here. Love how guys like yourself can translate data/analytics in a format fans can understand.

Things I'm intrigued about:
1. The fact the NBL has plenty of local, backup guards - enough so that we could make a separate category for them.
2. Seeing the import spreads is also interesting. Would be intriguing to see how the different clusters sat on teams' rosters to see what the trends are.
3. Interested to see which players were borderline between two clusters, as there seem to be some odd pairings.

Will need more time to unpack the insights here.

The only way I can think of to determine that is if you basically do as I suggested above, "if Conklin played a season with Adelaide would his stats for that season reflect a "quality forward"?".
So that would involve tracking players who change clubs and seeing if they're stats for that year fall into a different cluster based on the coach

Adelaide have that really obvious clustering but there is the potential there are other clubs displaying that effect albeit, less dramatically. For instance, maybe just one position rather than all bigs.

For the most part I agree with you though, they do look like they fit their clusters really well and damn it's satisfying when they do (for those that don't know cluster analysis usually takes a long time to give you hot garbage). And if there is a system effect going on I do think it looks like it's impacting the "big" clusters more than the outside players

Hey guys, thanks for the feedback

I'll try to answer a few of the questions -

Firstly this wasn't created with the intention of building rosters or picking starting fives, it's more a 'general interest' piece grouping together similar players to create discussion around the traditional five playing positions.

Down the track we will look to see if these groupings provide insight into which combinations of players in lineups perform well or poorly in certain situations, or against other combinations. A number of you have illuded to this outcome already. It was a significant undertaking getting it to this point, so we decided to publish the first stage and any resulting stages separately.

Secondly, it was an interesting point raised around whether a player fits in a cluster because of their nature, or because of the system they are in - with Adelaide being an example. While I don't have the answer to this (not sure if there is one, kind of a chicken and egg situation). My guess would be it's the former. Coaches usually know what type of player they need in their system and recruit accordingly. This usually serves to reinforce a player as a particular type as they are asked to perform the same role for different teams. We have used 4 seasons worth of data to try and smooth out any difference that may occur if players swap teams/systems, but only within the NBL. From the eye test, I think you'll agree there are very few that you could argue against the group they've been placed into.

Anon #763516 nailed it with their take on how clustering works, an individual will be placed within existing clusters and one player would never have a big enough effect on the entire league to shift the needle. A player like Lamelo will fit within one of these clusters, no problems. And good spotting on the Kickert one too, that's the one that's been bugging me too!

Thanks for the feedback team! Glad it's creating conversation

Is this piece saying these are the ONLY clusters or just the clusters that have appeared in the NBL over the past 5yrs?

Cool article, but I don't think you'd pick your starting 5 out of this. I think it would be more useful to see what type of player your team is missing or looking at compatibility, for example not wanting 3 imports that are "ball dominant studs" which I think teams do pretty well most of the time in the NBL.

The guys who made this would know far better than myself but typically when performing cluster analysis, the user needs to refine the number of clusters that exist. This is a bit of a balancing game as less clusters means more outliers and guys being put in groups where they don't really fit (perhaps your LaMelo yes) but more clusters means less classification power. What's the point of having 50 clusters with 4 guys in each? just can't use that.

So to answer you question in short, there are guys who might not fit in clusters and probably already are in the dataset (notice kickert perhaps a little out of place?) but they will still be put into the best available cluster, not creating their own new cluster

The Lemanis Bullets2Boomers arse-licking cluster is missing.

Really interesting and amazing that someone would put the time and effort into this (bonus points for r plots)

But as a researcher I must point out the potential interpretation error. Almost all recent Adelaide bigs (excluding Hodgson and Jacobson) are in one cluster. This could indicate that Joey is recruiting a very specific type of big for his system and would be fine with the current interpretation of this data. The alternative, however, is that the stats reflect the system they are in and the role they are asked from that team and NOT the potential or skill set of the player. eg. if Conklin played a season with Adelaide would his stats for that season reflect a "quality forward"?

That's brilliant. Thanks for posting.

Zaine Allen has stated that he can't wait to join the gators for 2013. Played today for the gators against Wodonga and loved it. Zaine has been quoted saying "McKinnon don't pass me the ball and they are no good". Coach Steve Noia had stated that "we are expecting Zaine to sign tonight"