Previously I took my machine learning algorithm and found line-up specific insights for the Dallas Mavericks.
Post can be found here: http://www.zigzaganalytics.com/home/getting-the-most-out-of-nba-lineups-with-machine-learning
An example of an insight learned being how the Mavericks really struggle with Dirk at the 5 spot. Most notably the struggles come in terms of defensive rebounding and rim protection, but can cover for this by playing Dirk next to Dwight Powell as much as possible and be a positive +/-
For this post, I have taken a similar deep dive into Miami Heat line-ups utilizing machine learning and here are the results...
The really interesting and surprising insight being the negative impact Goran Dragic is having on heat line-ups this season, with line-ups 2 & 4 both having a negative +/- to demonstrate this.
Dragic is a -2.3 +/- per game this season vs +0.9 last season and +2.8 the season before.
The downward trend is concerning.
The algorithm found to be of most concern, Dragic's inability to get to the free throw line and Dragic line-ups not getting up 3's at a rate that Miami's offensive strategy requires.
Most analysts would say "Time to trade Dragic!" and hit the trade machine for some fake trades. But how about we look into how we can make Dragic line-ups more effective....
30% of Dragic's shot attempts are from 3 vs the Heat's team average of 39% of shots from 3. One solution may be encouraging Dragic to change his mix of shots and shoot 10% more 3's (getting him in line with Miami's average) and ditch some drives to the basket that aren't generating free throws anyway.
This would mean getting up 1.5 more 3's per game (going from 4.1 to 5.6 attempts) and taking them away from drives.
Seems pretty reasonable in terms of applying the mix change, with Dragic shooting 36% from 3 this season which is a good rate. It wouldn't be a drastic change to what Dragic is doing, but will impact positively on line-ups he is a part of.
It's also much easier to adjust Dragic's game in terms of shot mix vs working on getting him to the free throw line more often at this stage of his career. Perhaps something for Dragic to work on in the off-season.
Again, I hope this post showed the power of what machine learning can do in terms of honing in on specific line-ups, then taking those findings and digging a little deeper into the numbers.
Ultimately "analytics" (I hate referring to it as that) is about taking all of this data and putting it into a format and language that coaches can make adjustments with, otherwise it's just useless numbers on a page.
Again I hope I have demonstrated how that can be done with the Dragic analysis.
Next up, I'll dive into the Cleveland Cavaliers.
(Thanks again to @nbastuffer https://www.nbastuffer.com/ for providing all of the NBA play by play data)
Continuing on with the machine learning theme of the last few posts, where previously I had looked at how a high level scouting report can be created for teams. I now wanted to get into some nitty-grity detail and see what insights machine learning can discover in terms of specific 5 man line-ups.
My last few posts have been based around producing a scouting report from a machine learning algorithm I have put together.
Where is the future for NBA analytics going? The buzz words you will hear more and more over the next few years will be “artificial intelligence”, “machine learning” and “deep learning”.
This is one of the hardest measures in basketball, how good or bad of a job is a head coach doing?
NBA Summer League is pretty early to call “bust” isn’t it? Yeah it sounds crazy and it might be rash, but hang in there with me.
For more than 25% of NBA teams, the first offensive set of the game looks to be predictable.
We have hit a milestone in the NBA schedule as we move through Christmas. So what better time to check in and analyze which players are hurting their teams, with poor on court decisions and simple skill errors which I tally up in my Coach Killer metric.
“Coach Killer” as defined by urbandictionary.com – "Any dumb or accidental action that causes an enormous let down, especially if it occurs at a critical time ".
The humble on-ball screen has been around since the beginning of basketball. For decades the formula has been simple, send one of your team's big guys to set an on-ball screen for your guard and that in itself will create a heap of options offensively. Whether it be allowing the guard to drive to the basket, the big guy to roll to the basket or the big popping to the perimeter to shoot a 3 to name a few.
The 6 point swing.
One of the biggest perceived momentum changing plays in basketball, where a team misses a 3 point shot and the opposing team drills a 3 pointer on the very next play, therefore causing a 6 point swing...
The latest reports have Stephen Curry coming back from injury sometime in the 2nd round series vs the Portland Trailblazers. The Blazers will be looking to steal early wins in the series whilst Curry sits, but how are they going to do it? And what adjustments are the Warriors making without Curry?
Here is the scenario:
Well maybe not totally forget about them, but regardless of what schemes a team tries to implement to stop the duo they are going to score whether the Thunder win or lose. More about that later.
Limit elbow touches, paint touches, post touches and passes out of the post. Simple right?
Make him do a left hand layup. That sounds pretty basic and logical right? Basketball 101 stuff? It is that basic.