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Surprisingly Awesome Jazz Statistics

Joe Bagadonuts said:
Not sure he should have retired:
PG_PER_by_Season_-_Stockton_Nash_Kidd_Payton.png
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Funny that list doesnt include Steph Curry's 32 PER.
 
13901371_10154449961154468_3408934890026282700_n.jpg


1. So...Kidd has a bunch more games of 10 assists or fewer than Stock. None of these guys touch Stock in games with more than 10 assists.
2. I don't think it's a coincidence that there's a huge drop-off from 10 to 11 assists for Kidd and CP3. Dudes are trying to get those double-doubles and triple-doubles...Boler would be proud.


Note: Isiah, Magic and the Big O aren't included because basketball reference only has assist data back to 1983/84. Mark Jackson isn't included because **** that guy.
Note #2: Data from basketball reference...
 
GVC said:
13901371_10154449961154468_3408934890026282700_n.jpg
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Nice work. The nature of of what is being measured makes it looks like Kidd was more awesome than he was, though. If you added someone who hardly ever got an assist they would look even better than him because their far left plot points would be really high.
 
GVC said:
Yeah, although overlapping bar graphs isn't the way to go. Might do multi-color line graphs of top point guards in a few days; I can't afford to procrastinate any more today.
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What's your job? I think I recall you got your Master's in Eco years ago.
 
Joe Bagadonuts said:
Nice work. The nature of of what is being measured makes it looks like Kidd was more awesome than he was, though. If you added someone who hardly ever got an assist they would look even better than him because their far left plot points would be really high.
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1. You just have to know what you're looking at (a histogram). If you add all the heights here, you get total games played (regular season and playoffs). If you multiple the x-axis assist values by the associated y-axis games values and sum, you get total career assists.
2. The Stock and Kidd plots are the best to look at/compare IMO, since the other two players played fewer games. Essentially, the plots show that Kidd had more games of 10 or fewer assists, and Stock had more games of more than 10 assists.
3. Plotting the actual empirical distribution functions would make them more comparable -- and only requires dividing each value on the y-axis by each player's total games played. What you get here is a visualization of how the players got to their total career assists number.
 
Cunning Linguist said:
How far into getting the PhD are you and why are you quitting?
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Received candidacy/ABD a year ago, after two years of courses and finishing a (qualifying?) paper in another year, so four years in. Years 1 and 2 were not great, but I managed. Year 3 was a ****ing nightmare, but they set the bar low enough for me to get candidacy. I thought it was a good idea to give it another year, but I was both unproductive and miserable -- aside from learning some Python, and scraping and cleaning a **** ton of NBA data. It's to the point where I spend over 90% of my waking hours avoiding work and other people entirely. Not good. Fortunately, I'm in a big city with lots of job opportunities, and I've already done some effective networking through some friends. I suspect I'll have a decent job by the end of the month. Since I have candidacy, I can always re-apply or apply elsewhere if I want to go back, and not have to re-do any coursework. Seems unlikely, although I still plan to play around with the basketball data I have.
 
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GVC said:
Received candidacy/ABD a year ago, after two years of courses and finishing a (qualifying?) paper in another year, so four years in. Years 1 and 2 were not great, but I managed, Year 3 was a ****ing nightmare, but they set the bar low enough for me to get candidacy. I thought it was a good idea to give it another year, but I was both unproductive and miserable -- aside from learning some Python, and scraping and cleaning a **** ton of NBA data. It's to the point where I spend over 90% of my waking hours avoiding work and other people entirely. Not good. Fortunately, I'm in a big city with lots of job opportunities, and I've already done some effective networking through some friends. I suspect I'll have a decent job by the end of the month.
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Sounds like a plan. Good luck.
 
Here it is normalized for games played:
13914120_10154450240099468_1554177389055339120_o.jpg


And here's the cumulative distribution (note: I'm just connecting the points here):
13680211_10154450240299468_3559070344939279950_o.jpg
 
GVC said:
Received candidacy/ABD a year ago, after two years of courses and finishing a (qualifying?) paper in another year, so four years in. Years 1 and 2 were not great, but I managed. Year 3 was a ****ing nightmare, but they set the bar low enough for me to get candidacy. I thought it was a good idea to give it another year, but I was both unproductive and miserable -- aside from learning some Python, and scraping and cleaning a **** ton of NBA data. It's to the point where I spend over 90% of my waking hours avoiding work and other people entirely. Not good. Fortunately, I'm in a big city with lots of job opportunities, and I've already done some effective networking through some friends. I suspect I'll have a decent job by the end of the month. Since I have candidacy, I can always re-apply or apply elsewhere if I want to go back, and not have to re-do any coursework. Seems unlikely, although I still plan to play around with the basketball data I have.
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There's lots of opportunity with python out in the world, all while programming can be rewarding with the challenges it can present and the income it can provide. If you're into it that is
 
jope said:
There's lots of opportunity with python out in the world, all while programming can be rewarding with the challenges it can present and the income it can provide. If you're into it that is
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I'll likely end up doing analytical work in a government ministry or consulting firm. I should have plenty of opportunities to use Python -- It's a lot more flexible for data cleaning/management than (most/all?) statistical software (if STATA can do it, you can do it!). I'll probably pick up SQL at some point as well, as my basketball data -- particularly the raw player tracking data -- is unwieldy.

edit: I'm a lazy non-R user...should probably figure out R before moving on to SQL.
 
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Here's a lot more from Stock in a little infographic I made a year ago:
https://imgur.com/a/BA1oh
Here's some that I've found before that will get you excited for this season (I haven't read the thread yet, so there may be some others have said):

• When Rudy played more than 25 minutes this year the Jazz were 30-21 (48 win pace), less than 25 minutes or didn't play (injured games) Jazz were 10-21 (26 win pace)
• Jazz starting lineup for a lot of the year (Neto/Hood/Hayward/Favors/Gobert) had a NetRtg of 7.2, 8th best in the league for lineups with more than 300 MP.
• Gordon is the 4th best transition player in the league (min 200 poss). At 1.31 PPP he's only behind Lebron, KD, and Ariza. He's ahead of Curry, Antetekounmpo, PG, and lots more.
• Rodney is the 2nd best isolation player in the league (min 100 poss). At 1.08 PPP he's only behind Bosh. Ahead of Curry, Lebron, Durant, Westbrook, Lillard etc.
• George Hill is in the 85th percentile for spot up shooting at 1.11 PPP. Created the most spot up chances in the league last year, Pacers were 2nd to last. Giving him plenty more of these chances will only make him better. Our trio of PG's (Burke/Mack/Exum) last year shot at 1.02 PPP, or about 68th percentile.

Oh and this graph:
https://plot.ly/8/~rgiss/
Plot 8.jpg
 
Rgiss said:
Here's a lot more from Stock in a little infographic I made a year ago:
https://imgur.com/a/BA1oh
Here's some that I've found before that will get you excited for this season (I haven't read the thread yet, so there may be some others have said):

• When Rudy played more than 25 minutes this year the Jazz were 30-21 (48 win pace), less than 25 minutes or didn't play (injured games) Jazz were 10-21 (26 win pace)
• Jazz starting lineup for a lot of the year (Neto/Hood/Hayward/Favors/Gobert) had a NetRtg of 7.2, 8th best in the league for lineups with more than 300 MP.
• Gordon is the 4th best transition player in the league (min 200 poss). At 1.31 PPP he's only behind Lebron, KD, and Ariza. He's ahead of Curry, Antetekounmpo, PG, and lots more.
• Rodney is the 2nd best isolation player in the league (min 100 poss). At 1.08 PPP he's only behind Bosh. Ahead of Curry, Lebron, Durant, Westbrook, Lillard etc.
• George Hill is in the 85th percentile for spot up shooting at 1.11 PPP. Created the most spot up chances in the league last year, Pacers were 2nd to last. Giving him plenty more of these chances will only make him better. Our trio of PG's (Burke/Mack/Exum) last year shot at 1.02 PPP, or about 68th percentile.
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Now we just need to actually run in transition.

Sent from my A0001 using Tapatalk
 
My favorite "stat" for today: The assertion of the Jazz having the best bench in the league isn't really all that controversial over at RealGM. Hell, I have forgotten what a competent bench even looks like. . .
 
GVC said:
I'll likely end up doing analytical work in a government ministry or consulting firm. I should have plenty of opportunities to use Python -- It's a lot more flexible for data cleaning/management than (most/all?) statistical software (if STATA can do it, you can do it!). I'll probably pick up SQL at some point as well, as my basketball data -- particularly the raw player tracking data -- is unwieldy.

edit: I'm a lazy non-R user...should probably figure out R before moving on to SQL.
Click to expand...

Yeah we use SQLite and postgres to manage hundreds of thousands of real estate and retail data points where I'm at. Solid stuff and really not to bad to learn or manage.
 
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