2017_____N–B–A–S–T–A–T–S_____2018

i was poking you with the simmons=pg talk.

i remember rondo taking a lot of elbow jumpers w the celts?

lol

https://i.imgur.com/q3s4O2J.png

i was poking you with the simmons=pg talk.

― Spottie, Thursday, December 28, 2017 12:10 PM (forty-six seconds ago) Bookmark Flag Post Permalink

ha yeah it just occurred to me that there was in fact a point guard weird enough to play like that

the elbow jumper was the one shot he cld hit (in 2010)

yeah he was good at that!

i cant remember what jason kidd was like before he started jacking 3s

i think he always kinda took a lot of threes, and mostly missed them until late in his career, other things he did iirc: unstoppable on the break both with passing and finishing, decent driver in the half court because of strength and handle but a bad finisher because of not great ups and zero scoring touch, missed a ton of shots from everywhere but continued to shoot lol

great defender too, cld guard both backcourt spots

its pretty crazy how high he is in the all time 3 pointers list

https://i.imgur.com/payEHK5.jpg

went through some tuff times in phoenix

bleached tips ruined a lot of lives tbf

yeah the nba stats landscape is a complete mess, baseball is so far ahead of them in terms of making actually interesting stats available to average fans

baseball is so easy to stat

this is true but I was referring to making stats easy to find for fans, like for baseball you basically just need fangraphs, baseball reference, and statcast to be fluent in baseball stat conversations. with basketball half of the stats dudes like zach lowe talk about are either proprietary, you have to pay for it, or it’s spread out over like 20 sites

yeah i just wonder what the issue is as far as supply/demand, feel like a lot of the basketball stats are just not very good and people dont want them

where baseball is just more a natural fit for statistical analysis so its flourished there, and even long before the analytics revolution baseball was always more numbers minded

with basketball stats always need to be contextualized and the best of the new breed are the more granular infos like shot distributions player tracking etc so it makes sense that its filtered through writers to make sense of it all, in contrast to baseball where u can throw out a good catch all stat like WAR thats actually useful, having said that it wld be cool if that granular data was more available and presented in good visualizations etc

yeah the ux is a nightmare, i get to the nba stats site and have no idea where to start or what to click on. bball reference is a little better but it looks like a ten year old site at hie point.

feel like if you're not on a 30" monitor for the nba stats site then dont even bother

so many columns, much rows, very tabular data

love to have the data in front of me

gotta have my datum

baseball has so many isolated, individual actions (batting and pitching) that happen thousands of times in the exact same way over there course of the season

football seems like it's even more difficult for analytics than basketball, like an individual running play - did the back make a great move or power through contact? did the blocking scheme result in a big hole? did an individual o lineman overpower someone? did someone take a bad angle? tackle poorly? misread the play? seems nearly impossible to use analytics in meaningful ways

yeah the current football analytics are horseshit.

yeah and the whole concept of downs really complicates things too, a good football analytics running joke is how footballoutsiders consistently rates the patriots as a middling to good team while they continue to produce the actual greatest results the game has ever seen

nba.com and that tweet have him taking 9 3s so far where the charts show 1 and 0 respectively?

― lag∞n, Friday, 29 December 2017 3:54 AM (four hours ago) Bookmark Flag Post Permalink

heaves?

this is an interesting discussion

part of the problem as alluded to upthread is that the baseball stat revolution happened before anyone including teams realized such information was worth being commodified, so bill james, tom tango etc were just working in the public sphere bcuz they had no choice. so pretty much the entire foundation of advanced stats in baseball is publicly available formulas. basketball came after that commodification... ben falk's site is a great example of something that would have been free if it started even 5 years ago.

i do wonder if there's some market for a fangraphs of basketball, basically... a place that centralizes the main advanced stats and publicizes some proprietary info (fangraphs buys info from firms) while also running an editorial site that contextualizes all of that w/ articles. maybe this exists and i don't know about it but it seems like the current relationship b/w basketball writing and basketball stats are sites that publish the stats and then writers that contextualize on mainstream sites or smaller blogs.

seems like "the analytically minded basketball fan" has kinda moved on from advanced stats to understanding basketball plays which is interesting in that it runs contrary to numbers guys hierarchy of knowledge

but i think its correct as far as how basketball functions the scheme is the most fundamental thing its the context on which everything else depends

statistic strives to normalize the scheme in order to make an apples to apples comparison across the league but its just really hard, maybe impossible, and maybe not that useful from a teams perspective for actual basketball business which is interesting

the big catch all stats are failures but the granular data is easily understood within the context of the scheme and is translatable across schemes if you understand the schemes

like is some blackbox defensive metric saying the giannis isnt that good of a defender for who knows what reason, well when we examine the player tracking data it says he is a very good defender in all aspects of the game except on the perimeter, when we look at his perimeter defense it says hes excellent when matched up with his man but struggles when switching, what do we know about the bucks defensive scheme, we know that it encourages tons of chaotic double teams and switching which doesnt work good, from out investigation we can conclude that giannis contrary to what the fancy advanced stat says in is fact likely an excellent defender who is playing in a bad scheme and would thrive in a good one, which not coincidentally is the same conclusion one wld reach by watching him play, thank u this has been my nba stats fan fic

now u cld try to create a stat which notices when everyone on a team tends to struggle in certain areas and labels it scheme and tries to account for it but it prob wldnt work and whats the point anyway like maybe its a scheme issue or maybe its a personnel which is a differentiation which is easy for a human to understand and very difficult for a computer to and youre never going to have a 100% quant basketball team so why not let the computers do the stuff theyre good at and let the humans do the stuff they are, humans are gonna make the decisions anyway

in conclusion in the words of smart stats boys everywhere "its stauskas"

ive found recently that reading about NBA plays makes the game feel super boring to me

I get the appeal of stats, but I'd rather hear (current) players' and (opposing) coaches' thoughts about/ratings of players than someone like Zack Lowe (who I really like) talk about stats. Way more interesting and feel like I learn more.

whereas w/ the NFL it's the opposite

I geek out on scouting reports like some people do on stats

like understanding all the movements and battles away from the ball in football help contextualize the action that draws your eyes, whereas in basketball when i read about that stuff the game starts to feel orchestrated and motorized in a way i find dispiriting

agree

huh weird wldnt have thought of that i feel like it helps me see the game better and plays in basketball are so much more wide open than in football anyway, theyre just sketches really, also the best nba players consistently destroy all schemes employed against them which is a neat feature and a good argument against stats tendency to value efficiency above everything and glorify role players who like hit a lot of open threes

nfl fans appreciation of scheme is def way ahead of the nbas tho, almost entirely because of madden (the game)

i think nba schematic stuff can be interesting but it’s a little abstract and in the back of my mind i’m always thinking about how many teams even basic scheme breaks down and teams have to improv.

its scheme vs scheme but sometimes u gotta just make something happen!

its not any coincidence that the best team over the long haul the spurs is also the most dedicated to quality robust scheming

It's interesting to observe and contemplate at times, but most of the time I don't want to have to think like a coach when I'm watching which is why I agree w/Jordan for most part.

like Thibs (to take the extreme example) does not look like he ever enjoys watching NBA guys play and I don't want to be anywhere near him on that spectrum.

reading about nba at a granular level has def improved my understanding and enjoyment of the game, but i think it's mostly about the way pick and rolls playout, defensive coverages generally etc. reading about set plays and that kinda stuff doesn't appeal to me much right now, tho it can be fun to recognize plays happening in real time

otm. i like when teams run plays that you start to recognize like elevator doors when someone is hot, or the hammer play that the spurs made now everyone does. but for the most part i just like to watch without thinking about it too much. i do like watching defensive switching, though.

yeah i mean im def not in coach mode when im watching nba my awareness of plays and schemes has gone from like 1% to 7% im still mostly in it for sick hooping and big wins

knowledge of "advanced stats" and knowledge of schemes/plays are of course not diametrically opposed things, as lagoon mentions you need some sort of grasp of scheme to be able to place advanced stats into context, and to understand the limitations of individual statistics