The Importance of Being Open

The paper is not yet available that I can tell but the Hot Hand debunker is back with something new, and also with Synergy the beginning of the end of any anti-stats arguments for the rest of history.

One of the better summaries so far you can find here: http://queencityhoops.com/blog/2011/03/ ... eing-open/

I'll quote some selected things:

This great new data is from Stats, LLC, as they have added multiple cameras (hence the optical in the title) to 3 NBA courts, with the sole intention of recording everything that occurs on the court. Players are tracked, with an exact location in x,y coordinates, as are referees and the ball. 25 times a second, software analyzes the video, and stores information about where everyone is and what is occurring. 1,000,000 entries per game with 60 some games added to their databases so far. Basic things like field goal attempts, blocks, rebounds, and assists are part of what is tracked. And that’s where it starts getting really cool – player position and defender proximity to a player are now available without having to chart and track a game by hand and eyeball estimates.

For his hot hand research, Sandy relied on play by play data to generate possession and play data on a granular level – but with the limitations inherent to play by plays. Passes aren’t tracked, unless they end in an assist; who had the ball in their hands during the possession is unavailable; where was the defender when a shot was taken is an unknown. But not anymore.

The focus of Weill’s research this time was on distance – from the rim and from defenders – and the impact on field goal percentage. Stats, LLC’s new tool provides exactly that, as Sandy was able to look at over 6,000 field goal attempts with the knowledge of where the shot was taken and the distance from defenders. Yes, plural defenders, as the range from all defenders is available, giving the ability to recognize double teams and an oncoming defender.

The three primary results of Weill’s poring through the data and accounting for things like historical player shooting percentages, distance, and shot type:
-Tight defense (within three feet) drops expected shooting 12% points (ie – a 50% shot becomes a 38% shot)
-FG% drops 1% point for every 1.5 feet from the rim
-There is something beneficial about the catch and shoot, beyond expectations

Hopefully we'll see the paper soon. The leaps in analysis over the last few years have been pretty awesome. Probably the only soft-science academic field that's been interesting in anyway. (To be fair, sports analysis is probably parsecs more science than what I do every day can even resemble science.)

Wow, So eventually we will have stats that can clearly show who is soft and can't handle contact. Like the first things that came to my mind was proving that LeBron and Wade is better at attacking inside than RuPaul. And say with absolute certainty which shooters are really the best pure shooters. I hope they could also show the reverse, and analyze the data on which defenders are quick to react, like when Rick Carlisle (I think?) was campaigning for Artest for DPOY b sending out stats to voters of opposing players stats "when guarded by Artest".

Those Artest stats were horrific.

But yes, parsing videos will leave us with more data than we can probably contend with. And will completely vaporize the standard pundit from orbit. Parsing PBP has already destroyed notions like the one that Kobe is clutch, parsing video is going to be a true revolution.

Don't worry though, baseball was deconstructed statistically decades ago yet somehow people continued to be employed thinking the sport could not be described empirically.

The major flaw to this, is that as more people learn it, the less advantage it offers. See the A's -> Red Sox.

Crazy idea. Liking the idea that it could tell... which players are good at shaking off a defender or which players are good at shooting over people. Or which defenders are abusive and whatnot.

But more importantly, this also tells us which team gives opposing teams the least space, meaning a good team D. And leads to a lot of other stats... exciting to hear about this. Hope this becomes available in all games as standard measurement.