APBRmetrics

J.E. wrote:

Nathan wrote:One other thought I'll throw out there is the following. I remember seeing on here a few months ago a stat showing that teams performed significantly better when facing a deficit than when holding a lead. This suggests that many teams do not play at or even near their maximum potential for long stretches of most games. Could this have to do with coaching? I would expect teams with the worst coaches to have the largest discrepancies between how they perform when holding a lead vs. when facing a deficit, reflecting the fact that the team is playing far below their potential except when they're facing a deficit. I would expect teams with the best coaches to have the smallest discrepancies between how they perform when holding a lead vs. when facing a deficit, reflecting the fact that the team is playing the best basketball they're capable of, or close to it, no matter the situation (note: even if a team's effort is perfectly consistent, they will still fare better when trailing because their average opponent's effort is not perfectly constant). Does this turn out to be the case?

I think the 'effect of leading' is mostly human nature. For one, pacing yourself in these situations decreases unnecessary injury risk. I doubt that coaches have much influence over this. Maybe a new coach will be succesful at keeping motivation high when up 20 in the first ~5 games but I'm sure it will loose its effect and players will start shaking their head at a coach that screams at them to continue to bust their asses even though they're up 25. You can't go full speed all the time, you have to pick your spots, and being up 10+ is probably not such a spot (unless it's a playoff game)

Agreed. You would probably have to filter out situations where the margin is above a certain threshold, maybe 10 or 15 for the first three and a half quarters, and just forget about the last six minutes of the game because there are too many confounding factors that come into play then.

It might be useful to check whether players of a certain level (plus 2-3 or better) from .500 plus teams tend to retain that level better than players from sub .500 teams after trades. And whether the worst rated guys on teams with a plus 4 or better guy stay that bad when traded to a team without a top guy of that level.

Another line of research that could be pursued by a max effort team would be to try to review a team's play videos and chart the field of vision of every player thru the course of plays. The motion capture cameras cant help with that now (tracking pupils instead of entire bodies) but you could try to get close with manual video review. The success / failure or efficiency of plays depends in large measure on what is seen / not and when (and then recognition and execution). I think that it is improvable with study and teaching. So do coaches of course but I just think that it is fairly likely that this could be pushed further with intense comprehensive video work, what if analysis, careful consideration of angle adjustments, etc. Maybe google glasses (perhaps with modification) would be the tool to do this job, at least in practice or model building simulation.

http://allthingsd.com/20130523/analytic ... -strategy/

I missed this when it came out. Useful main point.

Ideally teams would have the right resources to vigorously pursue several productive strategies. There may be some analysts with the talent and speed / endurance to successfully advance several strategies simultaneously but there are probably teams without that ability, relying on a analyst or analysis team without the ideal breadth and depth of expertise.

There may be other ways to characterize the pool of analysts but I see PhD data scientists, 25-35 yr olds with some stat training at the b.s. and m.s. level and then others with video review experience or a law degree. I see some with big data management and / or analysis experience and those who rely on Excel and recession for relatively small data sets. I see technicians who know how to do what they are told and people with nontypical / not already widely known ideas about what to try and / or how / what to use from the results. There probably are minimum tech requirements to be a fluent, collobrative team member but not everyone has to be a database or application builder.

Sport analytics has to be directed and managed. The degree to which the lead sports analytics guy or the bb operations executive directing and managing him is qualified or well qualified to do these tasks surely varies and surely affects achievements. I am now interested in finding good articles on analytic management. Suggestions welcome. I guess I should read Alimar's book. If you have, I'd be interested in hearing your thoughts about it and the topic.

Every once in awhile I go looking for relevant or thought simulating articles. Today I happened to stumble on this one that I knew about: http://www.ingentaconnect.com/content/u ... 1/art00002

I'd like to re-read it with a focus on the age-position interaction. Jose do you still drop by and read here? I think you sent it to before but I don't currently have access to it.

Taken to its extreme, age-position findings might, along with market availability and pricing information, suggest the more optimal way to sequence team construction and age by position.

(This http://www.ingentaconnect.com/content/u ... 1/art00002 struck me as funny on the surface but I haven't read it for a rationale explanation. But it does hint at there being lots of ideas and articles out there. How many teams make a serious effort to tracking academic research outside of sloan articles by academics or the occasional twitter or friend suggested links? How much time / money is it worth devoting to this? Is this a half or full time job? Does any team specific target an academic consultant to do this as a first, second or third responsibility?)

Another idea that might be worth pursuing would be to look at players in last year of contract (rookie deal, maybe older guys as another set) on several overall performance metrics and dividing players into several minutes per game tiers and see how next season pay varies in general and for specific levels of per minute or possession productivity. I especially be interested in a comparison between player groups where the players average say 16-19 minutes per game vs. 20-23 or slightly bigger minute sets. How does the past performance, next season pay and the resulting "value ratio" compare? Where is the market bargain? who reaps it more often, prior team or next one? How much evidence is there of teams steering players into one minutes per game pile for money all considerations instead of for straightforward competitive or development reasons? In a lot of player cases I'd guess that they could be managed into either of these minute tiers without major disruption of other priorities.

I assume in the financial markets there is a healthy amount of analytics forensics done on competitors? Yes? Do any teams make substantial research effort to backward map opponent strategy and supporting analysis? Do they make concerted intelligence gathering efforts (of public record or beyond)? Has any analyst (or other bb operative of any strip) been sued for breach of confidentiality (on that job or after a move)? What is the norm?

I saw something recently that said Cuban paid the owner of hoopshype to heighten the visibility and image of the mavs in the news and / or rumors feeds to try to enhance their free agent recruitment efforts. I think he volunteered this information. I wonder how much public and private communication effort is purposively trying to shade general or specific opinions on players, agents, etc. What is too much / unfair? Who does this the most and best and worse? Any media / bloggers willing to comment in any fashion from experience? How big is the cost of going too far?

On average for league are shots skewed to left or right facing the basket and is it by much? Does it vary by backcourt / frontcourt or position? Is this commonly known by teams?

Nathan wrote:Interesting thought...I'm finding in making my draft rater that for non-one-and-done players, previous college seasons are nearly as predictive of NBA success as their most recent season, which surprised me a bit.

One other thought I'll throw out there is the following. I remember seeing on here a few months ago a stat showing that teams performed significantly better when facing a deficit than when holding a lead. This suggests that many teams do not play at or even near their maximum potential for long stretches of most games. Could this have to do with coaching? I would expect teams with the worst coaches to have the largest discrepancies between how they perform when holding a lead vs. when facing a deficit, reflecting the fact that the team is playing far below their potential except when they're facing a deficit. I would expect teams with the best coaches to have the smallest discrepancies between how they perform when holding a lead vs. when facing a deficit, reflecting the fact that the team is playing the best basketball they're capable of, or close to it, no matter the situation (note: even if a team's effort is perfectly consistent, they will still fare better when trailing because their average opponent's effort is not perfectly constant). Does this turn out to be the case?

I know Ken Pomeroy shared some college basketball data that confirmed this (I think it was in this year's ESPN the Magazine "Analytics Issue"). I've found the same phenomenon occurs in soccer as well (working on a blog post to share that result right now). Teams that are down by a goal are more likely to score then teams that are up by a goal. The fact that this occurs across sports would be consistent with J.E.'s "human nature" explanation.