The "ghost" players in these animated replays that show where the system thinks a player should have been are fascinating to see. I wonder how automatic it is - if games could be analyzed like that without much expert input, this would be a really cool thing to have for recreational teams who want to get better but can't afford expert coaching. I'm thinking my late-night adult league hockey team would probably benefit from some replays like this.
I'd be pretty curious about that too. I actually tried doing something semi-similar before. My goal was to simulate a basketball game by having every player take an action based on "expected points per possession". So if you are covered tightly but a shooter is open, your expected points would be high for passing but low for shooting. This would then be done recursively for every decision, continuously looking ahead until the shot clock expires (so maybe the best move would be to pass it into the post, draw a double team, and then kick it out for an open shot).
The obvious problem was that there are a ton of free parameters involved and tons of branching. Every little action creates a new branch of possibilities with its own set of probability distributions. So even if (as they describe in the article) helping out more often decreases the likelihood of the current ball handler making a shot, how does that propagate through the rest of the possession?
It sounds like there probably wouldn't be enough data to generate the ghost players. According to the article they depend on the skills of the individual covers. (i.e. Player X is a 35% three point shooter so don't leave him in the corner to help on a cut)
The 82-game NBA schedule really helps to generate large enough sample sizes about players.
I could see it being potentially possible to just use average data, but if your rec league is anything like mine, talent ranges from a guy can credibly fake a three and then dunk after one dribble to guys that can barely get up and down the court.
Unfortunately the cameras are pricey enough that only 15 of 30 NBA teams have purchased them, not to mention the half decade of work it took the Raptors to build the code to actually generate the visualizations. Maybe someday it will be commercially available and affordable, but that day seems a long way off to me.
I'm wondering why the 15 other teams aren't on board yet. If the price is only 100k, it's nothing to an NBA team. If those other 15 teams don't already have an advanced analytics team in place, then it makes sense not to have the camera until you have a structure in place to make sure of the camera data.
It will be interesting with this huge push in basketball over the past couple years to see where this type of analysis leads. The NBA model right now is pretty simple: get two or three superstars, align them with solid role players, and play in championships. It's hard to imagine analytics pushing a team like Houston to be able to beat a team like Miami or Oklahoma City in a seven-game series because the talent gap is so substantial. Houston can play a smarter game but the other teams still function better. What I could see happening, however, if a team like Oklahoma City, while slightly less talented than Miami, can implement insights from this analysis to raise their EV, it might overcome the slightly smaller talent gap. Even in that small sense, it makes more to spend a couple million a year on analytics than it does to pay an average NBA player several million. Since the NBA has both a salary cap and maximum contracts, it pushes the price of an average play up quite a bit, so better value may be had by raising the effectiveness of your current talent than trying to bring in new players.
I completely agree, but, as referenced in the article, there is still pretty strong resistance to analytics-driven decision making in the NBA. Many NBA coaches and GM's are former players, who generally resist advanced stats. Hence "it can't measure personality, chemistry, heart." That quote fails to mention neither can anything else, so it makes much more sense to focus on what can be measured than on what can't (I'll concede personality should in some cases be taken into account if there are clear clashes).
Forget the advanced stats, it also elucidates the best defensive/offensive scheme for the team. That's part of a coach's job description right there. It's probably also not much of a stretch to encroach on the scouts' & GM's territory too - How will our team look if we trade Lopez for Howard? - for example.
When the system gets more optimized and easier to use, the role of a coach & GM could get diminished, and with it, their salaries. Of course they would do everything in their power to stop that.
Except for the coaches who embrace it. When the Mavericks hired Rick Carlisle, a big reason they hired him was that in Indiana he had consistently used his teams best lineups, and in his interviews expressed a strong interest in embracing analytics (which, with Mark Cuban as your owner, you won't ever lack the resources to get the best analytics). In baseball, the best (in terms of wins/resources) team is the Rays, who hired investment bankers as their GM and have a coach who listens to the sabermatricians, platooning like crazy and shifting the infield all over.
>I'm wondering why the 15 other teams aren't on board yet. If the price is only 100k, it's nothing to an NBA team. If those other 15 teams don't already have an advanced analytics team in place, then it makes sense not to have the camera until you have a structure in place to make sure of the camera data.
As someone who is on the periphery of working in a professional sport in both analytics and player development, the simple answer is the fact that market forces are comparatively weak here. You have monopolies with a ton of inertia in doing things the same way, plus a lot of the decision-makers are luddites in nature who think the human element is the single most important factor.
Times are changing as the economics of sports tightens and becomes more efficient, but it's not like there are ways to disrupt the market openly. The Dallas Mavericks (Cuban) and the Houston Rockets (Morey) are the ones leading the charge in the NBA, just like the Oakland Athletics (Beane), Cleveland Indians (Shapiro), and Tampa Bay Rays (Friedman) led the charge in MLB.
I don't think it's the cost that's keeping other NBA Teams from purchasing ($100K/year is pennies to an NBA franchise). I suspect its more of a front-office vs coaching thing. Adopting this as part of a teams core prep takes education; Effectively learning how to understand this type of data and apply it in practice over the course of a season.
It should be pennies to an NBA franchise (when they are spending millions on players who don't play). Unfortunately, owners like Robert Sarver and Donald Sterling are notorious for refusing to spend on marginal upgrades like a quality visitors locker room, or a a full support staff. Even Paul Allen has a reputation for refusing to pay for a high quality training staff in Portland - probably a bit undeserved since he seems to spend on other important things and I can't imagine why training staff would be something he ignores. Also, there is a floor for player salaries that must be met.
The analytics vs. coaching issue is a real one too, but don't discount owners being cheap.
I can imagine facilities like hockey rinks buying the cameras and selling the service to the teams that play there, but not at that price. My impression of hockey rinks is that they're not terribly profitable. Most of the ones I've played in seem like borderline charities.
While I agree 100K is alot, it's nothing compared to salary and cap space. To be able to spend money outside of cap restictions to imporove your team is a stragetic advantage.
I don't think the price will come down, the only people who need it are wealthy and the wealthy can't afford to not have it.
