# An Exhaustive Probabilistic Look at Every Team’s NBA schedule

Following up on my last post, I decided to leap ahead a bit and use the projected season level team point differentials and home court advantage numbers from Evan Zamir — which show that not all home court advantages are made equal — in order to predict the probabilities of a team winning each game on its schedule, based on the strength of the opponent and whether the game was home or away. The above spreadsheet is the result of all that work. The column marked “Log5 W%” represents the probability a team will win a given game, using the log5 method. The column marked “Pyth W%” is the same, only using the projected point differential-marked “Game MOV” in the spreadsheet- in order to use the Pythagorean formula to determine the probability of a win in that game.

Caveats, of course, abound. The minutes projections that I made could be wrong, skewing the projected strength of each team. The xRAPM projections from Nathan Walker and the rookie projections from Hickory High will be imperfect- they are just projections, afterall. In addition, teams may play better or worse for a stretch than their season level strength might indicate- for example, the Lakers will likely be much worse in the early part of their schedule when they are likely to be without Kobe, despite all of his tireless work to get back in time for the start of the season. Kobe is Kobe, but Kobe is also human and a torn achilles is one of the toughest injuries from which to return that exists. So take these numbers with the large dose of salt that they deserve. But, you know, have fun with them.

Sidenote: the Sixers will almost certainly not win 33 games or anywhere close to that many- I’m not sure what to do about that. The issue, I think, is that xRAPM basically measures impact on the court- but within the role that the player played- and can’t really account for changing roles. A lot of players on Philadelphia’s roster are going to be thrust into roles for which they are simply ill-equipped, whether due to inexperience or lack of talent, and therefore, I’d be shocked if you saw them perform at the level they are projected to perform by the numbers. This includes their new rookies, Nerlens Noel and Michael Carter Williams, who both project to be solid rookies, according to the Hickory High regression. Those projections are based on a regression of past performers and I think it’s pretty fair to say that the average rookie in the time frame during which the regression covered simply did not have anywhere near the level of free reign- and therefore on-court responsibility — that Noel and MCW will have this coming season.

Image from aidanmorgan via Flickr.