FanPost

The NBA: Where Amazing ... Scheduling Happens, Part 2

This is the second of a three-part series that examines the differences between this season and past seasons, the empirical impact of the compressed NBA schedule, and finally examining which teams understand the schedule and what their adjustments have been.

In the first part, of this post, we discussed how this season looks different from past seasons. We pointed out that teams are turning it over more and are also worse on offense this season and provided possible reasons. In one of our examples, we used the Knicks’ lack of a point guard and the lack of quality PGs across the league being one of the factors. Since then, Linsanity has happened and our theory that putting a serviceable point guard into the Knicks’ lineup would greatly improve their offense was proven true.

In this post, we’ll dive more deeply into the crazy NBA schedule and show what the Nuggets’ performance has looked like with the effects of the schedule. There has been a lot of talk about the significance of stats being lessened or invalid in this shortened season. The stats are just as valid as they’ve always been as every team experiences the effects of the shortened schedule, however the stats have taken longer than past years to converge. As an extreme and simplified example, consider the following: team A plays their first 5 games on the road and all back-to-backs. Their next 5 games are at home and there are no back-to-backs. Let’s say that Team B’s schedule has been the opposite where they play their first 5 games at home with no back-to-backs and their next 5 games are on the road and all back-to-backs (for simplicity, assume the same opponents). After 5 games, you can take away a little bit about how good the teams are, however you can’t make real comparisons and draw reasonable conclusions until both teams have played 10 games with almost equal scheduling effects. That’s the effect we’re seeing this year.

Before discussing how the Nuggets have done this season, it’s worth taking a historical look at the effect of rest days on team performance. DSMok at APBR took a look at the data from the 2007, 2008, and 2009 seasons with a look at how offense, defense, and pace are affected by both lack of rest and extra rest. Particularly, he broke the data down into teams playing 4 games in 5 days, 3 games in 4 days, other forms of back-to-backs, 3 games in 4 days with a day of rest and then team performance with 1, 2, and 3 or more days of rest. His findings are shown below:

The efficiency differentials are given per 100 possessions and positive numbers on offense indicate that an offense is X points/100 possessions better (greater positive numbers on offense are good) while positive numbers on defense indicate that a team gives up that many more points/100 possessions on defense (greater positive numbers on defense are bad). In the NBA, teams average a little bit over 1 point per possession.

Keep in mind that there’s still a lot of noise due to small sample sizes, but from the data above, we can see that in a normal season, when teams play back to backs, offense suffers, but defense suffers even more. Subjectively, this makes sense, as players are less likely to close out and hustle, two hallmarks of defense, if they’re tired. In games where a team is playing 4 games in 5 nights, they’re 3.68 points / 100 possessions worse. The interesting thing is long layoffs are actually just as bad as 4 in 5’s – there has been research in the past that has indicated that teams that have long layoffs between playoff series’ tend to perform worse in the NBA and the NFL.

How does all this apply to this season? Well, one way to mentally model this season is to treat the whole season as a 4 in 5 or 3 in 4 since there are many more back-to-backs, 3 in 4’s, 4-in-5’s as well as back-to-back-to-backs. Thus, we would expect the average league pace to be down by about .3 possessions. Teams are playing at a 93.8 possession per game pace this year whereas they played at 95.1 possessions and 94.5 possessions in the 2009 and 2010 seasons, respectively. Pace is down almost a full possession from the previous 2 years and you’d expect absolute scoring (point totals) to also be down. If you had bet the under in every game this season you’d have made a profit since even Vegas also hasn’t quite understood the effects of the schedule.

You’d also expect to see a slight increase in efficiency numbers across the board since offense would be worse per 100 possessions but defenses would seemingly be worse by a greater margin. Recall, however, in our previous post we saw that this season it’s offense that is worse, which is the opposite of what we’d normally see when teams are playing a lot of games with little rest. When all teams are subject to the same scheduling conditions, what you have is a decrease in absolute efficiency. If you looked at the 3 in 4 and 4 in 5 data, you know that teams should be about 2.19 to 3.68 points/100 possessions worse across the board with drop in defense accounting for the majority of it. Average offensive efficiency this year is 100.3 points per 100 possessions whereas it was 104.5 in 2010, 104.9 in 2009, and 105.4 in 2008. It seems like the downward trend in efficiency is continuing with the added factor that almost all the effects of the schedule are being manifested on the offensive side of the ball.

How Have the Nuggets Done?

We’ve provided the data below for how the Nuggets have done this year in various rest or lack of rest situations (all rest games are treated the same since there are very few games with 2 or more days of rest). The charts below show each game the Nuggets have played, their offensive and defensive efficiencies (ORtg and DRtg) and the differential between their actual performance and season averages. The sample sizes are pretty small so it’s tough to draw meaningful conclusions from the data, especially since there are many more variables at play such as home court advantage and opponent’s rest situation. The one very obvious conclusion we can draw is how affected a team can be by scheduling artifacts – with the Nuggets being obviously worse than their season averages in games that are B2B, 3 in 4, and 4 in 5 while being better than their season averages in games with 1 or more day of rest. Apologize ahead of time for how hard the charts are to read - we still haven't figured out how to properly build charts using SBNation's blogging software so we end up pasting images in.

We’ll emphasize it again as it’s so important when evaluating teams this year. An individual game against a specific opponent tells us very little about how good or bad the Nuggets are. There will be games where we get blown out against horrible teams and games where we destroy the elite teams – and they both tell us almost nothing. With the exception of the Miami Heat, every single team in the league will be affected and have stretches of seemingly terrible play. The only way to draw accurate conclusions about games is to distill out the relevant variables for both teams, which is far beyond the scope of this post. Be encouraged that the Nuggets, playing without Nene, who makes a huge difference, and Gallo were able to hang at Oklahoma City against a very good Thunder team where both teams had one day of rest, without other scheduling variables.

Further, a lot of you will disagree with this, and we’ll delve more into it in the third part of this series, but teams need to manage the schedule. If a team’s goal is to win the maximum number of regular season games to secure the highest playoff seed, it actually behooves them to smartly pick and choose games to take nights off. For example, if your team is on a 3 in 4 against a quality opponent and the next night is a 4 in 5, it is actually better to rest your starters, lose the game and give your team the best chance to win the next game. A team needs to give themselves the best chance to win the games that they should win, to not lose games that are relative coin flips, given the schedule, and to beat the good teams who are on the wrong side of the rest situation while choosing games with a low win probability to rest key players. This is an unpopular viewpoint as people pay good money to see their team and to watch the superstars. Matt and I look at things from a longer term perspective, however. While we enjoy the regular season games and would like to see our team win, we’re focused on giving ourselves the best chance to win in the playoffs and that means good health and home court advantage. The timing of our injuries has actually been very good and giving our young guys minutes now will play dividends down the road.

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