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DSMok1
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PostPosted: Wed Nov 10, 2010 6:20 pm Post subject: Effect of Rest Days on Efficiencies Reply with quote
Rest Day Analysis
NBA Stuffer has done some good work on rest days, but I thought I'd attack it more rigorously.
I compiled all regular season games in the last 3 years, each team's efficiencies and the pace of the game. I also generated their rest situation, using the same set of cases that NBA Stuffer did:
4th in 5 days
3rd in 4 days, B2B
Back-to-back (other)
3rd in 4 days, 1 day rest
1 Day Rest (other)
2 Days Rest
3+ Days Rest
To estimate these values, I ran a regression on each year's data, solving for each team's offensive and defensive ratings, the effect of home court advantage, and the effect of the rest days. I then averaged the 3 year's results, based on the number of observations of each type.
Here are the results:
Code:
Off Rtg Def Rtg Eff Diff Pace Observations
4th in 5 days -0.63 1.34 -1.97 -0.42 230
3rd in 4 days, B2B -0.30 1.37 -1.67 -0.32 942
Back-to-back (other) -0.31 1.13 -1.44 -0.11 608
3rd in 4 days, 1 day rest 0.07 -0.03 0.10 0.10 1126
1 Day Rest (other) 0.14 -0.51 0.64 -0.06 2778
2 Days Rest 0.64 -0.22 0.85 0.21 1164
3+ Days Rest -1.11 -1.14 0.03 0.50 532
And here's a pretty chart:
The home court efficiency advantage generated was 4.68. I generated the estimates for each game using the form Team1*Team2/LgAvg for each portion of the estimate (offense, defense, pace).
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inkt2002
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PostPosted: Wed Nov 10, 2010 10:37 pm Post subject: Reply with quote
Solid analysis as always. Very interesting. Amazing that the biggest drop-off in efficiency would be offensively when resting 2 days vs. 3+ days.
Thanks for sharing.
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Serhat Ugur (hoopseng)
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PostPosted: Thu Nov 11, 2010 1:53 am Post subject: Reply with quote
@DSMok1, thanks for the analysis. Maybe we should increase observations and extend this study by going back to -let's say- 10 years.
From my archive, here's another study on rest days.
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DSMok1
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PostPosted: Thu Nov 11, 2010 9:23 am Post subject: Reply with quote
Serhat Ugur (hoopseng) wrote:
@DSMok1, thanks for the analysis. Maybe we should increase observations and extend this study by going back to -let's say- 10 years.
From my archive, here's another study on rest days.
I had not realized that the home team typically has more rest than the road team! That's interesting...
I have the framework in place to do this for as far back as we want to look, though it takes time to set up the data.
I think that one of the primary reasons for the bad offensive numbers on the 3+ days of rest is that every team has that on the first day of the year, and I think defenses typically dominate the first day.
Perhaps I should add a factor that looks at what point in the season the game occurs? Perhaps offenses progress after, say, the first month, because it takes more practice working together at game speed to get the offense rolling.
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greyberger
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PostPosted: Thu Nov 11, 2010 2:38 pm Post subject: Reply with quote
If it's not a huge headache you could try breaking it down further into "3 or more days rest, inside the season" and "Returning from break", or just chopping off the starting day games (and post all-star break games, if needed).
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DSMok1
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PostPosted: Thu Nov 11, 2010 6:55 pm Post subject: Reply with quote
greyberger wrote:
If it's not a huge headache you could try breaking it down further into "3 or more days rest, inside the season" and "Returning from break", or just chopping off the starting day games (and post all-star break games, if needed).
I think I'll graph the whole season and see if there seems to be particular trends visually. Your approach may be what is required...
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Marver
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PostPosted: Sat Nov 13, 2010 5:00 pm Post subject: Reply with quote
I'm not so sure this is an effect of the actual players performing worse than normal, or if this is largely a function of playing time. Surely some, if not all, coaches temper the playing time they give to their star players when playing multiple games in a short time-span. Granted, this wouldn't explain the differences observed for games played with excess rest, but it certainly could play a large mitigating factor for the other scenarios. Perhaps you could use player efficiency, rather than team efficiency, as the main metric.
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Italian Stallion
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PostPosted: Tue Nov 16, 2010 10:52 pm Post subject: Reply with quote
Is there any way to convert that into a Points Per Game impact?
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DSMok1
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PostPosted: Thu Nov 18, 2010 10:10 am Post subject: Reply with quote
Italian Stallion wrote:
Is there any way to convert that into a Points Per Game impact?
It depends on the pace of the game (usually around 92 poss/game, check Basketball Reference for each team). The numbers are points/100 possessions, so it's an easy conversion.
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bstenger
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PostPosted: Sun Nov 21, 2010 11:11 pm Post subject: Reply with quote
There's recent research from Europe that looks at the how Champions League soccer players' injury rates and athletic performance depending on whether they play one game in a week, or two. The researcher, Gregory Dupont from University of Lille, found that injury rates increased substantially (6X more likely) but athletic performance (based on player-tracking data analysis) did not drop off. ... the paper from the American Journal of Sports Medicine, http://ajs.sagepub.com/content/early/20 ... 6.abstract
I discuss the research in an article on NBA schedules at http://news.medill.northwestern.edu/chi ... ?id=171975
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DSMok1
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PostPosted: Tue Nov 23, 2010 10:06 am Post subject: Reply with quote
DSMok1 wrote:
greyberger wrote:
If it's not a huge headache you could try breaking it down further into "3 or more days rest, inside the season" and "Returning from break", or just chopping off the starting day games (and post all-star break games, if needed).
I think I'll graph the whole season and see if there seems to be particular trends visually. Your approach may be what is required...
Here's that graph:
There are several distinct things to note here:
1) The playoffs are a lot slower paced
2) The pace is higher at the very beginning of the season and right after the all-star break, but is pretty consistent otherwise
3) The overall efficiency seems to increase quite a bit in the first week, then increase at a steady pace throughout the season (apparently, offense takes more practice than defense?)
I will endeavor to tease out these effects. I will change my regressions in the following ways:
1) Add another category: 3-4 days rest and 5+ days rest. The latter only occurs at the start of the season and at the all-star break.
2) Add a modifier for the first week of the season that simply adds a constant to pace and efficiencies
3) Add a linearly increasing term for the efficiencies over the course of the regular season.
4) Add a constant and a second linear term for the duration of the playoffs, for both efficiencies and pace
Once running this more intricate regression, I should be able to separate out all of the effects.
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mtamada
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PostPosted: Tue Nov 23, 2010 4:43 pm Post subject: Reply with quote
Is "RTG" the offensive rating, or defensive rating, or both combined? Or the offensive rating for both teams in a given game?
There is a big increase in the range and variance of RTG around Day 200; I'm presuming that's when the playoffs start; if the ratings are for teams rather than for games, then that variance might reflect #1 seeds stomping all over #8 seeds, resulting in sky-high ratings for the winners and low ratings for the losers. But I'm not sure what the RTG figures represent.
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DSMok1
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PostPosted: Tue Nov 23, 2010 6:32 pm Post subject: Reply with quote
mtamada wrote:
Is "RTG" the offensive rating, or defensive rating, or both combined? Or the offensive rating for both teams in a given game?
There is a big increase in the range and variance of RTG around Day 200; I'm presuming that's when the playoffs start; if the ratings are for teams rather than for games, then that variance might reflect #1 seeds stomping all over #8 seeds, resulting in sky-high ratings for the winners and low ratings for the losers. But I'm not sure what the RTG figures represent.
Ratings are the average for the game. The playoffs start at day 170; there is a lot of variance because of fewer games/day over the 3 year sample (under 10 at that point).
In my initial regression it doesn't appear that there are any significant differences in the 1st week in the season for pace that are unexpected (other than the fact that after a long rest teams play faster). As I have the opportunity I'll keep everyone posted.
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Italian Stallion
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PostPosted: Mon Dec 06, 2010 6:20 pm Post subject: Reply with quote
What about if a team plays back to back at home both games vs. back to back where traveling is involved?
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DSMok1
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PostPosted: Mon Dec 06, 2010 8:13 pm Post subject: Reply with quote
Hmmm. It seems I forgot to update with the results of my proposed changes above.
Here are the results:
There are some changes in the results from the original regressions. I minimized absolute error in this regression, rather than squared error (I'm not sure what effect that has).
EDIT: I forgot to mention a few things. The corrected home court advantage is now 3.24.
Here is the table of actual numbers:
Code:
Case ORtg DRtg Differntial Pace Observations
4 in 5 -0.44 3.24 -3.68 -0.27 230
3 in 4, BTB -0.54 1.64 -2.19 -0.37 942
B2B -0.11 1.37 -1.48 0.20 608
3 in 4 -0.30 0.71 -1.01 0.10 1126
1 Day Rest 0.31 -1.63 1.94 -0.17 2778
2 Days Rest 0.71 0.31 0.40 0.31 1164
3-4 Days Rest -0.23 -0.04 -0.19 0.30 353
5+ Days Rest -3.25 1.48 -4.73 0.96 179
Also, I found a best-fit "scaler" that ends up reducing the projected efficiency differential if it's above average and increasing the projected efficiency differential if it is below average. Basically, this scales to adjust for the fact that good teams will take it easy against the worst teams. That "scaler" is 93.6%, and the league-average game differential is 6.394. So, if a game has a projected differential of 15 (rare) then the adjusted projected differential would be 6.394+(.936*(15-6.394))=14.44. It's just a slight tweak, but I thought it interesting. /EDIT
As a byproduct of these, here are the ratings of all of the teams in the last 3 years. These include the playoffs:
Code:
2009-2010 Off Def Margin
ORL 3.29 -3.73 7.03
PHO 8.14 1.22 6.91
CLE 4.54 -2.05 6.59
UTA 4.00 -2.43 6.42
LAL 2.44 -3.81 6.24
ATL 5.43 0.48 4.96
BOS 0.37 -4.04 4.41
SAS 1.69 -2.60 4.29
DEN 3.35 0.14 3.21
POR 2.61 0.37 2.24
DAL 0.80 -1.36 2.16
OKC -1.16 -3.19 2.02
MIL -4.32 -5.97 1.66
MIA -0.40 -1.63 1.23
CHA -2.25 -3.23 0.98
HOU -0.07 -0.90 0.84
CHI -4.08 -3.77 -0.32
TOR 4.04 5.22 -1.18
SAC -1.66 0.67 -2.33
MEM -0.18 2.71 -2.89
NOH -0.36 2.61 -2.97
NYK 0.57 3.78 -3.21
GSW 0.69 3.91 -3.21
WAS -1.90 1.32 -3.22
IND -3.81 0.28 -4.09
PHI -2.33 1.81 -4.14
LAC -4.52 1.62 -6.14
DET -1.42 4.98 -6.40
MIN -7.04 2.92 -9.97
NJN -6.47 4.67 -11.14
2008-2009 Off Def Margin
CLE 5.52 -5.17 10.69
LAL 3.83 -5.14 8.96
BOS 2.40 -5.38 7.78
ORL -0.01 -6.98 6.97
HOU 0.92 -5.74 6.65
DEN 3.64 -0.97 4.62
POR 4.76 0.89 3.87
DAL 2.78 -0.44 3.21
UTA 0.83 -1.78 2.61
ATL 0.57 -0.67 1.24
CHI 1.17 -0.05 1.22
SAS -3.18 -4.37 1.19
NYK 1.44 0.42 1.03
NOH 0.14 -0.78 0.92
PHI -0.87 -0.72 -0.15
PHO 3.89 4.17 -0.28
IND -0.66 0.16 -0.82
CHA -2.60 -1.41 -1.19
MIA -1.41 0.30 -1.71
DET -1.89 -0.02 -1.87
MIL -1.07 0.94 -2.00
NJN 0.19 3.60 -3.41
GSW 1.50 5.15 -3.66
TOR 0.37 4.34 -3.96
MIN -2.16 3.14 -5.29
MEM -4.90 1.14 -6.04
OKC -5.35 1.56 -6.91
SAC -1.49 5.69 -7.17
LAC -5.65 2.27 -7.92
WAS -2.71 5.84 -8.55
2007-2008 Off Def Margin
BOS 3.45 -7.47 10.92
LAL 7.21 -3.18 10.38
NOH 6.88 -0.27 7.15
UTA 7.16 0.27 6.89
HOU -1.45 -7.58 6.13
DET 2.27 -3.51 5.78
SAS -0.20 -5.70 5.50
ORL 4.02 -0.78 4.80
PHO 6.86 2.26 4.59
DAL 4.50 0.20 4.30
DEN 1.37 -2.01 3.37
GSW 4.51 1.55 2.96
TOR 3.80 0.92 2.88
CLE -1.51 -4.15 2.64
WAS 2.10 0.62 1.48
POR 1.63 1.21 0.42
IND -0.88 -0.77 -0.11
PHI -1.83 0.46 -2.29
SAC -1.21 1.99 -3.21
CHI -4.01 -0.60 -3.41
CHA -2.81 1.49 -4.30
ATL -1.62 3.32 -4.94
NJN -4.08 1.25 -5.33
MIL -2.21 4.35 -6.55
MEM -2.50 4.13 -6.62
MIN -4.38 3.71 -8.09
LAC -6.38 1.85 -8.23
NYK -3.44 5.11 -8.55
SEA -8.88 0.13 -9.01
MIA -8.37 1.18 -9.55
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Italian Stallion
Joined: 04 Mar 2009
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PostPosted: Tue Dec 07, 2010 12:56 am Post subject: Reply with quote
Fabulous stuff.
In my examination of point spreads I would repeatedly see spreads that were lower than the efficiency differential when one of the best teams was playing one of the worst.
I assumed that was related to the best teams pulling star players early.
The thing that's kind of puzzling to me is that you could kind of assume that the best teams also have better benches and that even if the starters are pulled early the good teams would either maintain or extend the lead. After all, bench players are trying to earn minutes too. But my observation (no data) tells me that's the not the case. It appears that the team that is way ahead eases up.
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Italian Stallion
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PostPosted: Tue Dec 07, 2010 1:01 am Post subject: Reply with quote
DSMok1 wrote:
Hmmm. It seems I forgot to update with the results of my proposed changes above.
Here are the results:
There are some changes in the results from the original regressions. I minimized absolute error in this regression, rather than squared error (I'm not sure what effect that has).
EDIT: I forgot to mention a few things. The corrected home court advantage is now 3.24.
Also, I found a best-fit "scaler" that ends up reducing the projected efficiency differential if it's above average and increasing the projected efficiency differential if it is below average. Basically, this scales to adjust for the fact that good teams will take it easy against the worst teams. That "scaler" is 93.6%, and the league-average game differential is 6.394. So, if a game has a projected differential of 15 (rare) then the adjusted projected differential would be 6.394+(.936*(15-6.394))=14.44. It's just a slight tweak, but I thought it interesting. /EDIT
As a byproduct of these, here are the ratings of all of the teams in the last 3 years. These include the playoffs:
I wonder why 2 days rest isn't as much of an advantage in this output as in the previous?
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DSMok1
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PostPosted: Tue Dec 07, 2010 8:59 am Post subject: Reply with quote
Italian Stallion wrote:
I wonder why 2 days rest isn't as much of an advantage in this output as in the previous?
Probably because I did my regression better! Very Happy
I find it satisfying that there seems to be very distinct trends in terms of rest: offensive rating is fairly consistent, though more rest is better up to 2 days. Defense is far more effected by rest--and that makes sense.
Reminder: 5+ days only happens twice each season for each team: their first game of the year and the first game after the all-star break.
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greyberger
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PostPosted: Tue Dec 07, 2010 5:56 pm Post subject: Reply with quote
Quote:
It appears that the team that is way ahead eases up.
I'm inclined to attribute this to strategy and call it a day. When you can see the finish line and you almost have enough of an advantage to dribble it out, points above a comfortable lead become a kind of a resource. There's waiting until the shot clock is almost out to make an attempt, of course, but also more subtle trading going on. Teams will gladly give back points for a chance to get certain players reps, to avoid risk of injury, or just to get the game over faster.
Well, maybe not the Celtics.
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back2newbelf
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PostPosted: Thu Dec 09, 2010 5:54 am Post subject: Reply with quote
I think it's also important to know which coaches play certain players less minutes because they know it's a back to back, 4th game in 5 days or something similar.
Some players will certainly suffer in certain ratings when coaches don't do that, others will look better as they should if the coach keeps them from playing the amount of minutes they "should" be playing if it were a non-back-to-back.
Shaq in Phoenix was held out of almost every back to back, I believe. His teammates' (reg.) adjusted +/- rating probably suffered in the back to back games Phoenix had, but Shaqs' never did. This is problematic because not only does Shaqs' rating come out too high, but because his rating is now so high the rating of his teammates will be reduced
One step would be to check if team efficiency suffers the same amount in back to backs even if every player played <x minutes the day before.
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DSMok1
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PostPosted: Fri Dec 10, 2010 11:05 am Post subject: Reply with quote
I realized I had failed to post the table of actual numbers in my summary post.
Code:
Case ORtg DRtg Differential Pace Observations
4 in 5 -0.44 3.24 -3.68 -0.27 230
3 in 4, BTB -0.54 1.64 -2.19 -0.37 942
B2B -0.11 1.37 -1.48 0.20 608
3 in 4 -0.30 0.71 -1.01 0.10 1126
1 Day Rest 0.31 -1.63 1.94 -0.17 2778
2 Days Rest 0.71 0.31 0.40 0.31 1164
3-4 Days Rest -0.23 -0.04 -0.19 0.30 353
5+ Days Rest -3.25 1.48 -4.73 0.96 179
These are from the last 3 years of data.
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Italian Stallion
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PostPosted: Sun Dec 26, 2010 12:36 pm Post subject: Reply with quote
I want to ask one last question on this.
I assume you adjusted out the effect of home court.
It's hard to tell how much of home court advantage is related to actually playing at home on a familiar court with positive fans etc... vs. the fact that road teams tend to play more back to backs and that's partly why home court is an advantage.
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DSMok1
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PostPosted: Sun Dec 26, 2010 5:27 pm Post subject: Reply with quote
Italian Stallion wrote:
I want to ask one last question on this.
I assume you adjusted out the effect of home court.
It's hard to tell how much of home court advantage is related to actually playing at home on a familiar court with positive fans etc... vs. the fact that road teams tend to play more back to backs and that's partly why home court is an advantage.
Home court advantage came out the same after adjusting for rest days: here, 3.24 pts/100 possessions, right in line with other studies.
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Mike G
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PostPosted: Mon Dec 27, 2010 4:22 am Post subject: Reply with quote
DSMok1 wrote:
Home court advantage came out the same after adjusting for rest days: here, 3.24 pts/100 possessions, right in line with other studies.
Sort of a tangential question, but in general regarding HCA --
If Boston and Miami are a pair of evenly matched teams, then in Boston the Celts are favored by 3.24 pts, right?
In Miami, the Heat are favored by 3.24 .
So the difference between Bos and Mia venues is 6.48 points?
In a playoff series, home court swings the expected differential by 6.5 points; so why not call that the value of HCA?
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DSMok1
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PostPosted: Mon Dec 27, 2010 7:13 am Post subject: Reply with quote
Mike G wrote:
DSMok1 wrote:
Home court advantage came out the same after adjusting for rest days: here, 3.24 pts/100 possessions, right in line with other studies.
Sort of a tangential question, but in general regarding HCA --
If Boston and Miami are a pair of evenly matched teams, then in Boston the Celts are favored by 3.24 pts, right?
In Miami, the Heat are favored by 3.24 .
So the difference between Bos and Mia venues is 6.48 points?
In a playoff series, home court swings the expected differential by 6.5 points; so why not call that the value of HCA?
That's just the way most people describe it--the ratings are discussing neutral court performance, you just add on the HCA to that.
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Italian Stallion
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PostPosted: Fri Jan 14, 2011 11:00 pm Post subject: Reply with quote
I have a new one for someone with the ambition, data, knowledge, and curiosity to study.
The Knicks just played a horrific game against the Kings. It was their worst performance of the season. They had no energy at all. D'Antoni kept saying it was the fact that they were coming back east off a road trip on the west coast and even though they had a day off he knew there was a good chance they would be dull. In fact, he supposedly warned the team about it before the game.
He said any time a team makes that west to east trip it takes something out of the team...plus it was a 3 out of 4 nights game.
Anyone want to study the impact of the west coast east coast trip.
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BobboFitos
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PostPosted: Sat Jan 15, 2011 1:42 am Post subject: Reply with quote
Italian Stallion wrote:
I have a new one for someone with the ambition, data, knowledge, and curiosity to study.
The Knicks just played a horrific game against the Kings. It was their worst performance of the season. They had no energy at all. D'Antoni kept saying it was the fact that they were coming back east off a road trip on the west coast and even though they had a day off he knew there was a good chance they would be dull. In fact, he supposedly warned the team about it before the game.
He said any time a team makes that west to east trip it takes something out of the team...plus it was a 3 out of 4 nights game.
Anyone want to study the impact of the west coast east coast trip.
I *think* someone did a study about miles traveled being a better determinant of fatigue then actual days of rest - something like the Heat and Blazers were 2 of the most #miles traveled whereas the Pistons or some centralized teams were affected the least. I'm not sure where I saw that, but it seems to make sense.
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Mike G
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PostPosted: Sat Jan 15, 2011 8:09 am Post subject: Reply with quote
If miles are an issue, wouldn't centrally located teams in general have a lesser home/away disparity?
The Heat and the Blazers would travel more miles than the Bulls or the Grizz, and so would their opponents (going to Miami or Portland).
A few times a year, a coastal team may lose it's HCA by having just flown cross-country.
The Knicks actually had a rest day after losing in Utah.
The Kings, meanwhile, had just been trolling down the East Coast : Tor, rest, Was, Bos, rest, NYK.
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BobboFitos
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PostPosted: Sat Jan 15, 2011 12:48 pm Post subject: Reply with quote
Mike G wrote:
If miles are an issue, wouldn't centrally located teams in general have a lesser home/away disparity?
The Heat and the Blazers would travel more miles than the Bulls or the Grizz, and so would their opponents (going to Miami or Portland).
A few times a year, a coastal team may lose it's HCA by having just flown cross-country.
The Knicks actually had a rest day after losing in Utah.
The Kings, meanwhile, had just been trolling down the East Coast : Tor, rest, Was, Bos, rest, NYK.
I wish I could find the specific study.
Funny enough trying to back locate it I found http://sabermetricresearch.blogspot.com ... teams.html
Mike - do centralized teams have a lesser home/away disparity? I know Utah and Denver always lead the pack here in terms of H/A splits, but I'm not really sure about the other 28 teams. Portland, for example, always have the vaunted home court advantage, but it could just be that they're tucked away in the deep northwest.
Also, I think the schedule makers somewhat randomize it (by accident?) so that the teams w/ most #miles traveled varies. In theory it would ALWAYS be Orlando/Miami and Portland, at the far corners, but I'm not sure if that's how it works according to the real schedule.
As far as the particular Sac/Nyk game, D'Antoni was probably trying to come up for an excuse in terms of his team's offensive futility. There could be some legit excuse behind his teams poor play, or maybe they just played terribly.
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gabefarkas
Joined: 31 Dec 2004
Posts: 1296
Location: Durham, NC
PostPosted: Sat Jan 15, 2011 10:36 pm Post subject: Reply with quote
Mike G wrote:
If miles are an issue, wouldn't centrally located teams in general have a lesser home/away disparity?
The Heat and the Blazers would travel more miles than the Bulls or the Grizz, and so would their opponents (going to Miami or Portland).
I've always thought traveling through time zones had something to do with it too.
For instance, Miami to Boston is about 1260 miles in a straight line distance. As a comparison, Cleveland to Denver is about 1225 miles.
Would anyone argue that CLE to DEN, crossing 2 time zones, is a less arduous road trip than MIA to BOS, because it's a few less miles to travel?