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ziller
Joined: 30 Jun 2005
Posts: 126
Location: Sac Metro
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 Posted: Wed Jul 13, 2005 2:51 pm Post subject: Off-days, Home/Road Splits and Rick Adelman |
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As I written before, I'm very cautious with any sort of actual research activity related to basketball because I'm not too sure of myself yet. But I did do a rudimentary look at Sacramento's performance last year in the second game of back-to-backs and in games following a day with no game (which I refer to below as zero-rest games, even though practice or travelling is likely to occur on those "offdays").
Using Basketball-Reference.com and my gorgeous orange calculator, I looked at the Kings 2005 seasons based on days between games and home-road splits in anticipation of the upcoming release of the 2006 schedule.
Looking at the raw data, it appears the Kings got jobbed. They had 17 games with 0 days rest -- the back-end of back-to-backs. Thirteen of those were on the road and four were at home. Highly suspicious.
The Kings went 2-2 in those home games with 0 days rest, for a 50.0 winning percentage. The roadies with 0 days rest with a different story, with the team going 5-8 for a 38.5 winning percentage.
Overall then, in the second games of back-to-backs, the Kings went 7-10, for a 41.2 winning percentage.
Looking at the suspicious part -- that more than 75 percent of the team's game on 0 days rest were on the road -- you'd assume that the team would pick up a win or two if the number of home games was closer to the number of road games. But you'd be wrong.
Using the above winning percentages (and laughing in the face of small sample sizes), if the Kings played eight of those zero-rest games at home, they'd be 4-4. The other nine would still be on the road, and the Kings would be expected to win 3.47 of them.
We'll round down here and say they go 3-6 (which is closer to the expected 38.5 winning percentage than 4-5 is) for an overall zero-rest game record of ... 7-10. Which is exactly what they went with four home games and 13 roadies.
So, because of the small number of zero-rest games compared to the season overall, there would seem to be no tangible positive effect of more evenly splitting the zero-rest games between the road and home.
But there's more. The home-road split seen in zero-rest games is flipped for games on one day's rest. Of the 47 games played last season by the Kings with one day's test, 28 (or 60 percent) of them were at home and 19 (or 40 percent) were on the road. Overall, the Kings went 31-16 in these games, for a 66.0 winning percentage.
The home-road disparity doesn't appear as great as the zero-rest game split, but it's more significant because of the sheer number of the games in question -- 57 percent of the games came on one day's rest.
The Kings went 22-6 in the home single-day's-rest games (winning 78.6 percent) and 9-10 on the road (winning 47.4 percent).
So let's even these games out and say that 24 came at home and 23 came on the road. The Kings would be expected to go 19-5 in the home ones and 11-12 in the road ones, which would give them 30 wins in the 47 games.
So, the Kings would lose a win if the single-day's-rest games were evened out between Arco and the road.
That would've given the Kings 49 wins, preventing Rick Adelman from keeping up his "five straight seasons of 50 wins" bludgery.
So, in essence, Rick Adelman owes his streak to the schedule-makers!
Also, for what it's worth, there were 14 games on two days rest, eight at home and six on the road, and the Kings did evenly well. 5-3 at home, 4-2 on the road, 9-5 overall. Not too interesting.
The other four games include the first game of the season (a road loss) and three wins after four or more days of rest (two road, one home).
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Ed Küpfer
Joined: 30 Dec 2004
Posts: 785
Location: Toronto
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| Posted: Wed Jul 13, 2005 4:02 pm Post subject: Re: Off-days, Home/Road Splits and Rick Adelman |
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| ziller wrote: | | Looking at the raw data, it appears the Kings got jobbed. They had 17 games with 0 days rest -- the back-end of back-to-backs. Thirteen of those were on the road and four were at home. Highly suspicious. |
Not really. Only two teams had fewer back to backs than the Kings -- half the league had 21+ b2b's. Hell, Kings opponents had 22 back to backs:
| Code: | SAC OPPONENT'S REST
0 1 2 3 TOT
REST -------------------------
0 | 6 5 4 2 17
1 | 15 25 7 0 47
2 | 1 8 4 1 14
3 | 0 1 0 3 4
TOT | 22 39 15 6 82
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We've done some work on this type of stuff -- DanR had a nice post showing the relative advantage of various rest days -- scroll down a little more than halfway. If anyone wants to apply those findings to the schedules from last season, I have a summary of the rest days for each team and their opponents here.
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ziller
Joined: 30 Jun 2005
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Location: Sac Metro
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| Posted: Wed Jul 13, 2005 4:15 pm Post subject: |
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Thanks for the info, Ed. For the record, the jobbing I was referring to in the post was concerning the disproportionate amount of back-to-back backends on the road -- 13 vs. four home games. One would see that and think it's crazy, though it's not. I assume most teams have similar splits.
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ziller
Joined: 30 Jun 2005
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Location: Sac Metro
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| Posted: Wed Jul 13, 2005 5:16 pm Post subject: |
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I really do hate to spam (I do!), but I was poking around and couldn't find much on win probability in basketball. Anyone know of any work done on it?
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HoopStudies
Joined: 30 Dec 2004
Posts: 705
Location: Near Philadelphia, PA
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| Posted: Wed Jul 13, 2005 6:37 pm Post subject: |
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Quick point as I have to get back to work...
In general, some measure of schedule difficulty prior to the season would be very nice to have. This came up last year in Seattle. We felt prior to the season that we had a horribly difficult schedule with back-to-backs and road games and tough teams on back ends. I thought about putting together a metric of such a thing but it never rose to the top of the priority list.
It would be nice to have a measure that we could apply both pre-season and post-season.
Should be very interesting.
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Dean Oliver
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Kevin Pelton
Site Admin
Joined: 30 Dec 2004
Posts: 978
Location: Seattle
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| Posted: Wed Jul 13, 2005 8:52 pm Post subject: |
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| ziller wrote: | | I assume most teams have similar splits. |
They do. Most back-to-backs are on road trips to save a day away from home. Home-road and road-home sets are decently common, and home-home are virtually non-existent.
The Sonics had four home and 15 road second games, eyeballing their schedule. |
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Dan Rosenbaum
Joined: 03 Jan 2005
Posts: 541
Location: Greensboro, North Carolina
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| Posted: Wed Jul 13, 2005 10:24 pm Post subject: |
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| HoopStudies wrote: | Quick point as I have to get back to work...
In general, some measure of schedule difficulty prior to the season would be very nice to have. This came up last year in Seattle. We felt prior to the season that we had a horribly difficult schedule with back-to-backs and road games and tough teams on back ends. I thought about putting together a metric of such a thing but it never rose to the top of the priority list.
It would be nice to have a measure that we could apply both pre-season and post-season.
Should be very interesting. |
Unless the goal is to go undefeated, I think having games where you have an approximate 50/50 chance of winning would be the worst to have on the back end of back-to-backs. I would imagine in the 50/50 games the effect of the back-to-back would be the greatest.
The games against the tough teams on the road would be ones you would be likely to lose anyway; the back-to-back may not have significantly increased your chance of losing. |
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HoopStudies
Joined: 30 Dec 2004
Posts: 705
Location: Near Philadelphia, PA
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| Posted: Wed Jul 13, 2005 10:41 pm Post subject: |
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| Dan Rosenbaum wrote: | | HoopStudies wrote: | Quick point as I have to get back to work...
In general, some measure of schedule difficulty prior to the season would be very nice to have. This came up last year in Seattle. We felt prior to the season that we had a horribly difficult schedule with back-to-backs and road games and tough teams on back ends. I thought about putting together a metric of such a thing but it never rose to the top of the priority list.
It would be nice to have a measure that we could apply both pre-season and post-season.
Should be very interesting. |
Unless the goal is to go undefeated, I think having games where you have an approximate 50/50 chance of winning would be the worst to have on the back end of back-to-backs. I would imagine in the 50/50 games the effect of the back-to-back would be the greatest.
The games against the tough teams on the road would be ones you would be likely to lose anyway; the back-to-back may not have significantly increased your chance of losing. |
So I think your comment then means that your own prior expected win% matters in how tough the schedule is. Since we were supposed to be bad, we shouldn't have complained about tough teams on the back end of back-to-backs. But a posteriori, those were tougher trips because we became good enough that those games we should have lost easily became 50-50 games.
I'd probably leave that out of the first cut.
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Dan Rosenbaum
Joined: 03 Jan 2005
Posts: 541
Location: Greensboro, North Carolina
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| Posted: Wed Jul 13, 2005 11:07 pm Post subject: |
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| HoopStudies wrote: | | Dan Rosenbaum wrote: | | HoopStudies wrote: | Quick point as I have to get back to work...
In general, some measure of schedule difficulty prior to the season would be very nice to have. This came up last year in Seattle. We felt prior to the season that we had a horribly difficult schedule with back-to-backs and road games and tough teams on back ends. I thought about putting together a metric of such a thing but it never rose to the top of the priority list.
It would be nice to have a measure that we could apply both pre-season and post-season.
Should be very interesting. |
Unless the goal is to go undefeated, I think having games where you have an approximate 50/50 chance of winning would be the worst to have on the back end of back-to-backs. I would imagine in the 50/50 games the effect of the back-to-back would be the greatest.
The games against the tough teams on the road would be ones you would be likely to lose anyway; the back-to-back may not have significantly increased your chance of losing. |
So I think your comment then means that your own prior expected win% matters in how tough the schedule is. Since we were supposed to be bad, we shouldn't have complained about tough teams on the back end of back-to-backs. But a posteriori, those were tougher trips because we became good enough that those games we should have lost easily became 50-50 games.
I'd probably leave that out of the first cut. |
Yes, that is what I am saying.
But if you leave that out, I am not quite sure how who you were playing would affect the degree of difficulty. Are you sure what you were planning for the first cut isn't burying an assumption that you are an average team? |
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Ed Küpfer
Joined: 30 Dec 2004
Posts: 785
Location: Toronto
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| Posted: Wed Jul 13, 2005 11:25 pm Post subject: |
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| HoopStudies wrote: | Quick point as I have to get back to work...
In general, some measure of schedule difficulty prior to the season would be very nice to have. This came up last year in Seattle. We felt prior to the season that we had a horribly difficult schedule with back-to-backs and road games and tough teams on back ends. I thought about putting together a metric of such a thing but it never rose to the top of the priority list.
It would be nice to have a measure that we could apply both pre-season and post-season. |
Should be simple enough. Using the logistic model from a previous post we can estimate the probability of a team win given home team and opponent ability, and home team and opponent days rest. Prior to the season, we could use 0.5 for home team strength, and an estimate for opponent strength -- I would use the previous season's Pyth, regressed 40% to 0.5. (The 40% comes from a historical year to year team Pyth correlation of 0.6 -- regression to the mean is 1-r. This is a good fit empirically as well.) Tougher and easier schedules would deviate from 0.5 the most.
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HoopStudies
Joined: 30 Dec 2004
Posts: 705
Location: Near Philadelphia, PA
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| Posted: Thu Jul 14, 2005 12:27 am Post subject: |
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| Dan Rosenbaum wrote: | | HoopStudies wrote: | | Dan Rosenbaum wrote: | | HoopStudies wrote: | Quick point as I have to get back to work...
In general, some measure of schedule difficulty prior to the season would be very nice to have. This came up last year in Seattle. We felt prior to the season that we had a horribly difficult schedule with back-to-backs and road games and tough teams on back ends. I thought about putting together a metric of such a thing but it never rose to the top of the priority list.
It would be nice to have a measure that we could apply both pre-season and post-season.
Should be very interesting. |
Unless the goal is to go undefeated, I think having games where you have an approximate 50/50 chance of winning would be the worst to have on the back end of back-to-backs. I would imagine in the 50/50 games the effect of the back-to-back would be the greatest.
The games against the tough teams on the road would be ones you would be likely to lose anyway; the back-to-back may not have significantly increased your chance of losing. |
So I think your comment then means that your own prior expected win% matters in how tough the schedule is. Since we were supposed to be bad, we shouldn't have complained about tough teams on the back end of back-to-backs. But a posteriori, those were tougher trips because we became good enough that those games we should have lost easily became 50-50 games.
I'd probably leave that out of the first cut. |
Yes, that is what I am saying.
But if you leave that out, I am not quite sure how who you were playing would affect the degree of difficulty. Are you sure what you were planning for the first cut isn't burying an assumption that you are an average team? |
I don't mind burying that assumption for now. You make a good point (as usual), but I'd like to make that assumption. The reason why is that I think the tool makes most sense for use by the league itself. And the league is not well served by assuming that certain teams are going to be bad. "Oh, you're going to be bad, so actually that back-to-back against Dallas and San Antonio isn't so bad. You were going to lose it anyway." With almost every team striving to make the playoffs -- which is usually about .500 -- it also makes perverted sense to them to use this assumption (not actual sense, as you point out, but the kind of sense used car salesmen apply most of the time).
I would like to understand the difference in results between this approach and one more customized to prior estimates of w-l records. Maybe that's an econ paper, Professor Dan!
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Dean Oliver
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HoopStudies
Joined: 30 Dec 2004
Posts: 705
Location: Near Philadelphia, PA
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| Posted: Thu Jul 14, 2005 12:29 am Post subject: |
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| Ed Küpfer wrote: | | HoopStudies wrote: | Quick point as I have to get back to work...
In general, some measure of schedule difficulty prior to the season would be very nice to have. This came up last year in Seattle. We felt prior to the season that we had a horribly difficult schedule with back-to-backs and road games and tough teams on back ends. I thought about putting together a metric of such a thing but it never rose to the top of the priority list.
It would be nice to have a measure that we could apply both pre-season and post-season. |
Should be simple enough. Using the logistic model from a previous post we can estimate the probability of a team win given home team and opponent ability, and home team and opponent days rest. Prior to the season, we could use 0.5 for home team strength, and an estimate for opponent strength -- I would use the previous season's Pyth, regressed 40% to 0.5. (The 40% comes from a historical year to year team Pyth correlation of 0.6 -- regression to the mean is 1-r. This is a good fit empirically as well.) Tougher and easier schedules would deviate from 0.5 the most. |
Go for it, Ed. It sounds like the easiest approach. Do you have this past season's schedules to work with?
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Dean Oliver
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Ed Küpfer
Joined: 30 Dec 2004
Posts: 785
Location: Toronto
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| Posted: Thu Jul 14, 2005 2:23 am Post subject: |
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| HoopStudies wrote: | | Go for it, Ed. It sounds like the easiest approach. Do you have this past season's schedules to work with? |
Yup. I set up a little spreadsheet with all the data that anyone can download. Here is a summary:
| Code: |
TEAM 0 - 0.3 0.3 - 0.4 0.4 - 0.5 0.5 - 0.6 0.6 - 0.7 0.7 - 1.0
ATL 9 21 11 6 26 9
BOS 10 20 11 10 22 9
CHB 9 23 9 6 22 13
CHI 12 20 9 7 24 10
CLE 10 20 10 9 20 13
DAL 10 25 7 10 20 10
DEN 10 23 7 13 15 14
DET 8 24 9 7 22 12
GS 11 23 7 8 23 10
HOU 9 27 6 9 21 10
IND 7 24 11 6 26 8
LAC 13 19 10 9 27 4
LAK 10 20 10 10 23 9
MEM 11 24 6 12 20 9
MIA 9 18 14 10 21 10
MIL 9 21 10 9 21 12
MIN 8 28 4 10 23 9
NJ 6 23 12 7 24 10
NO 15 15 10 7 27 8
NY 12 20 9 6 23 12
ORL 11 21 9 4 22 15
PHI 11 17 13 10 20 11
PHX 12 21 8 12 17 12
POR 10 23 8 9 24 8
SAC 7 24 10 11 19 11
SAN 10 25 7 8 23 9
SEA 12 23 6 9 22 10
TRN 10 23 8 5 28 8
UTA 13 21 7 10 20 11
WAZ 9 21 11 9 23 9 |
The columns labels show the probability of a 0.500 team beating an opponent, factoring opponent strength and days rest for both teams -- the columns show how many games each team played in each bin. For example, ATL played 9 games in which, if they were a .500 team, they would have less than a 0.3 chance of winning the game. You can see the HCA effect at work in the middle columns.
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HoopStudies
Joined: 30 Dec 2004
Posts: 705
Location: Near Philadelphia, PA
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| Posted: Thu Jul 14, 2005 9:45 am Post subject: |
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| Ed Küpfer wrote: | | HoopStudies wrote: | | Go for it, Ed. It sounds like the easiest approach. Do you have this past season's schedules to work with? |
Yup. I set up a little spreadsheet with all the data that anyone can download. Here is a summary:
| Code: |
TEAM 0 - 0.3 0.3 - 0.4 0.4 - 0.5 0.5 - 0.6 0.6 - 0.7 0.7 - 1.0
ATL 9 21 11 6 26 9
BOS 10 20 11 10 22 9
CHB 9 23 9 6 22 13
CHI 12 20 9 7 24 10
CLE 10 20 10 9 20 13
DAL 10 25 7 10 20 10
DEN 10 23 7 13 15 14
DET 8 24 9 7 22 12
GS 11 23 7 8 23 10
HOU 9 27 6 9 21 10
IND 7 24 11 6 26 8
LAC 13 19 10 9 27 4
LAK 10 20 10 10 23 9
MEM 11 24 6 12 20 9
MIA 9 18 14 10 21 10
MIL 9 21 10 9 21 12
MIN 8 28 4 10 23 9
NJ 6 23 12 7 24 10
NO 15 15 10 7 27 8
NY 12 20 9 6 23 12
ORL 11 21 9 4 22 15
PHI 11 17 13 10 20 11
PHX 12 21 8 12 17 12
POR 10 23 8 9 24 8
SAC 7 24 10 11 19 11
SAN 10 25 7 8 23 9
SEA 12 23 6 9 22 10
TRN 10 23 8 5 28 8
UTA 13 21 7 10 20 11
WAZ 9 21 11 9 23 9 |
The columns labels show the probability of a 0.500 team beating an opponent, factoring opponent strength and days rest for both teams -- the columns show how many games each team played in each bin. For example, ATL played 9 games in which, if they were a .500 team, they would have less than a 0.3 chance of winning the game. You can see the HCA effect at work in the middle columns. |
Averaging things out, the expected wins vary from 39.9 (LAC) to 41.9 (NJ and ORL). Not a huge variation, though some may say that 2 games is big. How do the results look if you use end-season records for opponents (still assuming a .500 team)? (The above used previous season results, right?)
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Dean Oliver
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Ed Küpfer
Joined: 30 Dec 2004
Posts: 785
Location: Toronto
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| Posted: Thu Jul 14, 2005 3:53 pm Post subject: |
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| HoopStudies wrote: | | Averaging things out, the expected wins vary from 39.9 (LAC) to 41.9 (NJ and ORL). Not a huge variation, though some may say that 2 games is big. How do the results look if you use end-season records for opponents (still assuming a .500 team)? (The above used previous season results, right?) |
I used the previous season's results, regressed. The very nature of regression reduces the variability of the results, so it's no real surprise to see that every team's schedule looks pretty much the same. Here is the same table, but using the raw 03-04 results to calculate the probabilities:
| Code: | 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
TEAM -0.1 -0.2 -0.3 -0.4 -0.5 -0.6 -0.7 -0.8 -0.9 -1.0
ATL 0 5 6 14 15 9 20 7 6 0
BOS 0 5 9 11 16 13 11 10 7 0
CHB 0 6 8 10 15 12 13 11 7 0
CHI 0 6 9 9 18 13 13 10 4 0
CLE 0 7 8 12 14 8 15 12 6 0
DAL 0 7 10 14 15 7 15 9 5 0
DEN 0 6 10 13 15 11 10 14 3 0
DET 0 4 8 10 16 13 11 14 6 0
GS 0 8 10 8 16 13 15 7 5 0
HOU 0 6 9 17 13 8 16 8 5 0
IND 0 4 6 15 12 14 14 10 7 0
LAC 0 8 9 14 13 12 18 5 3 0
LAK 0 6 8 14 17 8 15 9 5 0
MEM 0 9 5 14 16 11 13 9 5 0
MIA 0 5 10 11 12 12 15 10 7 0
MIL 0 6 7 10 18 11 13 10 7 0
MIN 0 5 10 13 15 10 16 10 3 0
NJ 0 5 4 13 17 10 17 8 8 0
NO 0 8 10 12 11 15 13 9 4 0
NY 0 8 8 6 18 11 13 14 4 0
ORL 0 5 10 10 16 13 10 14 4 0
PHI 0 8 6 10 17 10 15 11 5 0
PHX 0 6 10 15 15 9 12 11 4 0
POR 0 8 7 15 15 10 17 7 3 0
SAC 0 6 7 14 14 14 12 11 4 0
SAN 0 3 12 14 14 11 15 9 4 0
SEA 0 7 9 12 18 9 14 9 4 0
TRN 0 6 8 14 13 9 17 10 5 0
UTA 0 9 8 13 15 9 15 6 7 0
WAZ 0 8 5 12 17 9 17 10 4 0 |
And here is the table you asked for, using the 04-05 Pyths in the calculations:
| Code: | 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
TEAM -0.1 -0.2 -0.3 -0.4 -0.5 -0.6 -0.7 -0.8 -0.9 -1.0
ATL 0 6 10 15 10 12 13 12 4 0
BOS 1 5 9 13 10 12 11 13 7 1
CHB 0 7 9 11 16 9 12 14 4 0
CHI 0 6 9 16 9 10 12 14 6 0
CLE 0 6 9 10 13 10 13 14 6 1
DAL 0 5 11 14 14 12 8 11 6 1
DEN 0 9 9 12 12 12 10 12 6 0
DET 0 4 10 15 11 7 16 12 7 0
GS 0 9 10 12 11 13 9 11 6 1
HOU 1 6 10 15 11 11 11 12 4 1
IND 0 5 10 16 13 6 12 15 4 1
LAC 1 6 11 14 11 13 7 12 7 0
LAK 0 9 11 13 12 13 9 8 7 0
MEM 2 6 9 17 12 9 10 12 4 1
MIA 1 2 9 13 14 9 12 15 7 0
MIL 1 5 8 13 15 9 14 11 6 0
MIN 1 8 9 12 15 10 10 11 6 0
NJ 0 4 11 13 13 8 14 14 4 1
NO 1 7 12 11 13 13 10 10 5 0
NY 0 7 5 19 10 10 13 12 6 0
ORL 0 6 8 15 12 9 13 11 8 0
PHI 0 6 8 15 13 8 15 10 6 1
PHX 0 6 9 14 12 14 9 10 8 0
POR 0 9 10 14 8 17 8 10 6 0
SAC 1 7 8 14 13 12 9 13 5 0
SAN 0 7 11 12 10 12 12 11 7 0
SEA 2 6 7 16 12 12 10 10 7 0
TRN 0 6 8 17 11 7 16 12 5 0
UTA 0 8 11 11 14 13 10 8 6 1
WAZ 0 8 4 15 14 10 10 15 6 0
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It would be an interesting exercise for someone to fiddle with the opponents and days rest in order to come up with a theoretical worst schedule, and compare it to a theoretical best.
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