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When Losing Leads to Winning
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Eli W



Joined: 01 Feb 2005
Posts: 402

PostPosted: Wed Mar 18, 2009 10:14 am    Post subject: When Losing Leads to Winning Reply with quote

There's some pretty interesting discussion going on springing from a research paper that suggests that it could be a good thing to be trailing by one point at the half of a college basketball game.

Here's the NY Times piece:

http://www.nytimes.com/2009/03/16/sports/ncaabasketball/16score.html?_r=2

It points to the original paper:

http://qbox.wharton.upenn.edu/documents/mktg/research/Losing_and_Winning.pdf

Some criticism of the study can be found on various blogs (the second link in particular may be of interest as it follows up with some NBA research):

http://www.insidethebook.com/ee/index.php/site/comments/being_behind_is_a_good_thing/

http://www.insidethebook.com/ee/index.php/site/comments/being_behind_is_a_good_thing_part_ii/

http://www.stat.columbia.edu/~cook/movabletype/archives/2009/03/basketball_news.html

http://freakonomics.blogs.nytimes.com/2009/03/17/when-losing-leads-to-winning/
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Ryan J. Parker



Joined: 23 Mar 2007
Posts: 708
Location: Raleigh, NC

PostPosted: Wed Mar 18, 2009 10:22 am    Post subject: Reply with quote

Gelman's analysis caught my eye this morning. I love this stuff. Right or wrong, this is a great learning tool when really smart people analyze this kinda thing.
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Guy



Joined: 02 May 2007
Posts: 128

PostPosted: Wed Mar 18, 2009 10:40 am    Post subject: Reply with quote

Does anyone here know of NBA data that would show if the same pattern occurs there? Ed K. posted some data on win% at various minute/score states a while back, but the link is now broken.
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Ed Küpfer



Joined: 30 Dec 2004
Posts: 785
Location: Toronto

PostPosted: Wed Mar 18, 2009 2:17 pm    Post subject: Reply with quote

I wish I could help. The original data is gone, disappeared on a long lost hard drive. I now have newer, better data, which I am obviously not allowed to give out.

I can tell you this: my original dataset came from NBA.com play by plays. You can recreate this by using the data provided at basketballvalue. In fact, it will be much better since their data is much cleaner than the stuff I used. I don't know how hard it would be to do this, but if I can do it, anyone can do it in half the time.
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Guy



Joined: 02 May 2007
Posts: 128

PostPosted: Wed Mar 18, 2009 3:34 pm    Post subject: Reply with quote

Ed: Can you just tell us how often teams win when they lead by 1 point at the half? Surely that isn't a proprietary figure. :>)
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Ed Küpfer



Joined: 30 Dec 2004
Posts: 785
Location: Toronto

PostPosted: Wed Mar 18, 2009 4:01 pm    Post subject: Reply with quote

I found some old data that may be helpful. Home team halftime leads and eventual wins, games from 1992 to 2002. (The 20 point leads and deficits, I'm not sure if they mean actual 20 points or 20+ points.)

Code:
lead   wins    games
-20     0       43
-19     4       55
-18     5       67
-17     6       72
-16     4       81
-15     14      117
-14     18      118
-13     32      155
-12     39      164
-11     38      221
-10     63      236
-9      64      246
-8      112     311
-7      113     364
-6      120     324
-5      147     386
-4      175     401
-3      190     395
-2      241     479
-1      255     460
0       271     497
1       296     509
2       289     483
3       322     500
4       335     513
5       315     438
6       372     462
7       331     424
8       311     377
9       293     358
10      296     355
11      293     336
12      266     287
13      245     279
14      205     231
15      207     221
16      169     184
17      178     185
18      135     140
19      115     116
20      102     105

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Serhat Ugur (hoopseng)



Joined: 13 Oct 2006
Posts: 208
Location: Basketball Research

PostPosted: Wed Mar 18, 2009 4:11 pm    Post subject: Reply with quote

last season it is 52-56. (trailing by 1 and win the game)
this season it is 38-47
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Last edited by Serhat Ugur (hoopseng) on Wed Mar 18, 2009 4:27 pm; edited 1 time in total
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Guy



Joined: 02 May 2007
Posts: 128

PostPosted: Wed Mar 18, 2009 4:24 pm    Post subject: Reply with quote

Thanks, Ed. Very helpful.
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Mike G



Joined: 14 Jan 2005
Posts: 3552
Location: Hendersonville, NC

PostPosted: Thu Mar 19, 2009 6:11 am    Post subject: Reply with quote

I'm guessing Ed's data must be referring to the halftime status of the home team. A halftime tie is won 56% of the time by somebody, eh?. Likewise:
Code:
lead    win
+20    .982
+15    .914
+10    .841
 +5    .723
  0    .561
 -5    .398
-10    .235
-15    .114
-20    .041

In each case, this team does much better in the 2nd half; and a halftime deficit is much worse for the 'other' team.
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Guy



Joined: 02 May 2007
Posts: 128

PostPosted: Thu Mar 19, 2009 9:45 am    Post subject: Reply with quote

Hoopseng: Is that data for all teams, or home teams only?
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schtevie



Joined: 18 Apr 2005
Posts: 408

PostPosted: Thu Mar 19, 2009 10:41 am    Post subject: Reply with quote

The paper is cute, but I don't find it that interesting from a basketball perspective. And apparently not at all from an NBA perspective.

Given Ed's data, and the familiar home court advantage of between 3 to 4 points - call it half that at halftime, it would seem that, lo and behold, home teams down 2 points at the half win....half their games (241 out of 479). Maybe this has something to do the attitudes of professionals vs. amateurs. Lack of rah, rah, and all that.

More generally, It would have been interesting if the study had included corroborating analysis of overtime games. According to their set-up, as I understand it, a game that ends in a tie is actually a very slight notional deficit for the away team, given the generally accepted existence of the home court advantage, and it should invoke their relatively greater effort. It would have been nice confirmation to see away teams winning more than 50% of OT games. Maybe it is so, maybe it isn't.
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Guy



Joined: 02 May 2007
Posts: 128

PostPosted: Thu Mar 19, 2009 11:21 am    Post subject: Reply with quote

Actually, the NBA data provides partial support. In Ed's data, and more recent data compiled by Mitchell Lichtman, it appears that HOME teams down one at the half win more than they should. They win about as frequently (slightly more) than in tie games. (Alternatively, road teams up by one at the half win less than they should.) Road teams do not show this -1 effect. See the 2nd link in Eli's original post above for discussion of this at The Book blog.
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Ed Küpfer



Joined: 30 Dec 2004
Posts: 785
Location: Toronto

PostPosted: Thu Mar 19, 2009 12:27 pm    Post subject: Reply with quote

Okay, I went ahead and did some more work on this. By incorporating the home and away teams' win percentage, I calcuated the home team win probabilty (log5) for each game in the old data I have. I created a histogram of home team half time leads, binned by the probability of the home team winning the game.



For some reason, "home team down one at the half" games are overrepresented when the home team is playing a far superior opponent.

Next home team win percentages by lead at the half, again binned by log5:



Nothing looks out of line there. It appears that once you take relative team strengths into account, home teams down one at the half win about as much as they're supposed to.
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ecumenopolis0



Joined: 15 Jul 2008
Posts: 22
Location: Houston

PostPosted: Thu Mar 19, 2009 12:33 pm    Post subject: Reply with quote

schtevie wrote:
It would have been nice confirmation to see away teams winning more than 50% of OT games. Maybe it is so, maybe it isn't.


Since the 86-87 season, home wins OT games 796-741, or at about .518

Home/away may not be the best OT predictor.

Somewhat OT (off-topic, not overtime), but it was always my understanding that the team to force overtime with that last score or stop in regulation was much more likely to win. I have no numbers to back this up, but this would seem to me the best way to predict the winner.
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Ed Küpfer



Joined: 30 Dec 2004
Posts: 785
Location: Toronto

PostPosted: Thu Mar 19, 2009 12:55 pm    Post subject: Reply with quote

Further evidence that I shouldn't trust my eyes to see patterns in the data. I regressed probability of home team win on home and away team win percentages along with home team lead at the half, the latter variable treated as a categorical (factor in R parlance). Here are the regression results, which do show something fishy about -1, but I'm not sure what.

Code:
              coef.est coef.se
a.win.p       -0.68     0.02 
h.win.p        0.76     0.03 
factor(h2)-15  0.17     0.04 
factor(h2)-14  0.23     0.04 
factor(h2)-13  0.25     0.04 
factor(h2)-12  0.28     0.04 
factor(h2)-11  0.21     0.03 
factor(h2)-10  0.30     0.03 
factor(h2)-9   0.31     0.03 
factor(h2)-8   0.38     0.03 
factor(h2)-7   0.32     0.03 
factor(h2)-6   0.38     0.03 
factor(h2)-5   0.39     0.03 
factor(h2)-4   0.42     0.03 
factor(h2)-3   0.46     0.03 
factor(h2)-2   0.49     0.03 
factor(h2)-1   0.54     0.03  <-- Oy!
factor(h2)0    0.52     0.03 
factor(h2)1    0.54     0.03 
factor(h2)2    0.56     0.03 
factor(h2)3    0.58     0.03 
factor(h2)4    0.59     0.03 
factor(h2)5    0.65     0.03 
factor(h2)6    0.73     0.03 
factor(h2)7    0.71     0.03 
factor(h2)8    0.74     0.03 
factor(h2)9    0.73     0.03 
factor(h2)10   0.74     0.03 
factor(h2)11   0.77     0.03 
factor(h2)12   0.79     0.03 
factor(h2)13   0.77     0.03 
factor(h2)14   0.78     0.03 
factor(h2)15   0.83     0.03 
---
  n = 10647, k = 33
  residual deviance = 1786.7, null deviance = 6268.0 (difference = 4481.3)
  overdispersion parameter = 0.2
  residual sd is sqrt(overdispersion) = 0.41


(I only inlcuded games where the absolute lead was less than 16.)
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