Tennis / likelyhood of winning a second time
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This post was updated on .
The question is whether a tennis player who won the first set, is more likely to win the second set.
For this I have two variables: Set 1 and Set 2 for the results of the sets (SET1_win / SET2_win 1 / 1= Player 1 wins, 2 = Player 2 wins). In addition, I have the game results in set 1 and set 2 ScoreSet1T1 for the number of points of player 1 in the first set ScoreSet1T2 for the number of points of Player 2 in the first set ScoreSet2T1 for the number of points of player 1 in the second set ScoreSet2T2 for the number of points of player 2 in the second set The record looks like this: ScoreSet1T1 ScoreSet1T2 ScoreSet2T1 ScoreSet2T2 Set1_win Set2_win I could also provide some data. Now I'm not quite clear which method is best. Any help appreciated. Thanks
Dr. Frank Gaeth
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I would do a chi-square. You have four possible outcomes for a 2 set match: win no sets, win set 1 only, win both sets, win set 2 only. A chi-square will answer the question if these four outcomes occur with equal likelihood or not. You would be most interested in the "win both sets" outcome.
On Mon, May 14, 2012 at 6:03 AM, drfg2008 [via SPSSX Discussion] <[hidden email]> wrote: The question is whether a tennis player who won the first set, is more likely to win the second set. -- Lori Andersen Ph.D. student, Educational Policy, Planning & Leadership College of William & Mary Williamsburg, VA |
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This post was updated on .
As far as I understand a Chi-square test is testing independence between the two sets, which is definitely not the case since the winner of set 1 is stronger and will be more likely to win set 2, too. And this is not my question. The question is if the likelyhood increases to win again when the player has won before.
I thougth about the McNemar test first since this tests if a change from winning to loosing is equal likely as the change from loosing to winning. If the hypothesis (see above) is true (namely that a winner is more likely to win again) there should be more changes from one side to the other. But this can not be the solution, since the winner is the non-looser and the looser is the non-winner in equal proportions.
Dr. Frank Gaeth
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Hi:
I think you have paired data, since in the first match, one member of the pair wins, and, therefore, the other one loses. You have to take into account the pairing and treat the data as a matched cohort study. McNemar test will do that, but you get only a p-value, not an estimate of the increase of likelihood of victory. You need a relative risk that takes into account the matching. Look for this paper: The Stata Journal (2004) 4, Number 3, pp. 274–281, Analysis of matched cohort data, by Peter Cummings Barbara McKnight. I have also read that log-binomial or Poisson regression can be used for that. I hope this helps, Marta GG El 14/05/2012 14:06, drfg2008 escribió: > As far as I understand a Chi-square test is testing independence between the > two sets, which is definitely not the case since the winner of set 1 is > stronger and will be more likely to win set 2, too. And this is not my > question. The question is if the likelyhood increases to win again when the > player has won before. > > I thougth about the McNemar test first since this tests if a change from > winning to loosing is equal likely as the change from loosing to winning. If > the hypothesis (see above) is true (namely that a winner is more likely to > win again) there should be more changes from one side to the other. > > > > ----- > Dr. Frank Gaeth > FU-Berlin > > -- > View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Tennis-tp5708820p5708910.html > Sent from the SPSSX Discussion mailing list archive at Nabble.com. > > ===================== > To manage your subscription to SPSSX-L, send a message to > [hidden email] (not to SPSSX-L), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSX-L > For a list of commands to manage subscriptions, send the command > INFO REFCARD > ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
Re: Tennis / likelyhood of winning a second time
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In reply to this post by drfg2008
As is typical, your question is as clear as MUD!
Please carefully reformulate this with the addition of whatever assumptions you are making about the data and try again. First step back and reread your question to a hopefully forgiving coworker and see if you get anything other than a blank stare. You don't do yourself any favors by repeatedly posting nebulous carelessly formulated questions to this list which require 4-5 iterations to gel. You seem to think this group is here as a free consulting service and that you don't need to use your own thinking about your research! Last week it was Futball, this week Tennis, a month or so ago some nebulous 5000 variable GLM and Poisson regression prior to that and Python in the mix as well. This wouldn't be so much a problem if it weren't for the fact that you *NEVER* bother to pitch in and help anyone else. Look up Reciprocity in your German/English dictionary. ---
Please reply to the list and not to my personal email.
Those desiring my consulting or training services please feel free to email me. --- "Nolite dare sanctum canibus neque mittatis margaritas vestras ante porcos ne forte conculcent eas pedibus suis." Cum es damnatorum possederunt porcos iens ut salire off sanguinum cliff in abyssum?" |
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This post was updated on .
@David
This wouldn't be so much a problem if it weren't for the fact that you *NEVER* bother to pitch in and help anyone else. Look up Reciprocity in your German/English dictionary. Look at that: http://www.statistik-tutorial.de/forum/index.php I posted over 1382 answers here for people asking questions. Look at that: youtube. Here I posted more than 60 films / introductions into SPSS (more than 100 thousand downloads) All for free, David.
Dr. Frank Gaeth
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Re: Tennis / likelyhood of winning a second time
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Administrator
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Congratulations on your contributions to German intellectual culture.
I was referring to the SPSS-X list (here, this place...). You still need to clarify your question.
Please reply to the list and not to my personal email.
Those desiring my consulting or training services please feel free to email me. --- "Nolite dare sanctum canibus neque mittatis margaritas vestras ante porcos ne forte conculcent eas pedibus suis." Cum es damnatorum possederunt porcos iens ut salire off sanguinum cliff in abyssum?" |
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In reply to this post by drfg2008
Thought about using a binary log Model, but couldn’t find a proper solution.
The question is part of an ongoing scientific discussion. Examples [1] [2] [1] http://www.plosone.org/article/info:doi%2F10.1371%2Fjournal.pone.0024532 [2] http://statracket.net/A.%20James%20O%27Malley.pdf [3] @ D. M.: 146.063 Downloads 25.03.2008 – 14.05.2012 Top Countries Germany Austria Switzerland Netherlands United States United Kingdom Spain Italy India Sweden
Dr. Frank Gaeth
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Re: Tennis / likelyhood of winning a second time
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Frank:
Did you read my reply to your first message? See below a simple dataset, adapted from the Stata Journal paper I mentioned then. I have changed the variable names to Set1 & Set2. This is the syntax I used for the conditional log-binomial regression model: * Ecuaciones de estimación generalizadas. GENLIN Set2 (REFERENCE=FIRST) BY Set1 (ORDER=DESCENDING) /MODEL Set1 INTERCEPT=YES DISTRIBUTION=BINOMIAL LINK=LOG /CRITERIA METHOD=FISHER(1) SCALE=1 MAXITERATIONS=100 MAXSTEPHALVING=5 PCONVERGE=1E-006(ABSOLUTE) SINGULAR=1E-012 ANALYSISTYPE=3 CILEVEL=95 /REPEATED SUBJECT=Match WITHINSUBJECT=Set1 SORT=YES CORRTYPE=INDEPENDENT ADJUSTCORR=YES COVB=ROBUST MAXITERATIONS=100 PCONVERGE=1e-006(ABSOLUTE) UPDATECORR=1 /MISSING CLASSMISSING=EXCLUDE /PRINT CPS DESCRIPTIVES MODELINFO FIT SUMMARY SOLUTION(EXPONENTIATED). HTH, Marta Dataset: * Use numerical values for Set1&Set2 (0=Loser; 1=Winner). Match Set1 Set2 1 Winner Winner 1 Loser Winner 2 Loser Winner 2 Winner Winner 3 Winner Winner 3 Loser Winner 4 Winner Winner 4 Loser Winner 5 Winner Winner 5 Loser Winner 6 Loser Winner 6 Winner Winner 7 Loser Winner 7 Winner Winner 8 Winner Winner 8 Loser Winner 9 Loser Winner 9 Winner Winner 10 Loser Winner 10 Winner Winner 11 Winner Winner 11 Loser Winner 12 Loser Winner 12 Winner Winner 13 Winner Winner 13 Loser Winner 14 Winner Winner 14 Loser Winner 15 Winner Winner 15 Loser Winner 16 Loser Winner 16 Winner Winner 17 Loser Winner 17 Winner Winner 18 Winner Winner 18 Loser Winner 19 Loser Winner 19 Winner Winner 20 Winner Winner 20 Loser Winner 21 Winner Winner 21 Loser Winner 22 Winner Winner 22 Loser Winner 23 Winner Winner 23 Loser Winner 24 Winner Winner 24 Loser Winner 25 Loser Winner 25 Winner Winner 26 Winner Winner 26 Loser Winner 27 Winner Winner 27 Loser Winner 28 Loser Winner 28 Winner Winner 29 Winner Winner 29 Loser Winner 30 Loser Winner 30 Winner Winner 31 Winner 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Thanks Marta! This is exactly what I was looking for. I tested the Syntax (probably Match should be unique?) with your data. ************************* Parameter Estimates Parameter B Std. Error 95% Wald Confidence Interval Hypothesis Test Exp(B) 95% Wald Confidence Interval for Exp(B) Lower Upper Wald Chi-Square df Sig. Lower Upper (Intercept) -.652 .0544 -.759 -.546 143.829 1 .000 .521 .468 .579 [Set1=2] .346 .0641 .220 .472 29.158 1 .000 1.414 1.247 1.603 [Set1=1] 0a . . . . . . 1 . . (Scale) 1 Dependent Variable: Set2 Model: (Intercept), Set1 a Set to zero because this parameter is redundant.
Dr. Frank Gaeth
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Re: Tennis / likelyhood of winning a second time
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El 15/05/2012 21:30, drfg2008 escribió:
> Thanks Marta! > > This is exactly what I was looking for. I tested the Syntax (probably Match > should be unique?) with your data. Yes, Match values should be, as in the example, 1 1 2 2 3 3.... It identifies the two players (winner&loser of the first set) that played one against the other. You can't have more than a pair of "1", or "2"... BTW, I did a bit of math with the help of old fashioned scrap paper & pencil and realized that your design can be seen as either a matched cohort design (you classify players for exposition - 1t set outcome- and watch the 2nd set to classify them as loser/winner), or matched case-control design (you classify players for the outcome of the 2nd set, and look retrospectively for the outcome of the first). This makes the output of a conditional log-binomial model and conditional logistic model exactly the same. Also, you could use contingency tables stratified by Mach, and ask for the Mantel-Haenszel OR, and get the same result. Regards, Marta GG > > ************************* > > Parameter Estimates > Parameter B Std. Error 95% Wald Confidence Interval Hypothesis Test > Exp(B) 95% Wald Confidence Interval for Exp(B) > Lower Upper Wald Chi-Square df Sig. Lower Upper > (Intercept) -.652 .0544 -.759 -.546 143.829 1 .000 .521 .468 .579 > [Set1=2] .346 .0641 .220 .472 29.158 1 .000 1.414 1.247 1.603 > [Set1=1] 0a . . . . . . 1 . . > (Scale) 1 > Dependent Variable: Set2 > Model: (Intercept), Set1 > a Set to zero because this parameter is redundant. > > > > ----- > Dr. Frank Gaeth > FU-Berlin > > -- > View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Tennis-likelyhood-of-winning-a-second-time-tp5708820p5710325.html > Sent from the SPSSX Discussion mailing list archive at Nabble.com. > > ===================== > To manage your subscription to SPSSX-L, send a message to > [hidden email] (not to SPSSX-L), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSX-L > For a list of commands to manage subscriptions, send the command > INFO REFCARD > ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
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In reply to this post by Marta Garcia-Granero
@Marta García-Granero-2
Thank you for the very interesting ideas you provided! Just a question to your data: As far as I understand now, each game is not unique, each game occurs two times and has two times the same matchnumber: 1-1, 2-2, etc.. But if you consider a Best of 3 game for example you only have the following alternatives: win - win (2:0) win - lose - win (2:1) lose - win - lose (1:2) lose - lose (0:2) So if you test the hypothesis of a higher probability after winning a set, you only have the (2:0) solution in best of three (best of five is more complicated). How can you have two lines for one game as in your example. Frank
Dr. Frank Gaeth
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