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Football General Talk

I was already concerned about you but I was really starting to get nervous when you were replying to yourself until I read Sytes’ comments.
I think we may need to do a rescue intervention on Sytes' here. Maybe strap him to a chair and make him watch Vikings/Packer reruns - every single one of them.
 
The nfl record after a bye this season is 15 wins-17 losses. Your Vikings are part of the 17. My packers and the lions are apart of the 15.

Every employee no matter the profession covets a day off. Are we at our best performing the first couple days back or we are running around frantically trying to get back in a routine?
For any random basket of games, on average the league is about .500 . So in advance I would have predicted 16-16 -- so essentially bye week does not negatively impact competitiveness of following game. But it is nonetheless a week no-one gets injured (a few may get arrested ;) ) and a week of rest - both good for the body over the long haul and especially good this late in the year.

edited - fixed math
 
Rank of interest:

Division One NCAA football
The rest of NCAA football
NFL
MLB
NHL
.
.
.
Sitting on chitter
.
.
.
NBA.

OK my rank of interest in watching - with gaps where the spread is large (chitter & pickleball only included out of respect to @BrentD and @Sytes):

MN Vikings
NDSU Bison
-
The rest of the NFL
Olympic Hockey
Top 25 match ups in the NCAA Division I FBS
NCAA D1 March Madness
-
NBA Playoffs
NHL Playoffs
-
-
NBA regular season
-
NCAA D1 Hockey
NHL regular season
NCAA BB D1 regular season
The final game of men's World Cup Soccer
Golf
-
-
Pickelball
-
-
Tennis
-
-
chitter
-
-
All other soccer
Baseball of any form
 
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For any random basket of games, on average the league is about .500 . So in advance I would have predicted 16-16 -- so essentially bye week does not negatively impact competitiveness of following game. But it is nonetheless a week no-one gets injured (a few may get arrested ;) ) and a week of rest - both good for the body over the long haul and especially good this late in the year.

edited - fixed math
This isn't a random sampling, this is the record for the whole league after a bye week, anywhere from 2-6 teams are on bye each week and they very rarely play each other following a bye. A bye week is not the same as a week where they play with certain players resting but in essence it's the same for the starters. If your argument is true, that teams benefit from resting players, the teams coming off a bye week would be undefeated or at least better than a .468 winning average.
 
This isn't a random sampling, this is the record for the whole league after a bye week, anywhere from 2-6 teams are on bye each week and they very rarely play each other following a bye. A bye week is not the same as a week where they play with certain players resting but in essence it's the same for the starters. If your argument is true, that teams benefit from resting players, the teams coming off a bye week would be undefeated or at least better than a .468 winning average.
First, either we call it "randomized" or not. If not, then nothing can be taken from it as you haven't normalized for home/road or opponent quality.

Second, some bye weeks are week 4, 5, etc -- a very different proposition than bye week in week 19

Third, under no scenario would I predict 100% value from anything - home field, week off, etc.

Fourth, there is no way your data set has statical power sufficient to distinguish between 15-17 or 17-15.

Also, you have two different hypothesis to test (1) does the bye week increase a team likelihood of winning the next game and (2) does the bye week decrease a team's likelihood of losing the next game. This data suggests both hypotheses are false, so it likely is true that a bye week spread across the early - mid season doesn't reduce chance of winning due to lack of continuity you suggest, but does not at all speak to the benefit of week 19 rest ahead of 3 more games against top competition.

In the end, if you are right, then the Vikings should throw our game against the Lions because we should fear a bye week. The Chiefs should have thrown a few games earlier for the same reason. That is a bit silly.
 
First, either we call it "randomized" or not. If not, then nothing can be taken from it as you haven't normalized for home/road or opponent quality.

Second, some bye weeks are week 4, 5, etc -- a very different proposition than bye week in week 19

Third, under no scenario would I predict 100% value from anything - home field, week off, etc.

Fourth, there is no way your data set has statical power sufficient to distinguish between 15-17 or 17-15.

Also, you have two different hypothesis to test (1) does the bye week increase a team likelihood of winning the next game and (2) does the bye week decrease a team's likelihood of losing the next game. This data suggests both hypotheses are false, so it likely is true that a bye week spread across the early - mid season doesn't reduce chance of winning due to lack of continuity you suggest, but does not at all speak to the benefit of week 19 rest ahead of 3 more games against top competition.

In the end, if you are right, then the Vikings should throw our game against the Lions because we should fear a bye week. The Chiefs should have thrown a few games earlier for the same reason. That is a bit silly.
You are the one that used a bye week as a comparison to resting players. and you are the one that said "For any random basket of games, on average the league is about .500" How do you define a random basket? The games following a bye week are a very specific set of games, not a random basket, and in that very specific set of games the entire league is 15-17.
In your defense, the teams that get a bye in the first round of the playoffs are a combined 39-13 since 2010 (according to reddit, so take that for what its worth)

Thanks to the google machine we do not have to use bye's as a comparison to resting starters. Here's an SI article from 2021 on resting vs not resting. According to this article teams who rest starters in week 17 (before the season was 18 weeks) had a winning average .333 and teams who did not rest in week 17 had a winning average of .786

The bottom line is resting may work for some teams, it may not work for others. It is the coaches job to do what they believe is best for their team. If a coach who has the option of resting players in the final week of the season has the philosophy that is what is best for their team then they will do it and vice versa.
 
First, either we call it "randomized" or not. If not, then nothing can be taken from it as you haven't normalized for home/road or opponent quality.

Second, some bye weeks are week 4, 5, etc -- a very different proposition than bye week in week 19

Third, under no scenario would I predict 100% value from anything - home field, week off, etc.

Fourth, there is no way your data set has statical power sufficient to distinguish between 15-17 or 17-15.

Also, you have two different hypothesis to test (1) does the bye week increase a team likelihood of winning the next game and (2) does the bye week decrease a team's likelihood of losing the next game. This data suggests both hypotheses are false, so it likely is true that a bye week spread across the early - mid season doesn't reduce chance of winning due to lack of continuity you suggest, but does not at all speak to the benefit of week 19 rest ahead of 3 more games against top competition.

In the end, if you are right, then the Vikings should throw our game against the Lions because we should fear a bye week. The Chiefs should have thrown a few games earlier for the same reason. That is a bit silly.
1735591345323.png
 
For any random basket of games, on average the league is about .500 . So in advance I would have predicted 16-16 -- so essentially bye week does not negatively impact competitiveness of following game. But it is nonetheless a week no-one gets injured (a few may get arrested ;) ) and a week of rest - both good for the body over the long haul and especially good this late in the year.

edited - fixed math
Actually, the null hypothesis might be .500, but in this case, it does not have to be. It is quite possible that every team could lose in its first game after a bye. It would be interesting to know, what is that batting average over a longer period - like the last 10 or 20 yrs. And especially for late-season byes when the banged up body count is a lot higher.

You guys need to bone up on your hypothesis testing skills. Be that as it may, it only makes sense to use all the data, since it is available (in principle but I do not know how to access it).


As for best sports, I generally prefer to watch individual sports, and though I have never played, golf is fascinating because it is very similar to competitive rifle shooting and it is one man against the elements sort of thing. With a million bucks and major titles at stake on a single swing of a stick, it has something that team sports will never have.

It is something to know that your next shot will make or break your quest for a major championship.
 
Can we all agree that the Chiefs and their striped home deciders will be well rested?

Hey now!!

Chiefs/Vikings in the Super Bowl will be a family splitter.

Daughter/SIL in Minnesota, they just keep waiting for SKOL Nation to snatch defeat out of the jaws of victory, but O'Connell/Darnold and speedy hitting machines on defense seem to have avoided the infamous ways of losing of past Vikings teams.

I hope it is a house divided monster of a game....with a first ever 3pete.
 
Cool, but what is it? Some sort of multivariate principle components analysis? My be interesting, might be garbage.
EPA is "expected points added" over median off/def by a given play or player. It is one of the modern metrics that correlates pretty highly with winning. Taking out "garbage time" is obviously subjective choice, but by taking out the parts of games where teams are in "prevent defense" and "burn the clock offense" does make sense.

 
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