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Titans to start Ryan Tannehill

Discussion in 'Miami Dolphins Forum' started by bbqpitlover, Oct 16, 2019.

  1. cbrad

    cbrad . Club Member

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    Good, so here's a nice lesson in how probability is calculated with continuous distributions. The probability of a rating being "average" the way you defined it is zero. You wanted to defined "average" as precisely a rating of 91. In ANY continuous distribution where every value has some non-negative probability of occurring, the probability of randomly picking any specific value (e.g., precisely 91) is zero.

    However.. the probability of 91.0001 and up refers to a range of possibilities, and in a symmetric distribution (which for simplicity we're assuming here – if you look at a large enough sample it is slightly skewed but symmetric is a good approximation) the probability of the entire range of 91.0001 and up is 50% probability.

    So.. based on how you want to define "average" and "above average", the probability of randomly choosing 4 out of 5 passer ratings that are "above average" and one precisely "average" is zero percent because you NEVER (probabilistically) can flip "average" = precisely 91.

    So it never happens basically, given how you want to define "average". In general, you have to choose ranges of values to get non-negative probabilities. But why do that in the first place? The thresholds defining any range as "average" or "above average" will be your subjective ones. It's much better to just take the ratings as is and calculate probabilities based on those. AND.. in ANOVA what you do is you look at properties of the distributions of those ratings, like their variance. In other words, for continuous values you don't care about the probability of every single value because it's always zero. Instead you look at the set of values as a unit.
     
  2. The Guy

    The Guy Well-Known Member

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    Quite possible, and that would be an internal attribution, as opposed to one centered on the athlete's surroundings. Again we have no idea the effect of the Titans' surroundings on Tannehill when we aren't measuring them.

    The questions then would become, how likely is the athlete to experience "the zone," and for how long can he sustain it?
     
  3. resnor

    resnor Derp Sherpa

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    Unlikely things happen all the time. Let’s say there are 50 unlikely things that can happen. Anyone of them is occurring in a game. Say there are 1000 unlikely things. Let’s say 10 happen in a game. That’s still unlikely. You guys love to play freaking semantics and avoid the actual discussion.
     
  4. The Guy

    The Guy Well-Known Member

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    Read post #680. Lots of unlikely things probably happened for Andy Dalton in 2015. But they've happened for only one season because they're unlikely.
     
  5. cbrad

    cbrad . Club Member

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    Semantics matters. I mean.. if you can't precisely define the question you can't answer it either because you can always keep saying "no that's not what was meant". Fin D was talking about random sampling from ONE continuous distribution. In that context unlikely things happen infrequently by definition. You're talking about the probability of one of X unlikely events occurring. That can be highly likely to occur of course. So.. either state things precisely or accept that people will infer what you meant based on context.

    And none of us are avoiding actual discussion. Just read the pages worth of actual discussion to see that.
     
  6. Fin D

    Fin D Sigh Club Member

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    No. Unlikely things happen all the time, every second of every day. It may not be the same unlikely things (hence those things being unlikely), but things we don't expect to happen, happen all the time. Every game, something unlikely happens at some point.

    The problem is people are using stats as definitive explanations. Statistically, there should be no Tom Brady. Statistically, at the time, Drew Brees career should have been over after that surgery. Stats only give an idea, not a reason. You have to look at more. That's why I keep asking you guys to explain the ways a team can counter the pass rush. If you don't understand or account for those things, all you're doing is making assumptions based on LESS data.

    The passer rating can be affected by numerous things from surrounding talent, opposing talent, to playoff chances to weather and all of that is based on when the game is played. Removing the "when" by randomly taking those numbers from anywhere, removes the effect of all those variables. You are literally removing data points.
     
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  7. cbrad

    cbrad . Club Member

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    When do I make these "definitive explanations"? I always make it clear we're looking at the likelihood of a hypothesis being true based on historical data. It's actually the guys that don't rely on statistics that tend to make definitive explanations.. you know like asserting that Tannehill had it worse than any other QB in the league here in Miami. Statistics actually keeps you more honest about what level of certainty you can apply to different hypotheses (because it allows you to quantify them).

    You're removing information when you use statistics, yes. But there are no causal variables being removed. Removing a causal variable (e.g., weather, crowd noise, etc...) would mean you adjusted the stat for that causal variable. That's not happening here. The stat is simply the effect of ALL those causal variables. None are being removed, even if you are removing information.
     
  8. The Guy

    The Guy Well-Known Member

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    Whether unlikely things happen doesn't make them frequent. Unlikely things can happen and nonetheless happen infrequently.

    Statistics indicate that a Tom Brady-caliber quarterback is highly unlikely to be drafted in the sixth round. Teams would be very foolish to believe they can wait until the sixth round to draft a great quarterback, and it's statistics that determine that foolishness. Statistics do account for a Tom Brady, and they allocate the appropriate probability to such an event.

    Again take a look at post #680. Andy Dalton apparently got a whole lot of unlikely events like the kind you mentioned to happen in 2015. Nobody is discounting the effect of those things when they occur.

    However, if you're using a quarterback whose performance at the necessary level hinges on the occurrence of such unlikely events (Andy Dalton), obviously you're doing a whole lot worse than you would be if you had a quarterback whose performance at the necessary level doesn't hinge on the occurrence of such events (Russell Wilson).

    Coming back to the topic at hand, this is why in my opinion it'll be necessary to wait two or three years to determine exactly what's going on with Ryan Tannehill right now. If he's essentially replicating an Andy Dalton 2015 season -- whether that's due to internal and/or external variables -- it won't mean much in terms of his overall career.
     
  9. Fin D

    Fin D Sigh Club Member

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    We tell you X is the cause, based on actual facts, and then you tell us nope that's likely not it based on statistical data. Data, which doesn't account in anyway for X. So we argue. You then go down rabbit holes and tell us definitively X is either not an issue or cannot be accounted for or is a constant across the league.

    Again this only works if the causal variables are consistent across the league or games. They aren't.

    Its entirely possible to pull three games from a QB and those three games are Game A= first game with team so everything is off, Game B= playing injured and Game C= playing the best defense in the league and the playcalling was off.
     
  10. Fin D

    Fin D Sigh Club Member

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    The way stats are being used in here, is that while Tom Brady's success is happening, we're being told it likely isn't.

    No one in here is really projecting anything, like your example that we shouldn't draft a 6th round QB expecting Tom Brady. All we are saying is that Thill had issues beyond his control that caused his time here to be less than what it could be. We are being told it likely isn't the case.

    No one is hinging anything on Thill putting up good numbers dude to unlikely events. We have explained that he had obstacles most QBs don't have beyond his control. Then we are told that's likely not true due to stats that don't in anyway account for the reasons we gave.

    I've asked 2 questions numerous times now and in all the years we've been arguing Thill no one actually answers them, including you....

    1. What are the ways a QB/team can counter a pass rush?
    2. What modern era QB had a terrible line, but was also not allowed to audible and had no commitment to the run game, but was successful?
     
  11. cbrad

    cbrad . Club Member

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    Yeah.. replace that word "definitely" with "likely" in the last sentence and that's more or less correct. Point is, I'm not providing definitive explanations of "why" we observed what we observe. However, I do make definitive claims about the math and sources of uncertainty.

    My response is very specific to your claim that the stat is NOT taking into account all the possible variables that could affect it. The stat literally is the effect of ALL possible variables that could affect it. All you're trying to say (though it's not what you actually wrote) is that we don't know how the myriad of variables affect that stat. And that's correct. But the stat does NOT remove the effect of those variables.
     
  12. The Guy

    The Guy Well-Known Member

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    The point you're making is essentially that statistics are less powerful with small sample sizes, which nobody would argue with.

    The point cbrad is making however is that Tannehill's recent performance can't yet be meaningfully distinguished statistically from his previous performance, which involves a large sample size.

    So whatever the causes of Tannehill's previous performance -- including his ability level, his surroundings, his opponents, injuries, weather, etc. -- those causes can't be reliably ruled out as explanations for his current performance because his current performance can't yet be meaningfully distinguished statistically from his past performance.
     
  13. Fin D

    Fin D Sigh Club Member

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    I'm fairly certain you have told me that things like oline play is definitely a constant.

    It does remove it, effectively.

    It is yet another way of saying all those things are constant and therefore don't matter, which removes them from the equation.
     
  14. Fin D

    Fin D Sigh Club Member

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    Except this isn't the only run he's had. In this one and all the others, there are things present, things a few off us said he needed before he got them. Then got them and had these runs.
     
  15. cbrad

    cbrad . Club Member

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    Nope, never. In fact I've repeatedly said OL is one of the hardest to measure aspects of football, probably second only to coaching.

    Nope.. it literally is the effect of all those variables. This distinction is important. A stat like passer rating fully incorporates the effect of everything that led to that stat, which includes all the variables you're referring to. However, passer rating does not allow you to infer how those variables affected it. It's the latter you're talking about, not the former. But the stat does NOT remove the effect of those variables.
     
  16. Fin D

    Fin D Sigh Club Member

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    Ok.

    You are effectively removing the specific variables that went into that specific passer rating.

    If you randomly compare Joe Whathistits against Bobby Whateverthehell and the game you randomly grabbed for Joe was his worst ever because he was injured playing in the terrible weather against the best defense in history and the random game you grabbed for Bobby was his best game ever in great weather during perfect health against the worst defense ever.....then what you've done by comparing them is completely ignore (or remove) opponent, health and weather as factors.
     
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  17. cbrad

    cbrad . Club Member

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    Yeah.. read the portion of my post you quoted again. Your example is showing that we cannot infer what the effects of those factors were just by looking at the passer ratings. But clearly those passer ratings incorporated those effects. The effects aren't being removed.

    This is a crucial distinction because it IS possible to remove effects from passer rating. For example, when I remove the effect of the defense based on average effect of points allowed on passer rating, that's literally removing the (average) effect of the defense from passer rating.
     
  18. Fin D

    Fin D Sigh Club Member

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    You are removing their importance. Again, look at the extreme hypothetical I used. By comparing those two passer ratings you are effectively removing the opponents, health and weather from the equation because are not making allowances for them. You are essentially saying they don;t matter so we will compare as if they aren't a factor because they aren't.
     
  19. cbrad

    cbrad . Club Member

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    Yes that phrasing is acceptable. So.. what has to happen then is to measure these other variables and see what the effect of removing them actually is (e.g., removing the effect of the defense). For some factors it's negligible, for others it's not.
     
  20. resnor

    resnor Derp Sherpa

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    Again there are 1,000s of unlikely events that can happen at any given point in a football game. When one happens, it doesn't make it any less unlikely.
     
  21. KeyFin

    KeyFin Well-Known Member

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    Dude, we all know that statistics will NEVER tell you more than a simple eye test for someone who knows what they're looking at. The statistics cBrad gives us are flawed because they don't have any context...it's just a standardized metric used for comparison. For instance, nowhere in his math does it tell you that Fitzpatrick has been running for his life the entire season, yet we grade him exactly as we grade Lamar Jackson or Aaron Rodgers because there's no better formula.

    To me, statistics have always been a starting point to form a conclusion....but they don't contain the actual story of whether or not those statistics are meaningful. For instance, Jimmy G and Tom Brady's teams are the two most dominant in 2019...yet ratings say Jimmy is the 10th most successful QB of the season and Brady is 21st. Is that factual? Yes. Is it accurate? No!

    The same goes for Matthew Stafford's Lions with a 3-8 record while Stafford is 6th overall this season. How does the 6th best QB only win 1 game more than a tanking Fitzpatrick squad with zero blocking or pass rush (PS, Fitz is 34th this season)? That's because the math doesn't look at any of the outside variables...it's a linear calculation in a non-linear game. And if it can't tell us with a reason of certainty the one true stat that matters (winning), then why are we arguing about it at all?

    One more thing for cBrad- the answer to your question about flipping a coin six times....the answer is 100%. I just flipped a quarter on my desk two rounds of six and both times, it was 4 heads, 2 tails (T, H, H, H, H, T and H, T, T, H, H, H). You'll come back to me and say that's not enough flips to be significant, just like you're saying that Tannehill needs to play more games to see if he's actually trending upwards.

    The part you're missing though is that he's already trended upwards by winning 4 of 5. That's what actually matters in the NFL...the end result is infinitely more important than the "how".
     
  22. The_Dark_Knight

    The_Dark_Knight Defender of the Truth

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    Unbelievable...Tennessee is 5-1 since Tannehill became the starting quarterback and there’s all of this argument whether or not Tannehill is a good quarterback.

    Just admit it and be done...Tennessee is a much better team with Tannehill under center than they were with Mariotta
     
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  23. cbrad

    cbrad . Club Member

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    Which is more flawed? Objective data that removes context or subjective opinions based on imperfect memory and human biases. BOTH are flawed. Just don't single out statistics without talking about how flawed subjective opinions are. I mean.. there's no way most experts are accurate with their purported explanations of what they see when they disagree with each other!

    If you want to estimate how biased the coin is (how good a QB Tannehill is) then you look at long term trends not short term trends.

    Also.. if it's really the case that what matters to you is the end result, then in your case we can judge Tannehill on win% (that's what you're using) and whether he can take Tennessee to the playoffs. Tennessee is 6-5 right now, and 3 of their last 5 games include a game against the Colts (6-5) and two games against the Texans (7-4). So they're in the driver's seat. So no excuses later on please if they don't make it.

    btw.. passer rating is a better measure for QB ability than win% if you want fewer confounds with surrounding cast.
     
  24. Pauly

    Pauly Season Ticket Holder

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    Tannehill > Mariota does not mean Tannehill = good.

    The same way that just because the Jags have decided Foles > Minnishew does not mean Minnishew = bad.

    Saying that A is better than B only tells you about A and B, not about how good A and B are compared to C, D … Z. What passer rating compared to league averages can tell you is that Mariota was below average, but not bad and Tannehill has been good (so far). They have thrown a similar number of passes, but against different opponents.
     
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  25. KeyFin

    KeyFin Well-Known Member

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    They're both obviously flawed..but at least subjective opinions are based on personal evaluation of a fully body of work (IE, what actually happens on the field).

    A good example to me is astrology- scientists just found a black hole that's much bigger than their data believed could be possible....and for a kicker there's a planet orbiting it (which "should" be impossible). Now they'll have to re-write many different theories since they were obviously wrong....but the real problem here isn't the math itself. It's that they don't have the full formula to solve for "x" because they've never actually been to space and seen what a black hole actually is.

    To me, QB rating might be a good long-term prediction mechanism of whether or not a QB is successful, but what does that actually tell us that we wouldn't already know? I mean, did we need analytics to say Marino or Manning were good QB's?

    Here's a practical example- the top two QB's from each division after 11 weeks is Cousins (NFC) and Jackson (AFC). This is a fact after just a hair below 65% of the season has been played. Using that data, will it be a Minnesota/Baltimore Super Bowl? Will Jackson and Cousins still be the top rated QBs by week 17? Will Baltimore and Minnesota even win their division? Heck, will those two QB's win next week?

    You can't answer any of those questions...and this isn't a "data set" issue at all. You have over a dozen years of Brady data, for instance...will he win next week? Will NE win the Super Bowl? The stats can't provide us answers for many reasons, mainly because Brady is an infallible human that has good and bad days just like everyone else. But even if you could somehow guarantee that Brady plays the best game of his life tomorrow, that's not enough to say NE will definitely win.

    So again, what is QB rating actually telling us that we don't already know?

    I don't buy that either. Passer rating doesn't look at how meaningful any one stat is. I'l stick with Brady since that's the last example I used. He passed for 262 yards in last year's Super Bowl (a positive), yet he had zero TD's and 1 INT (both negatives). The reality is that he played terrible for the first 50 minutes of the game, had one solid drive at the end and he's a SB winning QB.

    Statistically, Tom played a lousy game despite being the slightly better of the two QB's. Yet in this instance, around 83% of his stats on the day are "garbage time" since (1) he couldn't move the ball and (2) the Rams couldn't either. All that matters in that win was the final drive...it was the only significant factor on the entire day for the offense. Statistics don't even begin to tell us the story there though because they're unbiased treating every snap the same.

    As I mentioned way earlier in this thread, Tannehill has been strip sacked in multiple games...which is a big deal. QB rating doesn't care and calls it a non-factor, even though we know from history that his strip sacks have in fact directly cost us games. Fourth-quarter comeback drives? It doesn't matter to passer rating...those are just basic catches the same as any other. There are dozens of reasons why passer rating is a meaningless statistic since even after the fact, we can easily see instances where important data is outright ignored (like a strip sack or a SB game-winning drive).

    You asked me to trust passer rating over win percentage so let's bring my reply full circle- which of the two accurately depicts New England's chances of a Super Bowl repeat? Will Baltimore win the AFC championship....or any of the 8 AFC quarterbacks rated higher than Brady this season? Because once the playoffs start, win percentage is absolute- you win or you go home. But even before that across the final weeks of the season, Tannehill's individual statistics really don't matter as long as the day ends in W's instead of L's. He could post a 150 rating or a 80 rating...it won't give us any additional answers UNLESS you're trying to prove he's just average with a little blip on the stats radar with above average performances.
     
  26. cbrad

    cbrad . Club Member

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    Astrology??

    You mean astronomy. Astrology and astronomy used to be linked together in most ancient societies – it was natural for people to look at the stars to try to find "meaning" – but today those fields are not in any way related to each other. One is a science (astronomy) concerned with what actually occurs while the other (astrology) is.. fiction basically.

    Besides, that report about black holes was total media sensationalism and isn't really an important discovery in science. The size of that black hole was only larger than predicted by models of stellar evolution, not theories of black holes. What is it? 70 times greater than the mass of our sun? There are supermassive black holes that are billions of times the mass of the sun. So no, theories about black holes don't need to be revised per se, they'll just need to revise their assumption about how that particular black hole came to be. For example, it might not be a single star that led to it but multiple ones, etc...

    In any case, don't think the media is a good source for information on science. It's anything but.

    First, z-scores allow you to compare across in eras in ways no human could, and you get results that maybe most don't expect like Steve Young being the most efficient QB in history or that Brees and Peyton have the highest wins added. Stats allow you to show that offense is on average about 5% more important for winning than defense across NFL history. You can use stats to show how to remove the effect of certain variables, like defense, etc... Stats allow you to estimate the relative importance of different aspects of the game on win%. Do I have to go on? I have years of results to show the utility of stats you don't get through just watching the game.

    In general, for long term trends stats > humans, while for small samples of games humans > stats.

    No one can answer those questions. I mean.. what's the point of comparing two approaches when neither works? Besides, there's hardly a successful bettor that doesn't use stats and relies only on what they see. Vegas definitely uses stats.

    Don't change the question. The question is which of passer rating on win% is a better measure of Tannehill as a QB. And the answer, resoundingly, is passer rating. As I said already it has far fewer confounds than win% does.
     
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  27. The Guy

    The Guy Well-Known Member

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    The "how" is actually more important, because teams can win relatively small numbers of games via variables that aren't stable in nature and aren't likely to be replicated over longer periods of time.

    If the Titans had won four of the last five games by having an astronomical turnover differential, for example, that wouldn't likely be replicated, and you could say they're doing it largely with smoke and mirrors. The 2018 Dolphins started the season 3-0 largely for that reason, and we know how that finished.

    The Patriots have a dynasty because the "how" for them has been a HoF quarterback, a typically stout pass defense, and perhaps the best head coach in history. Those are all stable and replicable variables, hence the dynasty.

    The question for Tannehill currently is whether what he's been doing is stable and replicable, or whether it represents "smoke and mirrors" in terms of his own individual play. He hasn't done it long enough yet to rule out the latter explanation. We can't say with certainty that it is smoke and mirrors so to speak, but we can't say it isn't with certainty, either.
     
  28. cbrad

    cbrad . Club Member

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    lol.. I think I'll be watching the Tennessee game tomorrow more than the Dolphins game.
     
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  29. resnor

    resnor Derp Sherpa

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    In the Ohio State have, we had an unlikely event happen on a possession... RuNning back fumbled the ball, and it bounced perfectly straight back up to him. It's unlikely for that to happen that way. But it did. And that stuff happens all the time.
     
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  30. The Guy

    The Guy Well-Known Member

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    Over the 358 NFL games played this year, the correlation between passer rating differential (your own team's passer rating minus the opposing team's passer rating) and point differential is 0.83.

    69% of the variance in point differential is associated with passer rating differential. That's the opposite of a meaningless statistic. That's a highly meaningful one.

    EDIT: Sorry, made a mistake on that. The number of games has been 178, and the correlation is 0.66. Still, however, a highly meaningful variable.
     
    Last edited: Nov 30, 2019
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  31. The Guy

    The Guy Well-Known Member

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    Again, the fact that unlikely things happen doesn't make them frequent, common, or typical.

    People with IQs of 160 (or conversely 40) are out there, and they certainly happen, but they aren't frequent, common, or typical.
     
  32. cbrad

    cbrad . Club Member

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    And it's 73.09% of the variance in win% explained across NFL history.
     
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  33. resnor

    resnor Derp Sherpa

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    Who is saying that it dues make then common? Again, if you have 1,000 possible unlikely events, and 10 of them happen during a game, that doesn't make those 10 any less unlikely. But that's the point. During every game any number of unlikely events happens, because you're dealing with a minimum of 22 different humans playing, and 4 or so humans reffing. Random bounces of the ball happen, doesn't make the occurrence any less reason or unlikely, but they still happen. That ball bouncing back to up to the running back is a great example of that. The vast majority of the time, that ball bounces crazily away.
     
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  34. resnor

    resnor Derp Sherpa

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    So what? That's as great a stat as John Madden proclaiming that the team with the most points wins.

    You're looking at a result of a result. First result is passer rating. That is a RESULT of all the passing plays in the game. The second result is subtracting the lesser result from the greater.

    Of course the team with the better passer rating wins the overwhelming majority of the time: a great offer rating is the result of a whole bunch of successful plays.
     
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  35. The Guy

    The Guy Well-Known Member

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    The post you quoted was a response to the point made by KeyFin that passer rating is meaningless. If as you're saying passer rating is just as meaningful as which team scores more points, certainly you're agreeing with me that it's highly meaningful.
     
  36. The Guy

    The Guy Well-Known Member

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    I think I'm missing the point. What is it?
     
  37. cbrad

    cbrad . Club Member

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    This all started from us responding to Fin D who said unlikely events happen quite frequently.

    IF taken in the context of random sampling from a single continuous distribution (which btw was the context provided by my post which was quoted) then that's by definition wrong. But if you're just saying the probability that at least one out of X unlikely events will occur is highly likely (for large enough X) then that's obviously true.

    So it's just a matter of precisely stating what one means. This debate really shouldn't be happening.
     
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  38. Fin D

    Fin D Sigh Club Member

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    Yeah, the following is an enigma wrapped in riddle.....
    Sigh.
     
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  39. cbrad

    cbrad . Club Member

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    Yeah I was done with this subject BEFORE the post where you said that. My last post on this subject (before just now) was post #685 and you said what you just quoted in post #686. So I'm not sure why you're addressing that to me.

    The post I was referring to was the original post you made, post #669 with this sentence:
    https://www.thephins.com/threads/titans-to-start-ryan-tannehill.94693/page-17#post-3227217
    Given my post you quoted there as well as the fact you referenced "randomly choosing from a continuous distribution" multiple times, I think it makes total sense that The Guy and I both interpreted your statement the way we did.

    Either way, clarification is sometimes necessary and I think we're all on the same page now.
     
  40. Fin D

    Fin D Sigh Club Member

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    So to recap, I'm responsible for others misinterpreting something I wrote AND for following where you started and stopped a discussion even while you're commiserating with a person who hadn't stop and started the same conversation at same time as you.......so that makes me responsible for how your posts and my posts are taken.

    As I said.......sigh.
     
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