1. This site uses cookies. By continuing to use this site, you are agreeing to our use of cookies. Learn More.

Titans to start Ryan Tannehill

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

  1. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    Top 10 in passer rating in a given year or during some stretch of play, which was precisely the stat people were referencing when saying he was playing at a "top 10 level". Tannehill never did that in Miami when the proper comparisons are made. In Tennessee, we'll see. Right now his stats are still consistent with a short streak of great play, but like I said if he continues this to year's end it will be statistically significant. I mean.. his current z-score is +1.7106 so he has a tremendous head start.
     
    Irishman and Pauly like this.
  2. Fin D

    Fin D Sigh Club Member

    72,252
    43,678
    113
    Nov 27, 2007
    You're finding the the range/variables/etc. to use that best fits your argument. There is no need to normalize the results versus QBs in different sections of a given season, unless you have a narrative to push. All that does, is effectively strip out the counter argument by erasing its importance too the stats. You are and have been ignoring known handicaps that Thill had to deal with beyond his control and outside of his abilities, that other QBs did NOT have to deal with, then wanting to normalize his numbers versus that. And as always, your approach is predicated on the notion that everything comes out in the wash and everyone has the same issues to deal with.

    When i say plays at Top 10 level, I am referring to that given stretch or period when had the things I said he needed versus the QBs in that same time frame.

    I ask you again, what are the ways/tools a QB can use deal with a poor oline?
     
    AGuyNamedAlex and resnor like this.
  3. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    No Fin-D it's the other way around. It's ONLY if you have an agenda to push that you would compare a "best consecutive 8 game stretch" to a full year's passer ratings, which is precisely what everyone else was doing. THAT is deliberately trying to mislead people with stats.

    The comparisons I'm making are the comparisons you'd want to make if you start with the data and infer a hypothesis from the data instead of the other way around. That is, you want to compare "like vs. like" by equating sample size, or if you can't equate them use a statistical test that takes into account the different sample sizes (which lead to different levels of uncertainty).

    Also, the reasons it's fine to compare "best N game stretches" during different portions of a season are: 1) random variation means that the "best N game stretch" could occur at any time, and 2) average passer rating by game number is nearly constant throughout the season (very minor differences). So the comparisons I'm making are what you want to make IF you want the data to speak for itself.

    Finally, the claim Tannehill had to deal with issues so much worse than other QB's had to deal with is pure speculation. You're using that kind of assumption (and that's all it is, an assumption) to try to reject proper statistical analysis.
     
    Pauly and The Guy like this.
  4. Fin D

    Fin D Sigh Club Member

    72,252
    43,678
    113
    Nov 27, 2007
    Yeah no.

    Saying he's playing at a top 10 level based on the other QBs that week is perfectly acceptable and common. ONLY YOU CBRAD, decides to construct some BS overly complicated measure so you never have to admit you've been wrong.

    It is not speculation. We know for a fact, that he wasn't;t allowed to break the pocket or call audibles for huge portions of his Miami career. We know for a fact, Lazor called long developing pass plays with a crap oline. We know for a fact Sherman had Thill yell go or go go depending on pass or run. We know for a fact, most of his career in Miami the OCs called very little running plays relative tot he rest of the league. We also know the QBs you want to cherry pick time frames of DID NOT have to deal with those issues. This all happened and for you to keep denying these things and then pushing your own speculation that his situation was no different than anyone else's is absurd...no matter how many times you find a way to try (and fail) and justify it.

    And yes, i know you'll make another post full of reaches then tell me you're not discussing it with me anymore all while completely ignoring that you once again, engaged me.
     
    resnor likes this.
  5. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    It's not "perfectly acceptable" even if it's common. You won't get anything published in a scientific journal if you present a statistic without a measure of its uncertainty, and that's precisely what's missing when people deliberately ignore sample size. And even if you think what I'm doing is BS, it's not. What I'm doing is called proper statistical methodology, which you neither understand nor respect.

    None of that implies Tannehill had it worse than any other QB. I'm about to go and have Thanksgiving dinner with a bunch of Redskins, Vikings and Ravens fans. I can guarantee you the degree to which those Redskins fans think their OL is the worst, their team has way too many holes for any QB to succeed, exceed by FAR anything you hear from Dolphins fans.

    And Vikings fans are just expecting the worst come playoff time. It's like they expect a miracle play to occur that causes them to lose.

    So personally, I think all these opinions you and others have about how bad Tannehill had it relative to the rest of the league are because you don't pay anywhere near as much attention to the rest of the league. So no the facts you list (most of which I'm not denying btw) aren't at all evidence Tannehill had it worse than anyone else.

    You're wrong about the first part: I haven't made any post with "reaches" about Tannehill. What I'm posting is data driven analysis, not hypothesis driven analysis. But you're right about the second part. You're back to acting like proper statistical methodology is crap even when you don't have any clue about it. So yes it's time to end this discussion until the next time, and I'll let you end it. And no I don't mind engaging you until you start with that crap about proper statistical methodology being crap.
     
  6. Fin-O

    Fin-O Initiated Club Member

    9,937
    9,354
    113
    Sep 28, 2015
    LOL.

    Sooooo many memories.

    Why not just put your pitchforks down and compromise?

    When Ryan has had protection and a running game? He is good. Like good slightly beyond game manager.

    When Ryan's passing is the focal point of an offense? He has been bad. Not horrendous, just not good enough.

    Really is that simple, happy Turkey Day team!!
     
    Bumrush and KeyFin like this.
  7. Fin-O

    Fin-O Initiated Club Member

    9,937
    9,354
    113
    Sep 28, 2015

    :jt0323::jt0323:
     
    cbrad likes this.
  8. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    Just an update: the Redskins fans here are saying there’s a good chance they will NOT take a QB with their first pick.. owner apparently likes the QB and they knew going in that he was raw.

    Good news for those of us wanting a QB.

    It’s actually hilarious here. One Redskins fan is incessantly trying to convince a 1 year old that he HAS to become a Redskins fan lol.
     
  9. Pauly

    Pauly Season Ticket Holder

    3,172
    3,109
    113
    Nov 29, 2007
    I have to agree with cbrad. Whatever test you want to apply:- season rating, career rating, best N games, games against “top” defenses, rating when under pressure - it has to applied equally to all QBs. Then it is only meaningful if a sufficient number of QBs generate enough data for it to be significant.

    It is fair to say that Tannehill has the potential to be a top 10 QB and has played for large stretches at top 10 level. It is not fair to say he has been a top 10 QB.
    It is fair to say he has been held back by poor coaching/FO, and that with optimum coaching/FO he would do better. It is also fair to say that at least 26 QBs can make the same argument (Tom Brady, Lamar Jackson, Pat Mahomes and Drew Brees are the 4 I would definitely say you can’t make that argument for). For example Seahawks fans have complained for years about Russel Wilson being held back by the FO neglecting the OL and WR positions. What is not fair to say is that if all QBs got optimum coaching/FO that Tannehill would definitely be top 10.
     
    Irishman, cbrad and The Guy like this.
  10. Fin D

    Fin D Sigh Club Member

    72,252
    43,678
    113
    Nov 27, 2007
    If Thill puts up Top 10 numbers in given week, then he is being compared to all other QBs that week.

    If during one game, Thill put up 120ish rating with only two other QBs putting ratings that high, according to you and Cbrad I cannot say Thill played like a Top 3 QB that week, because first you'd have to take the BEST week of all the other QBs throughout the year first. That would be absurd and unnecessary.

    And again, if you agree with what you wrote that I bolded, then you DO NOT AGREE with Cbrad, but agree with me. Here's what I said that he started in on:

    There is nothing wrong with what i said and nothing that required him to redefine what Top 10 means.
     
    Last edited: Nov 28, 2019
    resnor likes this.
  11. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    The problem with the discussion above is that we aren’t reliably measuring the degree to which quarterbacks across the league are helped or harmed by their surroundings. Consequently there can be wild speculation about any quarterback in that regard.
     
  12. resnor

    resnor Derp Sherpa

    13,340
    7,553
    113
    Nov 25, 2007
    New Hampshire
    But your solution is to ignore it and act like every QB has it the same.
     
    Hoops, KeyFin, Fin D and 1 other person like this.
  13. Fin D

    Fin D Sigh Club Member

    72,252
    43,678
    113
    Nov 27, 2007
    Name a Top 10 QB that has a ****ty oline, not allowed to audible, team is in the bottom 5 in run plays called and was told not to break the pocket.
     
    Tin Indian and resnor like this.
  14. Fin-O

    Fin-O Initiated Club Member

    9,937
    9,354
    113
    Sep 28, 2015

    That honestly was only for the less than 2 seasons we had Bill Lazor, he wasn't allowed to change the formation but WAS allowed to change the play from what we've heard.

    The told not to break the pocket is likely hyperbolic as well, no coach would say "no matter what, don't leave the pocket"....even a goof like Philbin.

    The other two points however are hard to argue against.

    We should all be happy for Ryan, he is a fantastic situation and I've enjoyed watching him thrive.
     
    Irishman likes this.
  15. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    No, my response to that is to point out that the better quarterbacks in the league vary in their performance from year to year at a level significantly higher than the worse ones, which suggests that variation in quarterbacks' surroundings is a less powerful variable than quarterbacks' individual ability.
     
  16. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    The task should be to determine the degree to which the average QB was helped or harmed by his surroundings and to determine the degree to which Tannehill deviated from that average, not to determine whether there was a QB who experienced surroundings identical to Tannehill's.
     
  17. Fin D

    Fin D Sigh Club Member

    72,252
    43,678
    113
    Nov 27, 2007
    I keep asking people and no one ever actually answers.......

    What are the ways/tools a QB can use to counter the pass rush?

    But to your point....its not 0. If it's not zero, then it is some percentage. If it was as low as 5%, what would Thill's stats look like with players and coaches better than Brian Hartline, Legeduu Nanee & Mike Sherman?
     
    resnor likes this.
  18. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    That's only true if all surrounding variables truly "average out" over the time period you're looking at.

    Remember when I looked at the change in win% over 5 year periods (for each team) and found that the standard deviation in win% was about half of what you'd expect if team strength was random from year to year? That affects calculations of statistical significance.

    For example, a t-test shows that the probability Wilson's and Tannehill's game-by-game adjusted ratings "come from the same QB" is a ridiculously tiny 0.095%, clearly less than the 5% generally used to claim statistical significance. However, if we assume that half of the difference in their adjusted ratings is due to their surroundings, we'd have to remove ~6.3 passer rating points from Wilson's ratings and the t-test now gives you a probability of 9.5% that the two sets of adjusted ratings come from the same QB, which is no longer statistically significant (and btw it's total coincidence that the stat went from 0.095% to 9.5% and was 100x larger: it's actually 0.0951 and 9.53).

    Not saying that represents reality. Just pointing out that once you assume "partial" averaging out we're back to where we started: we can't use the stats available to determine what percentage of QB performance is due to the surroundings. Or at least I don't yet see how to do that.
     
    Last edited: Nov 29, 2019
    The Guy, AGuyNamedAlex and Pauly like this.
  19. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    You don't think the problem you outlined above is addressed by comparing multiple QBs over many years?

    For example, compare the passer ratings of the group comprised of Peyton Manning, Tom Brady, Drew Brees, Aaron Rodgers, and Russell Wilson, to the group comprised of Ryan Tannehill, Andy Dalton, Cam Newton, Joe Flacco, and Eli Manning, over the seven seasons from 2012 to 2018.

    If the passer ratings of the former group vary at a significantly higher level than those of the latter group, despite the year-to-year variation in passer ratings for all of them, what should the conclusion be?

    Surely we can't reasonably conclude that the former group's passer ratings are significantly higher because they enjoyed significantly better surroundings than the latter group over the entirety of that seven-year period.
     
  20. AGuyNamedAlex

    AGuyNamedAlex Well-Known Member

    1,727
    1,504
    113
    Sep 12, 2015
    I dont think anyone is arguing that a guy can be elite just due to surroundings.

    Just that QB's of a similar talent level with perform better/worse depending how their teams are tailored to thei talent.
     
    resnor and The Guy like this.
  21. Vertical Limit

    Vertical Limit Senior Member

    10,629
    3,728
    113
    Nov 25, 2007
    Another guy we dont talk about much that is suddenly having success is Jordan Phillips.. 7.5 sacks at his position puts him at 2nd in the league.. he turned his career around..
     
    Bumrush, Fin-O and The Guy like this.
  22. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    Sure, and that's true for all QBs, and then the questions become: 1) how likely are the surroundings to be optimized in that way for any QB, and 2) to what degree will that optimization enhance a QB's performance?
     
  23. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    Buffalo is doing it largely with smoke and mirrors, having for example the weakest strength of schedule in the league this year, but they're also surrendering an opposing passer rating of 78.5, which is fourth in the league and to which Phillips is likely contributing to significantly.
     
  24. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    First thing is to remember what the question is. The question is whether we can estimate the relative influence of the QB vs. the QB's surroundings on QB performance, in particular to determine which one is larger even if we can't quantify either.

    So for purposes of this discussion we need to look at variance in game-by-game passer ratings, not year-by-year ratings because year-by-year ratings already average out a lot of the effect of the surroundings – an advantage if your goal is to estimate QB ability, but a disadvantage if your goal is to estimate the effect of the surroundings. Variance in game-by-game ratings is determined by variance in QB ability, variance in the QB's teammates' abilities, and variance in opponent players' abilities (which is larger than for the QB's teammates because the opponent changes).

    Once adjusted to a common year (2019), Tannehill's average game-by-game rating (literally the average across games, which is different than a passing attempt weighted career average rating) is 91.62 with a standard deviation of 26.76, while Wilson's average is 104.24 with a standard deviation of 28 (league average is 91). Note how large those standard deviations are. The difference in means is 12.6 yet the standard deviations are more than twice that!

    To make the argument you're making you'd have to show that the influence of the QB multiplied by variation in QB ability is larger than the total influence of the QB's surrounding cast and opponent multiplied by their variation in abilities. It's hard to say which is larger because the influence of the QB on passer rating is huge – the QB is the only constant in that formula – but the QB is also only one person! And variances add (mathematically). So the variations in ability for each of the other players add.

    What you are trying to do is compare year-by-year ratings which already wash out tons of variation in the surroundings. Naturally you do that and the main reason for the difference, with large sample size whether it's one QB or many, is that the QB was the main difference. But that's not the right stat to answer the question of which has more influence.
     
    Last edited: Nov 29, 2019
    Irishman and The Guy like this.
  25. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    But the quarterback's surroundings don't typically change significantly on a game-by-game basis, whereas they can on a year-by-year basis (through player acquisitions and losses, coaching changes, etc.).

    Note for example the huge increase in Tom Brady's season passer rating in 2007, presumably as a function of the receiving trio of Randy Moss, Wes Welker, and Donte Stallworth. His passer rating probably didn't vary from game to game any more that season than it has from game to game in any other season of his career, but I suspect it varied from game to game at a level significantly higher that year than it has in any other year of his career.

    So if it's true that a QB's performance is determined more by his surroundings than by his own ability (or vice-versa), shouldn't a year-by-year comparison, across multiple QBs and teams, provide the best test of that hypothesis?

    There's nothing inherently stopping us from finding elevated standard deviations analogous to the ones you pointed out above, but on a within-group basis in the comparison I outlined in the post you quoted. Whether those would outweigh the between-group variation would be the question.
     
  26. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    I agree with you that a QB's surroundings are likely to change more across years than within each year, but given that the passer rating formula keeps the QB constant, any within-year variation in surrounding cast is being ignored if you just look at across-year variation. In particular, you're ignoring the effect of within-season injuries and all the variation in ability from game to game of the other players (and there are many more of them!). So ignoring game-by-game variation is artificially making the QB more important than he actually is.

    Also.. to address the issue about looking at multiple QB's, the similarity in surrounding cast for a given QB decreases as a function of time so you'd actually be better off looking at N consecutive years for a single QB than N different years for N different QB's, or N/K sets of K consecutive years for N/K QB's because you'd have more data on games farther apart in time.

    The data you really want is how that QB plays when he changes teams. For example, if you do an ANOVA on Fitzpatrick's adjusted ratings with the 6 different teams he's been on previous to Miami with 300+ passing attempts you see no significant difference:
    [​IMG]
    This year in Miami might be the lone statistically significant season once it's over. That's the kind of data, at least for one QB, that suggests the QB may be the more influential component. But again this is just one QB.

    Also.. while you're right that some of Brady's years are significantly different than the others (p-value is less than 0.05), note how similar many of the years are (the blue "box" indicates the middle 25-75% range of adjusted ratings in that year):
    [​IMG]

    I mean.. there's hardly any real difference from 2003-2006 for example (red line is median). So it wouldn't surprise me if within-year variance in surrounding cast during those years was actually larger than across-year variance. But there's no way to really know because all this is confounded by variance introduced by opponent strength.

    Anyway.. best not to artificially remove sources of variance, especially if it biases the results. So I'd stick with game-by-game ratings.
     
    Irishman likes this.
  27. Phins_to_Win

    Phins_to_Win Well-Known Member

    318
    455
    63
    Nov 16, 2013
    So something else to consider (or at least another way to look at it) is what was the most likely outcome from Tannehill using the assumption that he is an average QB ( or slightly less then average for a few posters on this forum).

    So we have a QB that is coming in cold against teams in midseason form, who did not get an offseason with the A team or practices with the A team right up to the week he became the starter.

    The highest percentage outcomes up to Cbrads 120 passes would easily be as follows:

    1st Slightly below average play as he gets accustomed to the new environment.
    2nd Average play across the board
    3rd slightly above average play
    4th bad play, clear signs of struggling
    5th good play, looks competent
    6th horrible play, disasterous outcome
    7th Amazing play looks like a legit top 5 QB

    I think its pretty clear that it becomes considerably less likely with each step down the chart. number 7 should be practically impossible, in the .001 to .0001 percentage range. In perfect conditions it would be nearly impossible to hit 7th option, and I don't think you can point to anything about Tannehills conditions that are "perfect", and yet here we are and he is clearly up to this point playing in the 7th option category.

    So you really have 2 choices right now. You can stick by the notion that we just saw the lottery get won by the 1 guy we ran out of here with pitch forks.... or we have to re-evaluate our original hypothesis that he is in fact JUST an average QB.
     
    resnor likes this.
  28. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    Yeah, this is another good example of where statistical analysis matters. People don't have good intuitions about what the probability of a series of events is given past data. Here's the comparable graph to that for Brady in my post above:
    [​IMG]
    The p-value here is 0.2557 which is still well above 0.05 meaning it's not yet statistically significant, and that's precisely because he's only played 6 games. If that graph is exactly the same at year's end with 11 games I guarantee you that p-value is well less than 0.05 and we will definitely have to adjust our assumptions about Tannehill. Specifically, we'll know with certainty he can play at an elite level (if this continues) with proper surrounding cast over 11 games, which was not statistically likely by any stretch before.

    btw.. 0.2557 means 25.57% likely Tannehill's ratings in 2019 can be explained by random variation alone (ignoring factors we don't know how to adjust for like starting for a new team midseason etc..). So you can see just how far off your intuition about probabilities is.

    With Tannehill's 155.8 rating in his last game he now has his best 6 game streak in his career, but before that there were multiple 5-game streaks that were comparable, so it's not anywhere near as unlikely as you think it is. Anyway, like I've said many times before, let's let this play out. If he keeps this up, the stats will show it.

    Oh.. btw, the threshold for passing attempts I use is 150 not 120 (and Tannehill does have more than 150 now).
     
  29. Phins_to_Win

    Phins_to_Win Well-Known Member

    318
    455
    63
    Nov 16, 2013
    Isn't that probability of him having a 5 game stretch like this vs having that exact 5 games from a given point? If he played the next 5 years, then I assume the likelihood he could have this 5 game stretch goes up, but to have him do it immediately after switching teams with no cherry picking (you HAVE TO USE his first 5 games as a Titan) it seems like the odds would go astronomically against you.

    So if you told me I was going to flip a coin 100 times and sometime in that 100 flips I'm going to get 5 heads in a row, I would say sure that's possible. But IF you told me the next time you flip the coin it will be 5 heads in a row, that becomes insanely more unlikely.
     
  30. Phins_to_Win

    Phins_to_Win Well-Known Member

    318
    455
    63
    Nov 16, 2013
    Also, while stating that there are things we can't adjust for, but those things clearly make a difference, how can you turn around and say my probability is far off? If there is no way to capture the variance then that means there is a clear X factor, and that means that ANY statistical attempt to give a % will be wrong. In fact the only thing we can be sure of from a statistics stand point is that the answer from the math will be wrong (or incomplete if you prefer).
     
  31. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    That's a good question actually.

    Most statistical analysis for continuous data (ratings aren't ordinal.. they can be any number from 0 to 158.3 for passer rating), for better or for worse, ignores ordering with sets. That is, the assumptions of ANOVA (and of the t-test which I also use) include independence of observations which means that the probability of observing one rating doesn't affect the probability of observing any other rating.

    In other words, that test doesn't know about the ordering of ratings within a season. It knows about "sets" but not "ordered sets" (a set where you care about the ordering of the elements in the set), which means it doesn't know about "streaks" per se. It can calculate the probability of what to you and me looks like a "streak" but to the test itself it's not a streak at all, just a set of ratings whose ordering doesn't matter. So from that test's perspective the starting point is irrelevant because all it cares about is the set of ratings observed. So ANOVA is just comparing multiple sets of ratings with no "streaks" in them (you can randomize the rating orders and get the same result).

    The problem with creating a statistical test for passer rating "streaks" where starting point matters is that the ratings are not ordinal. That is, they're not restricted to a finite set of ratings such as integers from 0 to 5 (in this case only 6 possible ratings). If we restricted the set of possibilities like that, then you can start calculating the probability of different streaks starting at different points. But for data defined on a continuous axis that's really difficult and there really aren't statistical tests I know of that deal with that.

    We're talking about going from 25.57% to 0.001%. It's untenable to suggest probabilities will change by that much just because you change teams and conditions. This isn't a 5% or 10% change we're talking about.. it's a 25,000 fold change in probabilities lol.
     
    Last edited: Nov 29, 2019
  32. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    I'm not sure I see that when presumably those factors would be represented in the season passer rating. Why would game-to-game variability of the surrounding cast be more important than the overall performance of the surrounding cast throughout the season?
     
  33. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    For estimating the effect of surrounding cast? Suppose you have two different seasons A and B, and both are statistically similar. In other words, season ending passer rating washes out all game-by-game variability in both seasons. However, in season A let's suppose injuries took a toll in the first half of the season while in season B it was the second half. Season ending ratings can't see the effect of those injuries on QB performance while game-by-game ratings would.

    Extreme example of course but that shows how you could underestimate the importance of surrounding cast by ignoring game-by-game ratings. In general, the more variability you remove from everything that is NOT kept constant (and the QB is the only thing required to remain constant in the formula) the more you'll bias the data towards showing that what remains constant is more influential.

    Also.. just so it's clear, we're not removing the effect of different seasons here. That's still in the game-by-game ratings. So it's really a case of retaining information vs. removing it.
     
    Last edited: Nov 29, 2019
  34. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    You could say the same thing however about Andy Dalton's 16 games in 2015, where he posted a passer rating about 18 points above his career number. What was the likelihood Andy Dalton would have a passer rating of 106.2 in 2015, when his highest season passer rating before that had been 88.8, and he'd had other seasons of only 80.4, 87.4, and 83.5?
     
  35. The Guy

    The Guy Well-Known Member

    1,728
    860
    113
    Oct 1, 2018
    So then how would we explain the fact that the passer ratings for the group of P. Manning, Rodgers, Wilson, Brees, and Brady vary at a level significantly higher than that for the group of Tannehill, Dalton, Flacco, Newton, and E. Manning, over many years? Is there an explanation for that finding that illustrates the need for a game-by-game analysis rather than a season-by-season one?
     
  36. Phins_to_Win

    Phins_to_Win Well-Known Member

    318
    455
    63
    Nov 16, 2013
    Ok so let me see if I can blow your mind on this. you say that its all random then from that perspective it was equally likely (actually more likely but lets get into that some other time) that he would have started out his 5 game hot streak on the 2nd game, meaning it turned into just 4 games, it was also equally likely that he would have started randomly on his 3rd game meaning it turned into only 3 games, and equally likely that he started it on the 4th game and 5th. Each of these possibilities gets 25%, so what we have is 125% that Tannehill was going to have an amazing Game for his first game??? Mathematically impossible to have any other outcome. Not bad for an average QB...
     
  37. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    In practice I don't think you'll see too many differences if your only goal is to argue the QB was a major reason for the observed differences, though sample size will naturally be larger with game-by-game ratings so that's a plus.

    But that's not the question here. The question is what data would you use to try and infer whether the QB or his surroundings is more influential, and for that question you definitely don't want to remove sources of variance that matter. Regardless.. I don't think this question can be answered with the stats we have, so from that perspective it's irrelevant which data you use.. we just don't know.
     
    Irishman and The Guy like this.
  38. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    Well.. you blew my mind alright. Not sure I've seen so many errors in a single post.

    Like I just said, from the statistical test's point of view there is no such thing as a "streak". There is only a set of data. You can reorder the ratings in each set (season) any way you want it's the same from that test's point of view. And obviously a 5-game streak in a 6 game period can't begin from game 3. So the probability of that isn't 25% it's 0%.

    Point is.. when you look at the sets of ratings from different years (regardless of ordering within the sets) what Tannehill has done so far is still consistent with random variation. As I said though, it won't be if he continues performing this way.
     
    Irishman likes this.
  39. Phins_to_Win

    Phins_to_Win Well-Known Member

    318
    455
    63
    Nov 16, 2013
    If the start of a five game streak is based on randomness, then it is equally likely that the start of a 4 game 3 game 2 game and 1 game streak starts on that same game. My point was there is no way its 25% cause it doesn't stand to reason that the much easier 4 game 3 game 2 game and 1 game has a less % chance. Giving it the same % chance makes it impossible to have a failed game 1. so I don't think the 25% can be anywhere near possible in being correct for the 5 game winning streak.
     
  40. cbrad

    cbrad . Club Member

    7,516
    8,905
    113
    Dec 21, 2014
    You're not getting it. Take the ratings Tannehill has had so far in 6 games with the Titans: 78.1, 120.1, 109.8, 82.3, 133.9, 155.8.

    Now.. that's the actual order of the ratings. To you that looks like the 5 game "streak" started on game #2. Now suppose you randomly reorder those SAME ratings. For example: 109.8, 82.3, 155.8, 78.1, 120.1, 133.9. What does it look like to you now? That it was a 6-game "streak"? I don't know.. doesn't matter. To the statistical test the ordering is irrelevant and there is NO streak. There is no "5 game streak", there is no "6 game streak", there is simply NO streak.

    I used the word "streak" because others have used that and it usually helps with communication, but from the point of view of the statistical test there is NO streak. There are just sets of ratings (one for each season). So you can't start with the assumptions of the statistical test (the independence of observations assumption) and then say "suppose the streak started on game X". That's a meaningless assertion.
     
    Irishman likes this.

Share This Page