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

Ryan Tannehill

Discussion in 'Other NFL' started by bbqpitlover, Oct 16, 2019.

Ryan Tannehill is...

  1. A terrible QB

    0 vote(s)
    0.0%
  2. A below average QB

    4 vote(s)
    5.7%
  3. An average QB

    7 vote(s)
    10.0%
  4. An above average QB

    39 vote(s)
    55.7%
  5. An elite QB

    16 vote(s)
    22.9%
  6. The GOAT.

    4 vote(s)
    5.7%
  1. PhinFan1968

    PhinFan1968 To 2020, and BEYOND! Club Member

    You're gonna have to back that up with stats sir.
     
    Pauly, resnor and Silverphin like this.
  2. The_Dark_Knight

    The_Dark_Knight Defender of the Truth

    11,817
    10,321
    113
    Nov 24, 2007
    Rockledge, FL
    :sidelol:
     
    Silverphin likes this.
  3. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    I took another look at this and used teams' making the playoffs since 2004 as the dichotomous dependent variable and passer rating differential as the predictor. This is the graph for that, similar to the one you mentioned above:

    [​IMG]
    However when I replicate that process for the Super Bowl winners as the dichotomous dependent variable, I continue to get this graph:

    [​IMG]
     
  4. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    Right, just like I said in the post you quoted, for SB winners you have too few 1's (SB winners) and far too many zeros (non-SB winners) to have any confidence in the curve that's being fit. Look at the gray area (which I'm assuming is the 95% confidence region) in the SB winner curve.. it's massive! That means that any logistic function in that region could be the "true" curve => no reliability in the fit.

    The playoff graph is fine because you have enough 1's (12/32 playoff teams). And notice that it "looks" right too because 12/32 = 37.5% and you'd expect somewhat less than 37.5% of teams with PRD = 0 to make the playoffs, and that's what you see.

    Anyway, take home message here is that you have to report stats where the reliabilities are high enough for the argument you're making, and that's not the case with a logistic function fit to SB winners vs. all teams that didn't win the SB.
     
    The Guy likes this.
  5. Pauly

    Pauly Season Ticket Holder

    3,696
    3,743
    113
    Nov 29, 2007
    Why start in 2004?
    The only rationalization appears to be that it is a round number. The problem with this is that you are truncating the data, and whenever you truncate the data you run the risk of an anomaly changing the outcome.
    Dates that make sense for a cutoff dat, depending on what you are looking at.
    2011 - introduction of the rookie salary pool.
    2002 - the realignment into 4 divisions of 4 teams.
    1994 - introduction of the salary cap
    1978 - introduction of new passing rules that dramatically affected passing stats.
    1970 - AFL - NFL merger
     
    resnor and Fin D like this.
  6. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    I would defer to @cbrad on whether it was associated with a significant change in the nature of the passing game in the NFL (I think he may have actually generated those data at some point previously), but the rationale at least is this:
    https://www.espn.com/nfl/columns/story?columnist=pasquarelli_len&id=1771047
     
  7. Pauly

    Pauly Season Ticket Holder

    3,696
    3,743
    113
    Nov 29, 2007
    My understanding is that the rules change was evolutionary - a change in long term trends not revolutionary - a sudden change that clearly separates different periods.
     
  8. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    I did a t-test on average season passer rating in the league for the groups 1978 to 2003 (M = 75.6) and 2004 to 2019 (M = 85.7). That was significant -- p < 0.001.

    An ANOVA with three groups 1) 1978 to 1993 (M = 74), 2) 1994 to 2003 (M = 78.2), and 3) 2004 to 2019 (M = 85.7) was significant -- p < 0.001. Tukey and Scheffe post-hoc tests were significant among all three groups (highest p-value = 0.005).
     
  9. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    The change in passer rating is evolutionary since 1978, not change in passer rating differential. And you don't want to do a statistical test on passer rating itself – obviously due to passer rating inflation different periods are different which is why you need to adjust ratings – you want to do statistical tests on passer rating differential (since that's the question here).

    Most obvious things to look at to get some idea of how things have changed are the mean and standard deviations of the distributions across years. The mean is irrelevant here because mean passer rating differential is always around zero. Here's the standard deviation over time:
    [​IMG]

    That graph suggests that you probably won't see a major difference in most stats based on passer rating differential for different periods within 1978-2018, but that 1966-1977 might be different. In any case, no need to speculate here, we can do the calculations.

    Here the probabilities of making the playoffs for the specific periods you described:
    [​IMG]

    You can do statistical significance tests on these (and for anyone that wants to do that note that you have to modify the threshold for statistical significance because there are 6 tests being done simultaneously, so the thresholds is not 5%, it's 5/6 = 0.83%), and the two periods before the 1978 rule change are statistically significant relative to the league average (black line) but none of the other post-1978 periods are, though the 1994-2001 period is right on the borderline for statistical significance.

    Anyway, for future reference, the equation for that black line is:

    Playoff probability = 1/(1+e^(0.8746*PRD - 0.1187))

    So in summary, you can treat periods within 1978-2018 (I left out 2019 since we still have one game lol) as coming from the same distribution as long as you use passer rating differential. No need to adjust ratings as long as you take the differential.
     
    Pauly and The Guy like this.
  10. Pauly

    Pauly Season Ticket Holder

    3,696
    3,743
    113
    Nov 29, 2007
    Thanks so much for doing that cbrad.

    I expected all the post 1978 data to fit similar patterns. It was a little interesting to see the 2002-2010 mini-era being close to significantly different to the other eras.

    The basic take home message (as I understand it) is if we want to do analysis based on passer rating differential then there is no reason not to use the full data from 1978 onwards.
     
  11. Fin-O

    Fin-O Initiated Club Member

    11,375
    11,392
    113
    Sep 28, 2015
    Props to the extremists on both sides of this debate.

    I FULLy expected to log on and see “Ryan threw a pic, see he sucks” and a “see Ryan threw a TD, he’s the man!”

    And I saw neither.

    Keep it up guy’s, proud of ya’s.
     
    Pauly likes this.
  12. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    I would say it's just the opposite, actually -- that if we've achieved a significant result by using some subset of the passer rating differential data since 1978, there's no reason to use all the data, because the effect size is highly unlikely to change significantly.

    If for example the correlation between win percentage and passer rating differential from 2004 on is 0.81 (which it is), then the correlation between the same two variables from 1978 on is highly unlikely to be significantly different.
     
  13. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    Do you see a need to create an era cutoff based on a significant change in run-pass ratio in the league if the analysis is based on a passing game statistic, i.e., passer rating differential? We do know teams are passing the ball far more now than they were in the past.
     
  14. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    1994-2001 period you mean.. not sure what the explanation is, but the steeper that curve is the MORE passer rating differential matters, so the passing game was slightly (but not significantly) more important during 1994-2001 than any of the other periods you listed.

    And of course those pre-1978 periods show how little the passing game used to matter. It's not just the passing game, but also defense that mattered more up to 1977. That rule change in 1978 changed so much. Up to 1977 defense was on average more important than offense, but after 1978 that flipped and all that coincided with the massive increase in the importance of the passing game.

    Yeah, that's one take home message. The other is that IF you happen to not have all the data from 1978 then what you find from a decent sized subset of that period will most likely apply to the full post-1978 period. But yes, it's best to use the entire data.

    Yeah it's worth pointing out that just because passer rating differential from 1978 onwards doesn't need to be adjusted by era does NOT mean any other stat you're comparing it to doesn't need to be adjusted by era. Win% never needs to be adjusted, but technically playoff probabilities do need to be adjusted since 10 out of 28 in 1978 is different from 12 out of 32 today. However, the adjustment is so small it's not affecting how passer rating differential affects playoff probabilities (it might matter with other stats though). Run/pass ratio? I think that depends on context, but for most contexts I don't think it needs adjustment since it's a percent of total.

    As far as an era cutoff based on rushing percent, I wouldn't do it. I'd just use rushing percent as a predictor variable. Also, rush percent has gradually declined even since 1978 (green circles are playoff teams, blue = SB winner), so you'd probably not want a simple cut-off anyway:
    [​IMG]
     
    Last edited: Jan 26, 2020
    Pauly and The Guy like this.
  15. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    Heck the correlation (0.82) between passer rating differential and win percentage in 2018 alone is statistically significant, p < 0.001.
    OK appreciate that.
     
  16. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    Let's interpret that correctly though. All that means is that the true correlation is almost certainly not zero (less than 0.1% probability). It says nothing about whether you could use what you found in 2018 and apply it to 2017 or any other year. For that you actually need to do a t-test (actually Welch's test for unequal variances) given two different means and their estimated standard errors.

    In other words, something like what I did with those curves.
     
    Pauly and The Guy like this.
  17. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    Right but if what we're interested in is how the league is functioning at the present time, then shouldn't we make something of the fact that the 2018 correlation is what it is and is highly significant? And shouldn't that be even more relevant than what's gone on between 1978 and 2017?
     
  18. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    I had just posted the results of some more tests but then realized that the results already shown are sufficient. So deleting what I just posted lol.. let's just say that the curves shown earlier already show that the relation between passer rating differential and playoff probabilities (and also win% btw) is statistically the same in the 1978-2018 period, so picking one year from that is best thought of as "small sample size" as long as the relation is to win% or playoff probabilities. That's not necessarily true for any other relation until proven.
     
  19. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    In terms of the correlation between win percentage and passer rating differential (again 0.81), the 95% confidence interval for the sample from 2004 to 2018 (consisting of 480 team seasons) is 0.773 to 0.836. I can't imagine that confidence interval is going to narrow significantly by using the data from 1978 on, and in fact it may widen as we move back in time toward an era in which the league featured the run game far more than it has more recently.
     
  20. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    If you combine the data from 1978-2018 the correlation between win percentage and passer rating differential is 0.7939 with the 95% CI going from [0.7723, 0.8136] so it's slightly narrower than from 2004 to 2018. However, you do notice how large the confidence interval is for 2018 alone. It goes from [0.6635, 0.9099] which shows you why one year alone (e.g., 2018) isn't anywhere near as reliable.
     
    Pauly and The Guy like this.
  21. Finatik

    Finatik Season Ticket Holder Staff Member Club Member

    4,323
    4,012
    113
    May 2, 2014
    SO Cal
    This needs to now be moved to the Stats forum. If we had one.
     
    Sceeto likes this.
  22. Mcduffie81

    Mcduffie81 Wildcat Club Member

    6,053
    5,608
    113
    Mar 23, 2008
    Lake Worth, Fl.
    Yeah. You guys have ruined this thread with stats.
     
    Sceeto likes this.
  23. texanphinatic

    texanphinatic Senior Member

    11,881
    4,834
    113
    Nov 26, 2007
    Detroit Metro Area MI
    NERDS!
     
    Sceeto likes this.
  24. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    Once the SB is over, I'll start a statistical methods in football thread (Irishman's idea) and we can at least move statistical methodology discussions there. That won't remove statistical analysis from other threads, but it can move the discussion about methodological issues to that thread (and many of the "stats" posts here are of that kind), leaving mostly the results of the statistical analysis in the original thread, thus reducing the overall number of stats posts in the original thread. So that might help a bit.

    However, the real issue here is something else I've said previously: those posters wanting a different type of discussion need merely to post more themselves. I'm guessing each poster likes their own posts? lol.. But if you're not willing to do that, there's not much else others can or even should do other than to stop posting, which isn't going to happen. So post more yourself!
     
    FinFaninBuffalo and Irishman like this.
  25. Pauly

    Pauly Season Ticket Holder

    3,696
    3,743
    113
    Nov 29, 2007
    How do people analyze football/football players?

    Some people will say its all about film study and looking at players. Others will say it’s all about scheme and Xs and Os. Some people look at the stats. There are even some people who go on about how the team/player make them feel and whether or not they approve based on their social/political beliefs.

    At this point of the season we have run out of film and Xs and Os regarding Tannehill, well there was the pro-bowl performance but no one mentioned that. That leaves the only live subjects in the thread stats and how stats hurt your feelings (show me on this doll where the bad stat hurt you).

    I will always listen to someone who is more knowledgeable than me on a subject they have expertise in and I am interested in the subject matter. If it’s not a subject I’m interested in I’ll leave it alone.
     
    smahtaz and resnor like this.
  26. Sceeto

    Sceeto Well-Known Member

    13,501
    6,246
    113
    Oct 13, 2008
    New York
    Well then that's probably a good sign to put this thread to bed. Almost 200 pages. All good. Been there. done that. Goodnight.
     
    Irishman and Cashvillesent like this.
  27. smahtaz

    smahtaz Pimpin Ain't Easy

    I'd also like to know what affect coaching has on the player's performance.
     
    Irishman likes this.
  28. Fin-O

    Fin-O Initiated Club Member

    11,375
    11,392
    113
    Sep 28, 2015
    What do the numbers say for the total in the SB Sunday? Asking for a friend..
     
    Irishman likes this.
  29. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    Yeah.. predictions based on stats for any single game are HIGHLY unreliable, keep that in mind. Stats are good for predicting trends, not individual games, but there are nevertheless a few trends that are interesting to know about w.r.t. total points scored in the SB.

    We don't yet know who the winner and loser will be, but from 1970-2018 the correlation between the sum of regular season z-scores for both offense and defense (a measure of how much better both units together were than league average) and points scored for the SB loser is -0.0623 so basically zero. That means that regular season performance for whichever team is the loser doesn't help predict points scored by the loser and that the best estimate is the average points scored by the loser in the SB during that time, which is 16.7.

    So let's say the stats predict the loser will score 17 points.

    With the winner you do have some predictive power but not that much. The correlation between the sum of regular season z-scores for both offense and defense and points scored by the winner in the SB is much better at 0.3854 (still not that high though), and the best-fitting line to the data points is 3.8x + 21.35 where x is the sum of z-scores.

    If KC is the winner that gives you an estimated 29.51 points scored, while for SF it's 30.9. So the prediction would either be 30-17 if KC wins or 31-17 if SF wins. Tons of variations there if you look at the stats, but you get the idea: if the O/U is 54.5 the stats say Under wins.

    It's also interesting how similar z-score wise the two teams are. For KC the offense is at 1.2749 while the defense is at 0.8726 while for SF it's 1.69 for offense and 0.842 for defense. Very similar teams in terms of production.

    Anyway.. don't take the predictions too seriously since it's a single game prediction, but with the types of regular season stats these teams have, you'd expect the Under to win.
     
    Irishman and Fin-O like this.
  30. Fin-O

    Fin-O Initiated Club Member

    11,375
    11,392
    113
    Sep 28, 2015
    Interestingly enough, that is the top play of most "pro's". The Under...

    I'm going 31-27 Chiefs personally.
     
  31. Cashvillesent

    Cashvillesent A female Tannehill fan

    770
    641
    93
    Dec 8, 2019
    In got a call from someone earlier saying they’ve heard from someone that Gisele was spotted in Nashville, having flown on Wheels Up, which,’if you don’t know, is basically rideshare for private jet travel. And that there was talk she was joined by Tom Brady and they’re putting their kids into a private school down there. A quick Twitter search didn’t ping much beyond this, from a Nashville Post reporter:

    https://www.barstoolsports.com/blog...c8a3j7ppy_OiZdq7ChIX7vSKxGSm-LMLPMBnjLXMpnCc0

    Vrabel, and Tom Brady are good friends too..

    Also he posted this 10hrs ago in his twitter..



    But man, as much as I would love this to happen. I dont wanna get rid of Tannehill. :(
     
    Last edited: Jan 31, 2020
  32. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    There's good evidence that Brady's best days are behind him. 2019 was the first year he performed below average statistically... on a team with a great defense, the best coach in the NFL, and where he's won on average 12 games per season over 18 seasons and won 6 SB's (including in 2018). Not even as a rookie did he perform worse than average.

    So irrespective of Tannehill, the only reason I'd sign Brady is if you have a near-SB calibre roster (except at QB), need to win now and you currently have a below average QB. That's about it. Tennessee doesn't fit that mold.

    Brady's just one of the many great athletes that don't want to admit they're over the hill and keep playing after they should've stopped. Of course, Brady's accomplished so much it won't hurt his legacy (similar to Jordan playing with the Wizards not hurting his legacy), but there's no reason a team should be jaded by a great player who is past his prime.
     
    The_Dark_Knight likes this.
  33. Cashvillesent

    Cashvillesent A female Tannehill fan

    770
    641
    93
    Dec 8, 2019
    Dude Brady had no recieving core last year. Of course he sucked. Edelman was banged up all year and he had huge drops.
     
  34. The_Dark_Knight

    The_Dark_Knight Defender of the Truth

    11,817
    10,321
    113
    Nov 24, 2007
    Rockledge, FL
    There’s absolutely no reason to believe Tennessee would be better with Brady than they were this year with Tannehill
     
    Mcduffie81 and KeyFin like this.
  35. KeyFin

    KeyFin Well-Known Member

    10,488
    12,821
    113
    Nov 1, 2009
    Honestly, I would almost expect Tennessee the last place for Brady to land.
     
  36. The_Dark_Knight

    The_Dark_Knight Defender of the Truth

    11,817
    10,321
    113
    Nov 24, 2007
    Rockledge, FL
    I truly don’t understand the hype of where Brady will be next season. He’s going to be the same place he’s been for the last 20 years
     
  37. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    Brady's often had a less than stellar cast at WR. They won the SB in 2004 with Deion Branch, David Givens and David Patten at WR and Christian Fauria and Daniel Graham at TE. That's a SB winning WR corps!! Brady of the past wouldn't have performed below average with the WR corps he had in 2019 given all the other advantages he's enjoyed (esp: elite defense! and still below average??).

    Besides, that Titans playoffs game should have made it clear even without stats: Brady's not who he once was.
     
  38. resnor

    resnor Derp Sherpa

    16,329
    9,874
    113
    Nov 25, 2007
    New Hampshire
    And it was defense and special teams that won the Super Bowl.
     
  39. The Guy

    The Guy Well-Known Member

    6,598
    3,323
    113
    Oct 1, 2018
    This gets at exactly one of the points I've made here ad nauseam: the better QBs vary in their performance at a level higher than that of the worse QBs. Give Brady (or at least "the old Brady") a poor receiving corps and he'll do better than Andy Dalton would with the same corps. Likewise, give Andy Dalton Randy Moss, Donte Stallworth, and Wes Welker (i.e., Tom Brady circa 2007), and he won't perform nearly as well as Brady did with those receivers.

    There is both the individual ability of the QB and the ability of the surrounding cast, and those variables interact. It isn't either one of them that's completely responsible for what we see.
     
  40. cbrad

    cbrad .

    10,659
    12,657
    113
    Dec 21, 2014
    What did special teams do? This is the 2005 SB (2004 season) we're talking about:
    https://www.pro-football-reference.com/boxscores/200502060nwe.htm

    I can't remember that SB, but going through the play-by-play it looks like it was somewhat even in terms of how much defense and offense mattered, though I wouldn't have an issue with someone saying defense was slightly more important. But special teams??
     

Share This Page