2022 Best Case Scenario for Tua

One thing in Tua’s favour is the fact that most his offensive teammates are young.

Nearly all of the Olinemen have been drafted in the last two years. Waddle is a rookie, Ahmed is 23, Gaskin is 24. Even Gesicki, at 26 is only now coming into his prime. I know neither of these RBs is of the quality that a franchise needs to reach the top, but they do a job for the team.

Of course, Tua reaching his potential depends on those around him doing the same, especially the OLine, but I do think it’s possible.

"Galant wrote:

As mentioned above, if you click the Tweet and read the thread the point isn't to say that Tua is a great passer or deep-ball passer but to try to look at what he can do, what he has shown as a skill, and in that particular case, when he has thrown the deep ball he has been very accurate with it.

It's not so much a matter of saying whether or not Tua is great and has proven himself great, but rather to identify what Tua can do well and consider that.

What Tua does well is he knows his limitations and doesn't take many chances. His downfield passes were really not accurate, it's just that he only threw downfield when a receiver was wide open.

Throughout the season there were a few looks at what Tua had been doing well, particularly during that strong run.
Does anyone know a good place to gather some of those stats for the full season and perhaps compare from his first season?

For example:

Tua Tagovailoa Is Playing Well, Which Is A Real Inconvenience If You’re The Dolphins | FiveThirtyEight

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"But there’s plenty of room for growth. Though he’s been very accurate with his throws (especially late in the game), he’s also been extremely conservative. He’s averaging just 7.02 air yards per attempt this season, ranked 30th — and despite not throwing it very far downfield, he’s as prone to interceptions as you would expect for a quarterback who’s played in only 17 professional football games. Six picks against nine touchdowns gives him a TD-to-INT ratio of 1.5. That’s tied with Matt Ryan for 24th in the league and is just barely ahead of Jared Goff, Daniel Jones and Brissett.

To keep himself on the field, Tagovailoa will have to add more explosive plays to his game (like the 65-yarder to Hollins) while subtracting mistakes (like the first-quarter interception). But he already has demonstrated the accuracy, decision-making and clutch instincts of an above-average NFL starter."

Tua can throw the ball downfield. His problem is velocity. If your receivers aren't getting enough seperation it just won't work with downfield passes. He has a quick release but if you don't have time to plant your feet that doesn't matter. Get some oline help and we will see what happens.

"Galant wrote:

Tua Tagovailoa Is Playing Well, Which Is A Real Inconvenience If You’re The Dolphins | FiveThirtyEight

That huge difference between Q1-Q3 and Q4 is mostly due to small sample size. The article is from Nov 24th, so maybe Tua had only ~50 passing attempts in the 4th quarter (out of 203 total) at that point? Need closer to 150 before passer rating becomes more reliable.

Anyway, in 2021 Tua's passer rating for Q1-Q3 ended up being 89 after 290 passing attempts, and for Q4 it was 93.2 after 98 passing attempts. Attempts in Q4 is still a bit low, but you can see that the difference is now only 4.2 points instead of 18.4.

Next Gen Stats - https://nextgenstats.nfl.com/stats/passing

Avg Time to Throw
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Avg Comp. Air Yds
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Avg. Intended Air Yds
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Avg. Air Yds Differential
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Aggressiveness:
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Longest Completed Air Distance:
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Air Yds to the Sticks:
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Passing Attempts:
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Passer Rating:
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Passing Stats
Time To Throw (TT)
Time to Throw measures the average amount of time elapsed from the time of snap to throw on every pass attempt for a passer (sacks excluded).

Average Completed Air Yards (CAY) and Average Intended Air Yards (IAY)
Air Yards is the vertical yards on a pass attempt at the moment the ball is caught in relation to the line of scrimmage. CAY shows the average Air Yards a passer throws on completions, and IAY shows the average Air Yards a passer throws on all attempts. This metric shows how far the ball is being thrown ‘downfield’. Air Yards is recorded as a negative value when the pass is behind the Line of Scrimmage. Additionally Air Yards is calculated into the back of the end zone to better evaluate the true depth of the pass.

Average Air Yards Differential (AYD)
Air Yards Differential is calculated by subtracting the passer’s average Intended Air Yards from his average Completed Air Yards. This stat indicates if he is on average attempting deep passes than he on average completes.

Longest Completed Air Distance (LCAD)
Air Distance is the amount of yards the ball has traveled on a pass, from the point of release to the point of reception (as the crow flies). Unlike Air Yards, Air Distance measures the actual distance the passer throws the ball.

Aggressiveness (AGG%)
Aggressiveness tracks the amount of passing attempts a quarterback makes that are into tight coverage, where there is a defender within 1 yard or less of the receiver at the time of completion or incompletion. AGG is shown as a % of attempts into tight windows over all passing attempts.

Air Yards to the Sticks (AYTS)
Air Yards to the Sticks shows the amount of Air Yards ahead or behind the first down marker on all attempts for a passer. The metric indicates if the passer is attempting his passes past the 1st down marker, or if he is relying on his skill position players to make yards after catch.

Completion Probability
The probability of a pass completion, based on numerous factors such as receiver separation from the nearest defender, where the receiver is on the field, the separation the passer had at time of throw from the nearest pass rusher, and more.

Expected Completion Percentage (xCOMP)
Using a passer’s Completion Probability on every play, determine what a passer’s completion percentage is expected to be.

Completion Percentage Above Expectation (+/-)
A passer’s actual completion percentage compared to their Expected Completion Percentage.

Comp % -- Expected Comp % -- Comp % Above Expectation
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If you're searching for a stat that suggests what should be improved, look at average time between snap and either throwing the ball or being put under pressure. The league average there in 2021 was 2.41 seconds. The two QBs that had it the worst (among those with 150+ passing attempts) were Roethlisberger and Tua, both with ~2.2 seconds.

Thing is, the standard deviation is 0.0991, which means Roethlisberger and Tua are in that "statistically significant" category (i.e., more than 1.96 standard deviations above/below the mean), as in you can't just explain this away with random variation. It's the statistical equivalent of saying either pass protection was abnormally bad, or these QBs had abnormally fast release times. We know which it is.

"cbrad wrote:

If you're searching for a stat that suggests what should be improved, look at average time between snap and either throwing the ball or being put under pressure. The league average there in 2021 was 2.41 seconds. The two QBs that had it the worst (among those with 150+ passing attempts) were Roethlisberger and Tua, both with ~2.2 seconds.

Thing is, the standard deviation is 0.0991, which means Roethlisberger and Tua are in that "statistically significant" category (i.e., more than 1.96 standard deviations above/below the mean), as in you can't just explain this away with random variation. It's the statistical equivalent of saying either pass protection was abnormally bad, or these QBs had abnormally fast release times. We know which it is.

But do we know the correlation between time to throw and performance? We do know that when passes are thrown beyond three seconds after the snap, EPA on average is negative:

https://www.pff.com/news/nfl-the-perfect-timing-a-deeper-dive-into-time-to-throw-data

So that doesn't leave a whole lot of time between what's average throughout the league, in terms of time to throw, and when performance would be expected to drop off on average.

Pass Pro Stats - https://www.pro-football-reference.com/years/2021/advanced.htm#all_passing_detailed

PktTime
▲ -- Average time the QB had in the pocket between the snap and throwing the ball or pressure collapses the pocket, in seconds
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Hrry
▼ -- Times hurried
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Hits
▼ -- Times hit as a QB while passing
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Sk
▼ -- Times Sacked (first recorded in 1969, player per game since 1981)
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Prss%
▼ -- Times pressured per dropback
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Scrm
▼ -- Scrambles (rushes on plays designed as passes)
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Yds/Scr
▼ -- Yards per scramble attempt
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"Dolfanalyst wrote:

But do we know the correlation between time to throw and performance? We do know that when passes are thrown beyond three seconds after the snap, EPA on average is negative:

https://www.pff.com/news/nfl-the-perfect-timing-a-deeper-dive-into-time-to-throw-data

So that doesn't leave a whole lot of time between what's average throughout the league, in terms of time to throw, and when performance would be expected to drop off on average.

For those averages the correlation to passer rating is -0.1068, and importantly the p-value is 0.5235 which means that the correlation isn't significantly different from zero. Your link helps explain why: EPA increases over some portions but decreases over others. However, that's using only averages. I don't have play by play data on hand to do a better analysis.

Your link is better in that regard, but what the EPA analysis in that link is lacking is multiplying those effects by the probabilities of different time to throws occurring. That is, if something occurs infrequently it won't have as big an effect on overall performance even if EPA increases or drops by a lot. So you really need to look at play by play EPA combined with the probability of different events occurring.

Telling stats from the OL/pass pro. categories?

Miami were tied for second in shortest time to pass, Tua was hurried a lot but Miami show up a middle of the pack or better when it comes to pressure %. So Miami and Tua apparently did an incredible job of getting the ball out quickly.

One way of reading that is to say that the Dolphins planned for a majority of short and quick passes, not longer ones, otherwise you'd expect to see Tua planning to hold the ball longer and thus facing more pressures, hits and sacks, right?

Air Yds to the Sticks (-1.4) and average Air Yds (7) seem to indicate the Dolphins were aiming to pass just short of first downs and keep the ball moving that way.

At the same time, Tua showed better than middle of the pack completion %, and even though there were a lot of short passes Tua had the highest aggression rating in the league which means he was passing into tight windows. That could come to Tua forcing passes when easier options might have been available, but it could also indicate the receivers weren't getting a lot of separation, and/or it could simply be a result of a short passing game that doesn't give time for plays to develop. Either way, he managed to get the ball to his receivers pretty well despite having to throw quickly and into tight windows.

In terms of accuracy:

OnTgt% 10th in the league
▼ -- Percentage of on-target throws per pass attempt, excluding spikes and throwaways
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Poor throws was just on the low end for league average (10th from bottom):
Bad%
▼ -- Percentage of poor throws per pass attempt, excluding spikes and throwaways
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Average Depth of Target was, as expected, on the low end:
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But yards before catch seems to be about average or better, which seems surprising considering the short passes, maybe the league as a whole were also passing short?
YBC/R
▼ -- Yards before catch per reception
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Receiving Stats:

Yards after catch were tied for 2nd to bottom. Maybe a result of short passes and tight windows, or maybe receivers not able to get separation and break tackles?
Interestingly, the Bills were worse.
YAC/R
▼ -- Yards after catch per reception
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Number of broken tackles was good for 11th in the league:
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Drop % was bad enough to tie for 3rd worst:
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Although the Bills and Eagles were also on the low end of the league.

Red Zone Stats

Comp % inside 20
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Inside 10:
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Right towards the top.

"Galant wrote:

What do you think will be a best case scenario for Tua next year? It could be, the developing pieces around him, it could be the offense/strategy, or it could just be a reflection on Tua himself, and what we know, and hope to see.

Pertaining to what's quoted above, the good news is that teams can apparently help their QBs and pass offenses function significantly better with help at receiver. Obviously that's intuitive as well, but the degree to which it's true may be surprising.

For the 2017 and 2018 seasons the standardized regression coefficients in predicting EPA per pass dropback team-by-team are as follows.

84% of the variance in EPA per pass dropback explained, with all independent variables statistically significant.

PFF QB grade: 0.425
PFF OL pass blocking grade: 0.198
PFF team receiving grade: 0.560

So the league as a whole is more dependent on receiver play than it is on QB or OL play, in terms of pass efficiency.

When you confine the analysis to Tom Brady's career year-by-year exclusively (NE and TB), you get a roughly analogous finding.

69% of the variance in EPA per pass dropback explained, with all independent variables statistically significant.

PFF QB grade: 0.300
PFF OL pass blocking grade: 0.316
PFF team receiving grade: 0.630

So while Brady has been somewhat more dependent than the league at large on his offensive line play for his teams' pass efficiency, he's been hugely dependent on his receiver play.

So when you consider that the 2021 Dolphins' pass offense was envisioned to function with a premier downfield threat in Will Fuller, capable receivers in Devante Parker and Mike Gesicki, and a highly-touted newcomer in Jaylen Waddle -- and instead functioned with a crippled version of that -- help for Tua and the pass offense could indeed be on the way in the form of personnel changes at receiver.

A qualification here is that while the correlations between QB and OL grades, and the correlation between OL and receiver grades are non-statistically significant, the correlation between QB and receiver grades is 0.52 and statistically significant. I'd like @7089 to weigh in on that (and anything else here) if he would.

"Dolfanalyst wrote:

For the 2017 and 2018 seasons the standardized regression coefficients in predicting EPA per pass dropback team-by-team are as follows.

84% of the variance in EPA per pass dropback explained, with all independent variables statistically significant.

PFF QB grade: 0.425
PFF OL pass blocking grade: 0.198
PFF team receiving grade: 0.560

So the league as a whole is more dependent on receiver play than it is on QB or OL play, in terms of pass efficiency.

A qualification here is that while the correlations between QB and OL grades, and the correlation between OL and receiver grades are non-statistically significant, the correlation between QB and receiver grades is 0.52 and statistically significant. I'd like @7089 to weigh in on that (and anything else here) if he would.

Only comments I'd make here:

1) Is "team" receiving grade a sum of individual WR grades? If so, then it's not removing correlations between individual WR grades, which means the team receiving grade is overestimating the effect of the unit. Same might be true for OL unless they view it as a unit and don't sum up individual contributions.

2) The statistically significant correlation between QB and team receiver grades suggests they need to put an interaction effect into the linear regression, i.e., a QB*WR interaction effect. If the QB*WR interaction effect soaks up most of the variance then that suggests PFF analysts have a difficult time separating the individual contributions of QB and WR.

Otherwise it's a good start. One thing PFF doesn't do but should do is transform their grades to a logit scale. When people rate things the difference between ratings K and K+1 don't a priori represent the same difference in an underlying latent variable (in this case the ability of the football player). If you have many graders rating the same individuals there's a mathematics called Rasch analysis that can transform the ratings onto a scale (in logit units) so that the difference between K and K+1 represent the same difference. That automatically would improve predictions, mostly at the tail ends of the scale.

"tirty8 wrote:

Okay, I have a question about that. Would you still sign another WR?

If so, what names would you be looking at and more importantly, how would you define their role within the team?

I see this as more of the meat and potatoes of team construction. If I was recruiting someone like Christ Godwin, he is probably looking to a situation where he is catching 100 passes. The Miami Dolphins had 400 catches as a team last year.

If you are in his camp, you are seeing Waddle probably getting 100 catches. Let's count Gesicki as 65 if he returns. Give another 50 for RBs. We will go with "other receivers" catching 50 receptions.

Giving an incentive based contract to Parker would leave me to believe that he could expect around 50 catches. Is that enough to meet his incentives? If you are giving him more, you are taking away from someone.

I am not saying that it could not work, but it is starting to get tight.

I would absolutely be looking to upgrade the WR group but I havent started looking at which FAs are available yet. But with Parker it's "the devil you know" scenario. By the same token if they decide he's not part of the future plans, I'm ok with that as well. He's never lived up to his potential for various reasons, but it also seems like he's been a good team player (or at least not a locker room cancer).

IMO when Parker is healthy and involved in the game plan he can be a very good receiver, however his inability to stay healthy creates problems for the team. I wouldn't have a problem with them letting him walk away either. I just wouldn't give him any kind of big guaranteed salary but he has yet to live up to what they have paid him. He's worth a low dollar short-term (maybe 2 years) deal. Just because he would have an incentive package doesn't mean they have to target him just to try and meet his numbers, if they come organically, so be it, it means he's contributing. They could also just offer him a veteran-minimum salary. Lots of ways for this to play out that don't handcuff the team.

Sorry I kinda rambled on a bit but I think I answer your question.

If Aaron Rodgers leaves GB, I’d push hard for Adams.

"Fishhead wrote:

If Aaron Rodgers leaves GB, I’d push hard for Adams.

Its looking like Rodgers and Adams are a package deal. GET THEM BOTH TO MIAMI!

"M1NDCRlME wrote:

Its looking like Rodgers and Adams are a package deal. GET THEM BOTH TO MIAMI!

Keep in mind the cost would be enormous. We'd probably have to give up the equivalent of at minimum 3 and possibly 4 1st round picks for this given the huge interest from other teams. Having said that I'd be for it. Rodgers should be an elite QB for several years at least, giving us a short window for a SB. It would rejuvenate this franchise. Whoever the HC is will also look "impressive" lol.

If we do this we'd obviously trade Tua. Probably worth at least a 2nd and maybe a 1st given how QB needy some teams are, so that would cushion the cost a bit.

"cbrad wrote:

Keep in mind the cost would be enormous. We'd probably have to give up the equivalent of at minimum 3 and possibly 4 1st round picks for this given the huge interest from other teams. Having said that I'd be for it. Rodgers should be an elite QB for several years at least, giving us a short window for a SB. It would rejuvenate this franchise. Whoever the HC is will also look "impressive" lol.

Agreed. This is one of the only scenarios where I'd be willing to mortgage the future to win now.

"cbrad wrote:

Only comments I'd make here:

1) Is "team" receiving grade a sum of individual WR grades? If so, then it's not removing correlations between individual WR grades, which means the team receiving grade is overestimating the effect of the unit. Same might be true for OL unless they view it as a unit and don't sum up individual contributions.

2) The statistically significant correlation between QB and team receiver grades suggests they need to put an interaction effect into the linear regression, i.e., a QB*WR interaction effect. If the QB*WR interaction effect soaks up most of the variance then that suggests PFF analysts have a difficult time separating the individual contributions of QB and WR.

Otherwise it's a good start. One thing PFF doesn't do but should do is transform their grades to a logit scale. When people rate things the difference between ratings K and K+1 don't a priori represent the same difference in an underlying latent variable (in this case the ability of the football player). If you have many graders rating the same individuals there's a mathematics called Rasch analysis that can transform the ratings onto a scale (in logit units) so that the difference between K and K+1 represent the same difference. That automatically would improve predictions, mostly at the tail ends of the scale.

In a model with QB grades, receiving grades, and an interaction effect, 81% of the variance in EPA per pass dropback is predicted, and none of the three independent variables is statistically significant.

As far as I know the team receiver and OL grades are for the whole units, as they're on a scale that's the same as the individual player grades.

"JJ_79 wrote:

Good sum up but I don't know if I want to replace Parker he's pretty cheap and when on the field quite useful. The more I hear and see about McDaniel, wants me to see him here and the more I want him here the less likely I think he's going to be our HC.

As to the best case scenario, Tua becomes what we hoped for and silences his critics but I have my doubts that will happen, if not that he has to show that he's more then just a game manager...

Oh and that he fully heals up and stays healthy. Tua is not the QB he was before the hip injury, his body is probably at 75% what is was before maybe a little more and a guy from his statue needs to be healthy to perform. I think when and if he fully heals from that hip injury his ball velocity is going to get a little better and that might be enough for him to become a top 10 QB, hopefully…

"Dolfanalyst wrote:

In a model with QB grades, receiving grades, and an interaction effect, 81% of the variance in EPA per pass dropback is predicted, and none of the three independent variables is statistically significant.

That's interesting lol. So QB and WR alone (with OL) are statistically significant, but put in the interaction term and they no longer are. That supports the hunch that it's really difficult to tease apart contribution of the QB and WR when evaluating either.

Anyway, you'll get statistical significance if you increase sample size enough. Question is which becomes significant first, and if multiple factors are significant what are their p-values (or t-values). It will be important to report the coefficients (slopes) at that point to see which has the biggest effect on EPA per pass dropback.