Well, you guys think I'm a nut... So here it is, the data you've all been waiting so patiently for. I've included the Excel Workbook I used. the 20##P tabs are punting stats, the 20##D are defensive stats with correlations to punting, and the 20##WL tabs are W/L records with correlations to punting. I even made a sheet with all the glorious data in one spot.
There is no strong correlation between having a good punter and how good an NFL defense is and there is no strong correlation between having a good punter and win percentage. So, next time you want to defend a contract to a punter for millions per year, I'm going to tell you that you're an idiot. So long as a punter is NFL caliber, he's simply good enough.
Below are the correlation coefficients. I'll leave it to you folks to pour through the rest of it on your own.
Spoiler!
2017
Correlation Coefficient of Yds/G to Punter Rank (Net Ave) -0.194
Correlation Coefficient of Yds/G to Net Ave 0.085
Correlation Coefficient of Yds/G to Punter Rank (IN 20) 0.028
Correlation Coefficient of Yds/G to IN 20 -0.053
Correlation Coefficient of Pts/G to Punter Rank (Net Ave) -0.152
Correlation Coefficient of Pts/G to Net Ave 0.073
Correlation Coefficient of Pts/G to Punter Rank (IN 20) -0.035
Correlation Coefficient of Pts/G to IN 20 -0.020
Correlation Coefficient of W% to Punter Rank (Net Ave) -0.027
Correlation Coefficient of W% to Net Ave 0.132
Correlation Coefficient of W% to Punter Rank (IN 20) 0.022
Correlation Coefficient of W% to IN 20 -0.006
2016
Correlation Coefficient of Yds/G to Punter Rank (Net Ave) -0.209
Correlation Coefficient of Yds/G to Net Ave 0.180
Correlation Coefficient of Yds/G to Punter Rank (IN 20) 0.209
Correlation Coefficient of Yds/G to IN 20 -0.165
Correlation Coefficient of Pts/G to Punter Rank (Net Ave) 0.096
Correlation Coefficient of Pts/G to Net Ave -0.014
Correlation Coefficient of Pts/G to Punter Rank (IN 20) 0.256
Correlation Coefficient of Pts/G to IN 20 -0.147
Correlation Coefficient of W% to Punter Rank (Net Ave) -0.314
Correlation Coefficient of W% to Net Ave 0.163
Correlation Coefficient of W% to Punter Rank (IN 20) -0.140
Correlation Coefficient of W% to IN 20 0.041
2015
Correlation Coefficient of Yds/G to Punter Rank (Net Ave) -0.266
Correlation Coefficient of Yds/G to Net Ave 0.299
Correlation Coefficient of Yds/G to Punter Rank (IN 20) -0.220
Correlation Coefficient of Yds/G to IN 20 0.202
Correlation Coefficient of Pts/G to Punter Rank (Net Ave) -0.236
Correlation Coefficient of Pts/G to Net Ave 0.259
Correlation Coefficient of Pts/G to Punter Rank (IN 20) -0.116
Correlation Coefficient of Pts/G to IN 20 0.054
Correlation Coefficient of W% to Punter Rank (Net Ave) 0.231
Correlation Coefficient of W% to Net Ave -0.323
Correlation Coefficient of W% to Punter Rank (IN 20) 0.280
Correlation Coefficient of W% to IN 20 -0.199
2014
Correlation Coefficient of Yds/G to Punter Rank (Net Ave) -0.161
Correlation Coefficient of Yds/G to Net Ave 0.131
Correlation Coefficient of Yds/G to Punter Rank (IN 20) 0.207
Correlation Coefficient of Yds/G to IN 20 -0.156
Correlation Coefficient of Pts/G to Punter Rank (Net Ave) -0.114
Correlation Coefficient of Pts/G to Net Ave 0.060
Correlation Coefficient of Pts/G to Punter Rank (IN 20) 0.340
Correlation Coefficient of Pts/G to IN 20 -0.296
Correlation Coefficient of W% to Punter Rank (Net Ave) 0.128
Correlation Coefficient of W% to Net Ave -0.046
Correlation Coefficient of W% to Punter Rank (IN 20) -0.126
Correlation Coefficient of W% to IN 20 0.102
2013
Correlation Coefficient of Yds/G to Punter Rank (Net Ave) 0.102
Correlation Coefficient of Yds/G to Net Ave -0.091
Correlation Coefficient of Yds/G to Punter Rank (IN 20) -0.120
Correlation Coefficient of Yds/G to IN 20 0.123
Correlation Coefficient of Pts/G to Punter Rank (Net Ave) 0.394
Correlation Coefficient of Pts/G to Net Ave -0.396
Correlation Coefficient of Pts/G to Punter Rank (IN 20) 0.156
Correlation Coefficient of Pts/G to IN 20 -0.129
Correlation Coefficient of W% to Punter Rank (Net Ave) -0.234
Correlation Coefficient of W% to Net Ave 0.276
Correlation Coefficient of W% to Punter Rank (IN 20) -0.138
Correlation Coefficient of W% to IN 20 0.122
Ok, so you weren't wrong to say 8 of the top 10 in PPG were top 15 in Punts inside the 20%. However, this theory doesn't really hold up in other years in the data set. Also, I've shown no strong correlation. There also isn't a strong correlation between YDS/G and Punts inside the 20 %.
Despite the fact that we haven't found any strong indicator that punting affects defense in a meaningful way this did prompt me to do one more data set, and that is Win % versus Punt IN 20 % and that has given the strongest correlation of all data.
Spoiler!
2017 Correlation Coefficient of W% to %IN 20 0.469
2016 Correlation Coefficient of W% to %IN 20 0.316
2015 Correlation Coefficient of W% to %IN 20 -0.042
2014 Correlation Coefficient of W% to %IN 20 0.638
2013 Correlation Coefficient of W% to %IN 20 0.401
This is surprising, because one would expect that if they did affect W% they'd also affect Defensive performance. That really doesn't seem to be the case. [Reply]
Number of teams in the top 10 in % of Punts IN 20 that were also in top 15 in PTS/G
2017: 8
2016: 6
2015: 5
2014: 6
2013: 5
What this tells me is that if you have a punter that is in the top 30% of the league in % IN 20, then you've got about a 60% chance of being in the top half the league in PTS/G. But, if you have one of the 70% of the rest of the punters, you still have a 40% shot... However, 2017 skews the data and if we were to regress that value more towards the mean (6), we'd end up closer to a 55%/45% split.
Originally Posted by ntexascardfan:
I'm not sure those are the right things to be measuring.
To really determine the effectiveness of a good punter you'd have to measure the effect he has on the defense, not directly correlating a team with good defense to the quality of their punter.
Does having a top five punter in the league v. a replacement level punter keep points off the board, does it make teams have to drive more of the field to score?
A good defense doesn't need a great punter to be good, but how much better does having a great punter make a good defense? That's the question that needs to be asked.
Anecdotally, I would point to the Texas v. Mizzou bowl game last year for what an elite punter can do to a teams offense. If you want to tell me that Mizzou starting over 1/2 of their drives inside their own 15 yard line didn't have an affect on that game I have a bridge in New York I'd like to sell ya.
The Texas punter was the MVP of that bowl game. He’s a helluva punter. [Reply]
Originally Posted by KChiefs1:
The Texas punter was the MVP of that bowl game. He’s a helluva punter.
I agree with him on one note, occasionally a great punter can affect a game in a big enough way that it's significant in the team winning. However, the data clearly shows it doesn't over the course of a season and it doesn't over the course of several seasons.
The point of it all, to me, is to ask yourself whether or not it's actually worth spending high dollars on a "great" punter when, statistically, it really doesn't make much of a (if any) difference?
If you can spend low draft capital, or even sign a punter as an UDFA, and he will perform in line with NFL standards at the position, there isn't a clear statistic that I've found that correlates it being any worse than the best in the game over the long-haul.
One thing I'm looking into right now is the differences between punters that are 1 standard deviation below the mean in terms of IN 20 % and those that are 1 standard deviation above the mean. This should give me a better idea of impact of a bad punter versus great punter. [Reply]
Here are the approximate ranges within 1STDEV of the mean, so the data I worked with were for punters above and below these:
2017 1STDEV = 42.98% to 30.42%
2016 1STDEV = 44.69% to 29.99%
2015 1STDEV = 42.29% to 27.85%
2014 1STDEV = 41.68% to 28.90%
2013 1STDEV = 41.41% to 28.59%
I combined these into 1 list to get some data, and so I ended up with 26 punters in total in each category.
>1STDEV
Average %IN20 = 46.4% (Min 42.5%)
Average W% = 59.6%
Average PTS/G = 20.9
Average YDS/G = 344.4
<1STDEV
Average %IN20 = 26.1% (Max 30.0%)
Average W% = 35.1%
Average PTS/G = 24.2
Average YDS/G = 352.6
If I take the data set as a whole I get the following correlations:
IN20% to YDS/G = -0.140
IN20% to PTS/G = -0.430
IN20% to W% = 0.565
What I've learned. It is better to have a great punter in terms of %IN20 than an absolutely shitty punter. That said, overall that means you need to find a punter that is within 1STDEV of the mean or better. It may indicate as well that if you have a punter that is better than one standard deviation from the mean, he is an advantage.
In case you're curious, here's the best and worst through the past 5 years in terms of %IN 20.
Spoiler!
Best Punters 2017
1. Chris Jones, DAL
2. Sam Koch, BAL
3. Johnny Hekker, LAR
4. Dustin Colquitt, KC
5. Thomas Morstead, NO
Best Punters 2016
1. Bryan Anger, TB
2. Johnny Hekker, LAR
3. Dustin Colquitt, KC
4. Matt Bosher, ATL
5. Sam Koch, BAL
6. Jeff Locke, MIN
Worst Punters 2016
1. Britton Colquitt, CLE
2. Colton Schmidt, BUF
3. Bradley Pinion, SF
4. Kevin Huber, CIN
Best Punters 2015
1. Dustin Colquitt, KC
2. Marquette King, OAK
3. Jordan Berry, PIT
4. Brad Wing, NYG
5. Johnny Hekker, LAR
6. Ryan Allen, NE
Worst Punters 2015
1. Mike Scifres, SD
2. Tim Mathay, GB
3. Shane Lechler, HOU
4. Britton Colquitt, DEN
5. Jacob Schum, TB
6. Colton Schmidt, BUF
Best Punters 2014
1. Jon Ryan, SEA
2. Donnie Jones, PHI
3. Dustin Colquitt, KC
4. Pat McAfee, IND
5. Sam Koch, BAL
6. Drew Butler, ARI
7. Sam Martin, DET
Worst Punters 2014
1. Michael Koenen, TB
2. Bryan Anger, JAX
3. Spencer Lanning, CLE
4. Jeff Locke, MIN
5. Pat O'Donnell, CHI
6. Marquette King, OAK
7. Tim Masthay, GB
8. Tress Way, WAS
Here are the approximate ranges within 1STDEV of the mean, so the data I worked with were for punters above and below these:
2017 1STDEV = 42.30 to 39.14
2016 1STDEV = 42.21 to 38.44
2015 1STDEV = 41.68 to 38.16
2014 1STDEV = 41.30 to 37.73
2013 1STDEV = 41.55 to 37.48
I combined these into 1 list to get some data, and so I ended up with 25 punters above and 22 punters below 1STDEV.
>1STDEV
Average Net = 42.9
Average W% = 50.75%
Average PTS/G = 22.4
Average YDS/G = 348.2
<1STDEV
Average Net = 37.2
Average W% = 47.44%
Average PTS/G = 22.8
Average YDS/G = 337.7
If I take the data set as a whole I get the following correlations:
NetAve to YDS/G = 0.164
NetAve to PTS/G = -0.080
NetAve to W% = 0.065
After seeing all of this data, I can pretty well conclude that the only real factor you need to look at with a punter is % inside the 20. That seems to be the only factor that has any significant impact on games and it seems to do so in terms of PTS/G and W%. Now the question is, at what point is there a cutoff where it no longer matters? This would tell me a reasonable break in what should define a punter "worth paying" versus one that isn't. My next question would be, at what point is the cutoff for bad punters? I'm working on formulating how I want to tackle these questions. Basically, I have to continue to include punters by %IN 20 in tiers until I reach a 50% mark for win percentage, IMO. If anyone has a suggestion, feel free to chip in. [Reply]
Originally Posted by kccrow:
After seeing all of this data, I can pretty well conclude that the only real factor you need to look at with a punter is % inside the 20. That seems to be the only factor that has any significant impact on games
Considering that Peters,Hali and Johnson are gone and Ford,KPass are still question marks, with Amerson and Fuller getting acclimated with Fuller being the only real starting CB with no hard hitting safety, with inconsistent d-line play; our defense is still very suspect and why a good punter helps because when our offense gets stopped it will now be between the 40's with Mahomes(where a finesse punt is needed more often) as opposed to being stopped more often than not inside our 40 with Smith at QB(where you need a booming punt).
With Mahomes now at QB with still a very suspect defense you need finesse punting more than ever pinning back the opposing offense giving your suspect defense more of a chance for a stop and why Colquit got paid. Veatch recognizes his defense needs help in the field position game for sure. [Reply]
Originally Posted by Chiefshrink:
Considering that Peters,Hali and Johnson are gone and Ford,KPass are still question marks, with Amerson and Fuller getting acclimated with Fuller being the only real starting CB with no hard hitting safety, with inconsistent d-line play; our defense is still very suspect and why a good punter helps because when our offense gets stopped it will now be between the 40's with Mahomes(where a finesse punt is needed more often) as opposed to being stopped more often than not inside our 40 with Smith at QB(where you need a booming punt).
With Mahomes now at QB with still a very suspect defense you need finesse punting more than ever pinning back the opposing offense giving your suspect defense more of a chance for a stop and why Colquit got paid. Veatch recognizes his defense needs help in the field position game for sure.
I was just talking with a friend about this very thing.
We also discussed looking at how offensive performance affects Punt Inside 20 %. I think there's a solid chance it is a factor. Just looking at the data I've poured through and the teams I see having punters at the worst end of that, like Buffalo, Cleveland, New York, etc, I just want to see how it looks. I've put way too much time into this tonight and I'm not any further.
I'm looking for more beyond Dustin Colquitt though in all of this. I want to see if there really is a reason to pay a punter good money and when that situation should exist from a statistical perspective. I think I'm close to that answer now, but I don't know if I can take it much further.
It's been forever since I got my undergrad degree in mathematics. I haven't used it for a very long time, especially anything beyond basic algebra because of the field I'm in. I don't' have the time nor do I remember much on multivariate analysis. I'd love to see someone that does take this to another level. It'd be interesting to see it. [Reply]