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Around SBN: Don't Blame Wes Welker

Singletary’s Formula for Success: Introducing the 49ers’ Adjusted BS Rate

AUTHOR'S NOTE: Sorry for the delay in getting this posted. Below, you'll understand why it's a day late.

Welcome back for this week's look at how the 49ers are doing according to Mike Singletary's Formula for Success. For those that don't remember Singletary's Formula for Success, here it is:

  1. Total Ball Security
  2. Execute
  3. Dominate the Trenches
  4. Create Good Field Position
  5. Finish

The major takeaways form last week's post were that (a) the 49ers are an average team based on the formula, and (b) the formula itself is a pretty reliable indicator of the 49ers' record. Given that the play-by-play sample sizes are so large now, we shouldn't expect much statistical fluctuation from game to game. Nevertheless, the directions in which these stats change (i.e., for better or worse) can tell us something about the progress of our beloved team when it comes to doing the things that their coach views as most crucial for winning. But I'll get to that stuff later.

The focus of today's post emerged from some thinking I did about the two stats I used last week to measure Total Ball Security: Fumbles and Interceptions. In my haste to put the post together, I didn't really sit down and fully contemplate whether these were the best stats I could use. From reading Football Outsiders and other sources, I already knew that Fumbles is a much better stat than Fumbles Lost because the recovery of a fumble is more about luck and less about skill. But honestly, aside from relying on this basic knowledge, I used Fumbles and Interceptions because they were the most (and only ones) readily available.

Since then, I've searched around the internet trying to find more - I guess what you'd call - advanced stats related to the ability of an NFL team to hold onto the ball. Or, in the language of Singletary's Formula for Success, the ability of an NFL team to achieve total ball security. Not surprisingly, this was a fruitless search. As far as I can tell, no one's made a public attempt to develop such a statistic.

Well, consider yourselves lucky. Based on the premises that (a) Total Ball Security is an ingredient in Singletary's Formula for Success, (b) I'm writing a weekly post about this formula, and (c) no one else seems to have come up with a good measure for this specific ingredient, I've come to the conclusion that I'm the person I've been waiting for.

Therefore, in today's Formula for Success post, I'm going to introduce a new stat, which I'll call Adjusted Ball Security Rate, aka Adjusted BS Rate. Don't worry. I've reported the rest of the Formula's stats at the end of the post. But the major purposes of this post will be to give you my rationale behind Adjusted BR rate, tell you the methods I used to develop Adjusted BS Rate, and present some evidence showing you that Total Ball Security, as measured by Adjusted BS rate, is - as Singletary clearly believes - directly associated with winning in the NFL.

After the jump, I'll unveil my newly minted Niners Nation special, Adjusted BS Rate...

Star-divide

RATIONALE FOR ADJUSTED BS RATE

The first problem that emerged when I thought about Fumbles and Interceptions as measures of Total Ball Security is something very basic to statistics: rates are better than totals when sample units differ in their ability to aggregate the total. Using an NFL example, this essentially means that it's wrong to compare the 49ers' total number of fumbles (16) to that of the Steelers (16) because the 49ers' have had fewer "opportunities" to actually fumble the ball (SF = 701; PIT = 779). The better stat to use than Total Fumbles is, therefore, Fumble Rate, i.e., "fumbles per fumbling opportunity."

Similarly, it's wrong to compare the 49ers' total number of interceptions (9) to that of the Seahawks (9) because the 49ers' have had fewer "opportunities" to actually throw an interception (SF = 352; SEA = 424). The better stat to use than Total Interceptions is, therefore, Interception Rate, i.e., "interceptions per interception opportunity."

However, determining that it's better to use Fumble Rate and Interception Rate as measures of Total Ball Security only gets you so far. Given my definitions for each, the question becomes, "What constitutes a fumbling or interception opportunity?" Well, in the case of an "interception opportunity," the answer is pretty simple. An interception can only occur if an offense attempts a pass. Therefore, an "interception opportunity" is the same thing as a pass attempt, and so Interception Rate is simply Total Interceptions divided by Total Pass Attempts. Not surprisingly, this exact statistic - presumably because it's so easily calculated and understood - is one of the 4 components of the NFL QB Rating formula.

A "fumbling opportunity," on the other hand, is a much tougher nut to crack. First, going back to my original question, what constitutes a fumbling opportunity? Second, and just as important, even if we can define a fumbling opportunity, are there stats available to quickly and appropriately measure it?

To determine the qualities of a "fumbling opportunity," a good place to start is the NFL rule book, which defines a fumble as "the loss of player possession of the ball." In addition, the rules distinguish between a fumble and a muff - let's keep our minds out of the gutter here, guys - which is defined as "the touching of a loose ball by a player in an unsuccessful attempt to obtain possession." Nearly all muffs occur on punts and kickoffs. However, when a KR/PR muffs a kick/punt, it's an indication of his inability to maintain Total Ball Security, so, for our purposes, such muffs can also be considered fumbles. Therefore, taking these definitions and formula-related purposes into account, the only time a player has the opportunity to fumble the ball is if he (a) is currently in possession of the ball; or (b) is attempting to obtain possession of a kick/punt.

So the key here is to figure out all of the circumstances in which a player "is currently in possession of the ball" or "is attempting to obtain possession of a kick/punt." Well, it turns out that, when you think about it, the options are pretty limited. They basically boil down to the following:

  1. A QB has possession after he takes the snap from center
  2. A RB/TE/WR has possession after he receives a handoff
  3. A RB/TE/WR has possession after he receives a pass
  4. A defensive player has possession after he recovers a fumble
  5. A defensive player has possession after he intercepts a pass
  6. A PR is attempting to obtain possession when he fields a punt
  7. A PR has possession while he returns a punt
  8. A KR is attempting to obtain possession when he fields a kick
  9. A KR has possession while he returns a kick

Therefore, all of these constitute a "fumbling opportunity."

Now, with a "fumbling opportunity" defined, and the exhaustive list of fumbling opportunities identified, we move on to the next question: "Can we obtain stats to quickly and appropriately measure fumbling opportunities?" Thankfully, the answer here is "yes." That's because there are a whole host of official NFL stats that aggregate the various types of player possession (and attempts at obtaining possession of punts/kicks) listed above. For instance, the stat, Rushing Attempts, tells you how many times a team's RBs/TEs/WRs were in possession of the ball after receiving a handoff. In the next section, I'll list out all of the stats I used to measure "fumbling opportunities," but, at this point, just understand that we now know (a) what constitutes a fumbling opportunity, and (b) that we can measure it quickly and appropriately.

So, just to sum up, Total Fumbles and Total Interceptions are inadequate for measuring Total Ball Security because NFL teams differ with respect to the number of opportunities they have to fumble the ball or throw an interception. Better stats would be Fumble Rate and Interception Rate, but, before calculating them, we have to figure out what constitutes a "fumbling opportunity," and an "interception opportunity." In this section, I did just that.

METHODS FOR CALCULATING ADJUSTED BS RATE

Before we can calculate Adjusted BS Rate, we first have to calculate BS Rate. However, even before we can calculate BS Rate, we have to calculate Fumble Rate and Interception Rate, which I'll abbreviate as FR and IR from now on. As I mentioned earlier, IR is pretty straightforward. Here's the equation:

IR = Offensive Interceptions / Pass Attempts

Calculating FR eventually becomes straightforward as well, but only after first calculating "fumbling opportunities." Here's a list of the stats I've concluded best measure the number of opportunities a team has had to fumble the ball, as defined by either having possession of the ball or attempting to obtain it while fielding a kick/punt:

  1. Fumbling opportunities during QB possession = Sacks Allowed + Incompletions*
  2. Fumbling opportunities during a RB/TE/WR run = Rushing Attempts
  3. Fumbling opportunities during a RB/TE/WR run after catch = Receptions
  4. Fumbling opportunities during a fumble return = Defensive Fumble Recoveries
  5. Fumbling opportunities during an interception return = Defensive Interceptions
  6. Fumbling opportunities during the fielding or returning of a punt = Punt Returns
  7. Fumbling opportunities during the fielding or returning of a kick = Kick Returns

Therefore, here's the equation for "fumbling opportunities," which I'll abbreviate FOPPS:

FOPPS = Sacks Allowed + Incompletions + Rushing Attempts + Receptions + Defensive Fumble Recoveries + Defensive Interceptions + Punt Returns + Kick Returns

And that makes the equation for FR as follows:

FR = Fumbles / FOPPS

So now we have our two core stats, IR and FR, which measure "interceptions per interception opportunity," and, "fumbles per fumbling opportunity," respectively.

The next step is to combine IR and FR so that we come up with our BS Rate. Because we want to measure Total Ball Security, rather than Total Ball Insecurity, the first thing we have to do is subtract each of these from 100%. Then, in order to get BS Rate, we have to calculate what's called a weighted average of IR and FR because Pass Attempts and FOPPS are not equal. You can click here for a thorough discussion of weighted averages, but the bottom line is that, if we simply added IR and FR, then IR would be make up 50% of BS Rate, despite the fact that Pass Attempts only makes up about 30% of all ball insecurity opportunities. In other words, we'd be giving IR 20% more of an impact on BS Rate than it deserves. Just to make things as clear as possible, here's the equation for BS Rate:

BS Rate = {[(1 - IR) * Pass Attempts] + [(1 - FR) * FOPPS)]} / (Pass Attempts + FOPPS)

Finally, we can't ignore the fact that different teams play schedules of differing strengths when it comes to (a) their opponents' ability to force fumbles, and (b) their opponents' ability to intercept the ball. Therefore, in ultimate satisfaction of measuring Total Ball Security, we have to adjust BS Rate for strength of schedule (SOS). I did some hardcore stats on this and it turns out that a team's FR is not related at all to their FR SOS (correlation = .072, which is not statistically different from 0). In other words, how often a team fumbles isn't related to how often their opponents force fumbles, at least not in 2009. Therefore, the only thing to adjust for is IR SOS, which does have a statistically meaningful impact on IR (correlation = .486). After adjusting for IR SOS, we end up with this equation for Adjusted BS Rate:

Adjusted BS Rate = {[(1 - Adjusted IR) * Pass Attempts] + [(1 - FR) * FOPPS)]} / (Pass Attempts + FOPPS)

Notice that the only manner in which the equation for Adjusted BS Rate differs from that of Unadjusted BS Rate is the use of Adjusted IR, rather than IR, in the numerator. I fully understand that, unless you have statistical software handy and know how to "adjust for" IR SOS, you can't directly calculate Adjusted BS Rate at home (assuming you'd even want to do so). As you'll see below, however, Adjusted BS Rate doesn't differ all that much from Unadjusted BS Rate, which you can, in fact, calculate without the need for statistical expertise.

TOTAL BALL SECURITY STATS

Below you'll find Adjusted BS Rates, Unadjusted BS Rates, FRs, IRs, and Adjusted IRs for each NFL team so far this season (49ers and top 8 for each category in bold; bottom 8 in italics):

Team

Adj BS Rate

BS Rate

Rk

FR

Rk

IR

Rk

Adj IR

Rk

1

MIN

98.73%

98.82%

1

1.36%

2

0.80%

1

1.10%

2

2

NE

98.66%

98.38%

2

1.53%

3

1.80%

5

0.97%

1

3

MIA

98.20%

97.71%

13

1.99%

10

3.00%

21

1.34%

3

4

DEN

98.12%

98.29%

4

1.60%

4

1.94%

6

2.47%

11

5

IND

98.11%

98.21%

6

1.20%

1

2.82%

18

3.10%

20

6

SD

98.05%

98.25%

5

1.77%

7

1.71%

4

2.31%

7

7

ATL

98.02%

97.86%

10

1.67%

6

3.09%

23

2.61%

13

8

GB

97.98%

98.33%

3

1.84%

9

1.31%

2

2.40%

8

9

BAL

97.95%

98.18%

7

1.67%

5

2.14%

10

2.83%

15

10

HOU

97.90%

97.86%

9

1.86%

8

2.70%

16

2.59%

12

11

PHI

97.89%

97.92%

8

1.96%

13

2.30%

11

2.41%

9

12

NO

97.82%

97.62%

17

2.27%

18

2.62%

14

1.97%

6

13

DAL

97.78%

97.73%

15

2.43%

24

1.95%

7

1.80%

5

14

JAC

97.76%

97.79%

12

2.47%

26

1.66%

3

1.75%

4

15

STL

97.72%

97.73%

18

1.96%

14

2.89%

19

2.92%

19

16

NYG

97.70%

97.72%

14

2.11%

17

2.65%

15

2.70%

14

17

CIN

97.66%

97.79%

11

2.13%

16

2.38%

12

2.85%

16

18

SF

97.53%

97.63%

19

2.28%

21

2.56%

13

2.86%

17

19

PIT

97.41%

97.66%

16

2.05%

12

2.95%

20

3.70%

25

20

BUF

97.40%

97.28%

23

1.97%

11

4.42%

26

4.00%

26

21

TEN

97.37%

97.33%

22

2.52%

27

3.03%

22

2.89%

18

22

ARI

97.26%

97.40%

20

2.48%

25

2.80%

17

3.19%

23

23

CLE

97.19%

97.07%

26

2.21%

20

4.50%

28

4.11%

27

24

KC

97.18%

97.31%

24

3.00%

30

2.01%

8

2.43%

10

25

WAS

97.08%

97.12%

25

2.75%

28

3.15%

24

3.28%

24

26

SEA

97.03%

97.37%

21

2.90%

29

2.12%

9

3.11%

21

27

DET

96.90%

96.82%

28

2.11%

19

5.19%

30

4.97%

29

28

TB

96.89%

96.47%

32

3.07%

32

4.46%

27

3.19%

22

29

CAR

96.85%

96.66%

29

2.34%

22

5.60%

31

4.98%

30

30

CHI

96.82%

96.94%

27

2.03%

15

4.93%

29

5.28%

31

31

NYJ

96.72%

96.46%

31

2.50%

23

6.32%

32

5.37%

32

32

OAK

96.59%

96.69%

30

3.03%

31

3.95%

25

4.29%

28

Before I get into the 49ers' stats, I'd just like to point out some evidence supporting the validity of using Adjusted and Unadjusted BS Rate as measures of Total Ball Security. A pretty standard thing to do when you develop a so-called advanced NFL stat, is to find out how related the stat is to winning. Given that the context of my endeavor here is Singletary's Formula for Success, it makes extra sense to see whether being good at Total Ball Security, as measured by Adjusted and Unadjusted BS Rate, is associated with being good at, you know, winning games.  Of course, you probably suspect that I wouldn't be taking up all this time and space if they weren't. If so, you'd be suspecting correctly. Here's a table showing the correlations between the Total Ball Security stats above and Team Wins in 2009 (all are highly statistically different from 0), along with the percentage of "winning" that's explained by each stat (aka R-squared):

Statistic

Correlation

R-squared

Adjusted BS Rate

.659

43.45%

Unadjusted BS Rate

.689

47.41%

FR

-.547

29.93%

IR

-.553

30.56%

Adjusted IR

-.516

26.62%

If you don't know how to interpret a correlation or R-squared, click here. Basically, what this table is telling you is that each stat is highly associated with winning in 2009, and that each stat explains a considerable amount of the "winning" phenomenon.** For instance, the correlation between FR and Team Wins (-.547) means that, beyond the longest shadows of statistical doubt, a team has won more games this season if they have a lower FR. Furthermore, the R-squared value for Adjusted BS Rate means that 43.45% of "winning" is due to Adjusted BS Rate. Or, alternatively, only 43.45% 56.55% of "what it takes to win" has nothing to do with Adjusted BS Rate. Given the complexity of figuring out "what it takes to win" in the NFL, I'd say these correlations clearly suggest that Adjusted BS Rate is a useful measure of Total Ball Security, and that Mike Singletary is clearly justified for including Total Ball Security as an ingredient in his Formula for Success.

THE REST OF THE 49ERS' FORMULA STATS

Now that I have a useful stat for measuring Total Ball Security, I can add it to the following table, which displays the Niners stats according to Singletary's Formula for Success, what those stats were last week, and what the extent of change was between this week's stats and last week's stats (top-8 in bold; bottom-8 in italics):

 

 

This Week

 

Last Week

 

Change

Formula Ingredient

Statistic

Value

Rk

Value

Rk

Value

Rk

Total Ball Security

Adj BS Rate

97.53%

21

 

--

--

 

--

--

Total Ball Security

FR

2.28%

21

 

--

--

 

--

--

Total Ball Security

IR

2.56%

13

 

--

--

 

--

--

Execute

Total

-1.6%

20

-2.0%

20

+0.4%

0

Execute

OFF

-10.0%

21

 

-10.5%

22

 

+0.5%

1

Execute

DEF

-7.6%

7

 

-7.9%

6

 

-0.3%

-1

Execute

ST

0.8%

15

 

0.6%

15

 

+0.2%

0

Execute

1Q OFF

-39.3%

31

 

-39.9%

29

 

+0.6%

-2

Execute

1Q DEF

-2.7%

13

 

-3.7%

12

 

-1.0%

-1

Dominate the Trenches

OL ALY

3.21

32

 

3.23

31

 

+0.02

-1

Dominate the Trenches

OL ASR

9.3%

29

 

10.0%

29

 

+0.7%

0

Dominate the Trenches

DF7 ALY

3.65

7

 

3.34

3

 

-0.31

-4

Dominate the Trenches

DF7 ASR

6.7%

13

 

6.7%

14

 

+0.0%

1

Create Great Field Position

FG/XP Pts

1.1

15

 

-0.2

18

 

+1.3

3

Create Great Field Position

KO Pts

3.2

15

 

1.6

17

 

+1.6

2

Create Great Field Position

KR Pts

-1.9

18

 

-1.9

17

 

0.0

-1

Create Great Field Position

P Pts

11.0

2

 

12.4

1

 

-1.4

-1

Create Great Field Position

PR Pts

-10.1

31

 

-9.7

32

 

-0.4

1

Create Great Field Position

Own 1-20 OFF

-35.2%

30

 

-36.6%

30

 

+1.4%

0

Create Great Field Position

Opp 1-20 DEF

22.2%

24

 

17.9%

23

 

-4.3%

-1

Finish

4Q OFF

3.2%

18

 

5.9%

18

 

-2.7%

0

Finish

4Q DEF

2.8%

14

 

8.0%

18

 

+5.2%

4

Finish

Late/Close OFF

-27.7%

31

 

-26.0%

29

 

-1.7%

-2

Finish

Late/Close DEF

-13.1%

9

 

-12.3%

10

 

+0.8%

1

In terms of Total Ball Security, we now see that the 49ers a below-average team when it comes to their overall ability to keep possession of the ball, but an above-average team when it comes to keeping possession of the ball when they throw a pass. To this I say, enough already with the "shotgun offense equals more interceptions" crap.  Even their current Adjusted IR is almost twice as good as the team who has the #12 Rush OFF DVOA and a much-hyped wunderkind taking 82.5% of his snaps from under center (aka the New York Jets).

With respect to the other formula ingredients, like I said, not much has changed. The two biggest changes from Week 11 were defensive front 7 (DF7) ALY getting a lot worse and 4th Quarter DEF DVOA getting much better. Given that Maurice Jones-Drew was able to run the ball with reasonable success against the league's #5 run DEF, and the spectacular 4th-quarter display we saw from the Niners' #11 pass DEF, these changes make perfect sense.

BOTTOM LINE

Based on my introduction to Adjusted BS Rate and the 49ers' stats through 11 games, we can draw the following conclusions:

  1. Adjusted and Unadjusted BS Rate are good composite measures of Total Ball Security.
  2. FR is a good indicator of a team's ability to avoid fumbling the ball when they have the opportunity to do so.
  3. Adjusted and Unadjusted IR are good indicators of a team's ability to avoid throwing an interception when they have the opportunity to do so.
  4. A team's Adjusted BS Rate, Unadjusted BS Rate, FR, IR, and Adjusted IR are all highly associated with winning.
  5. Singletary is right to include Total Ball Security in his Formula for Success.
  6. The 49ers are a better team with respect to IR than FR and BS Rate (Adjusted or Unadjusted).
  7. The 49ers are still an average team with respect to Singletary's Formula for Success.

Coming up tomorrow... team DVOA stats and rankings.

 

*Incidentally, some of you might quibble with my use of Sacks Allowed + Incompletions as a measure of QB FOPPS. My reasoning is fairly simple. The overwhelming majority of a QB's fumbles in the pocket occur when he's sacked, with the remainder occurring while he's maneuvering in the pocket. In other words, a FOPP for a QB is when he's dropped back to pass. However, I can't use a handy stat like Dropbacks, which equals Sacks + Pass Attempts, because about 60% of all pass attempts result in either a reception or an interception, and I'm already using both Receptions and Defensive Interceptions in the equation. From a statistical perspective, Pass Attempts are what's called multicollinear with Receptions and Defensive Interceptions, which basically means they're providing the same information multiple times in one equation. That's a big no-no in statistics.

Given the need to avoid multicollinearity, I can only use those pass attempts that don't result in a reception or interception. Such pass attempts are otherwise known as "Incompletions." Given that Pass Attempts is part of what makes up Dropbacks, the byproduct of this is that I can only use those dropbacks that don't result in a reception or interception. Such dropbacks are otherwise known as Sacks + Incompletions.

**In case you're wondering why the unadjusted stats explain more of the "winning" phenomenon than the adjusted stats, the reason is pretty simple. Given that IR is itself highly associated with winning, when you adjust for IR SOS, you're essentially removing part of the reason for team wins and losses. In other words, if having a lower IR means winning more games, and part of the reason for having a lower IR is having an easier IR SOS, then that means part of the reason for having more wins also because of having an easier IR SOS. Therefore, when you remove IR SOS as a factor in IR (i.e., when you adjust for it), you're taking out one of the things that explains why a team wins. Necessarily, the result of this "factoring out" is that you've just decreased the stat's ability to explain "winning," shows up via a lower R-squared. Remember, the goal here is to find out how good a team is in Total Ball Security, not how easy an IR SOS they've had. A minor decrease in R-squred is a price that's worth paying in pursuit of a more informative stat.

***DVOA, ALY, and ASR statistics used to produce this article were obtained from Football Outsiders.

Poll
After reading this post, do you understand what Adjusted BS Rate is and how it works?
I understand what it is and how it works.
153 votes
I understand what it is, but not how it works.
16 votes
I don't understand what it is or how it works.
47 votes

216 votes | Poll has closed

Comment 110 comments  |  3 recs  | 

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I like this a lot.

My only questions are really related to moving the stat in other directions.

1) Do you see this being useful for individual player evaluation? Can it be successfully applied to individuals (sample issues clearly become a concern), and what kind of bearing would that have on evaluating an individual’s contribution to the team’s chances at winning?

2) Will there be a version of this for defense? Like… Total Ability to Cause Ball Insecurity… or… something snappier….?

I don't know about that, to the groin.

by howtheyscored on Dec 4, 2009 11:14 AM PST reply actions  

well...

yeah, you can definitely turn this into an individual stat. you’d just have to use only those specific types of fumbling or interception opportunities that are relevant to the player in question.

as for Total Ability to Cause Ball Insecurity (or something snappier), you’d simply use

forced fumble rate = forced fumbles / forced fumbling opportunities

and

interception rate = defensive interceptions / pass attempts allowed

and then come up with the weighted average accordingly. i guess i could come up with that for shits and giggles, but i’ll keep it out of future posts because of the relevance of Total Ball Security to singletary’s formula.

by (Florida) Danny Tuccitto on Dec 4, 2009 11:23 AM PST up reply actions  

Off the top of my head, I would think that if the offense has some ability to control turnover rate, and the defense has some ability to control turnover rate, and both of them are related to winning, than an even stronger stat would be adjusted total team turnover efficiency. That would be kind of cool.

I know that it still doesn’t have to do with the Singletary formula, though. And the idea still assumes some things about a defense’s ability to control turnover rates and an association between defensive turnover efficiency and winning, both of which would have to be measured….

But I just think it sounds cool. And useful.

I don't know about that, to the groin.

by howtheyscored on Dec 4, 2009 11:30 AM PST up reply actions  

also, i might add...

even though you didn’t ask it, you can turn BS rates into Ball Insecurity Rates by subtracting BS Rate (or Unadjusted BS Rate) from 1. so the Niners are insecure with the ball in 2.37% of their opportunities when not adjusting for IR SOS, and insecure in 2.47% of their opportunities if you do adjust for SOS.

something else i didn’t mention in the post is that, seeing as how the most ball insecure team in the NFL is still secure over 96% of the time, it’s amazing to me how such little variation between teams still explains so much of “what it takes to win.” i mean, comparing OAK and MIN, about 50% of the difference between 3-8 and 10-1 is due to being only 2.13% more insecure with the ball. that’s mind-blowing to me…the razor thin line between winning and losing when it comes to Total Ball Security. it sure makes you understand why “attention to detail” is such a positive quality in a head coach. margin for error is so ridiculously small in the NFL.

by (Florida) Danny Tuccitto on Dec 4, 2009 11:32 AM PST up reply actions  

i was surprised by that too!

it really puts even dehlomme’s INTs into some perspective

by sleepyotter on Dec 4, 2009 1:50 PM PST up reply actions  

I wonder if it’s due in part to your IR formula, IR = offensive interceptions / Pass Attmpts and if you need weigh the pass attempts # to account for QB intent. Because, right now each pass attempt results in either:
 - offensive interception
 - NOT offensive interception ( 1 – offensive int)
which means each pass attempt could go 50/50 as it being intercepted or not. However the QB is actively trying NOT to throw interceptions. They are aiming for their own team each time (Rex Grossman, aside), so given that, of course your numerator will be tiny compared to pass attempts and that makes the IR for each team small, so when you do 1-IR and factor it into your Ajd BS, it doesn’t create much differential from the 100%. Maybe instead of total pass attempts, you could some how segment out the pass attempts where the QB was under a lot more pressure, hurried, or the WR did get to their route in time…because for some pass attempts, the chances of throwing an INT are slim because the QB has a lot of time and a clean shot.
So I’m not sure how much of a differenc that would actually make…I’m just kind of taking a break from and thinking out loud here…
great post, by the way!

by sleepyotter on Dec 4, 2009 2:04 PM PST up reply actions  

i think you're on the right track...

in doing the analysis, i actually noticed several qualities of the data that affect the correlations and r-squareds (if that’s the plural of r-squared). one is that, when i just used sacks, rather than sacks + incompletions, as the measure for QB FOPPS, the correlation and r-squared for FR and BS Rate increased. i think that’s because, when adding incompletions, you’re introducing a whole lot of plays, the vast majority of which a QB is never in danger of fumbling. i kept incompletions in because, if i left it out, i’d be omitting all of these plays where a QB is in possession of the ball in the pocket, but does not fumble. using only sacks, i’d basically be adding 100% of the time a QB fumbles in the pocket, but omitting the 98% of the time he’s in the pocket but doesn’t fumble.

incidentally, taking this from purely a measurement perspective, the process is to identify the theory or theories on which you’re basing your measurement (Sing’s Formula & NFL Rules in this case), identify all aspects of the phenomenon that you want to measure, come up with indicators for each of these aspects (or as many as is possible), and ten collect the data. making sure the measure conforms with the underlying theory(ies) is just as imporant as throwing everything at the wall and seeing what makes R-squared get better.

by (Florida) Danny Tuccitto on Dec 4, 2009 2:15 PM PST up reply actions  

Re: your second paragraph

That’s very much true. One thing that I don’t think you’ve addressed, however, is whether this is an illustrative or predictive statistic. Essentially, you have shown corrolation between ‘a lower fumble rate’ and ‘winning rate’,, but you’ve not demonstrated causation.

If, for example, the rate of fumbling was caused by the same thing that caused winning (say, for example, ‘offensive line strength’, however you care to measure that), then you’d expect the two statistics to be show a strong corrolation.

I suspect that you think tilting at windmills means something other than what it does

by bobnothing on Dec 5, 2009 10:51 AM PST up reply actions  

Awesome work Danny..

Holy (site decorum), you do this in your spare time?

Well, we're waiting....

by drummer on Dec 4, 2009 11:31 AM PST reply actions  

well...

i love working with NFL stats, obviously.

but also, i just couldn’t stand the fact that i was giving you guys ridiculously stupid stats like fumbles and interceptions when talking about Total Ball Insecurity. it was for my own piece of mind too, you know. :-)

by (Florida) Danny Tuccitto on Dec 4, 2009 11:35 AM PST up reply actions  

It would be interesting..

To see how you can use your type of analysis in a different sport, like say the PGA Tour. Combine stats with the psychology, and maybe it can explain the how and why of Sergio Garcia choking short putts.

Well, we're waiting....

by drummer on Dec 4, 2009 11:41 AM PST up reply actions  

haha...

for the record…sergio’s not the only one that chokes on short putts…

so does this guy —→ danny

by (Florida) Danny Tuccitto on Dec 4, 2009 11:43 AM PST up reply actions  

Wow, this is excellent. I’m no stat nerd but I can’t think of anything wrong with it.

The next step, I think, would be to automate the generation of the stat and go back through previous seasons as long as we have data for, then look at correlation to winning.

Nobody likes money

by fwoty oz on Dec 4, 2009 11:36 AM PST reply actions  

yes, that is the next step...

seeing how the Niners’ BS Rates have fluctuated throughout their history and seeing if that fluctuation matches their winning and losing seasons.

by (Florida) Danny Tuccitto on Dec 4, 2009 11:39 AM PST up reply actions  

Are you having to manually enter in the data into a spreadsheet or SSS or is there a way to gather all these stats in a comma delimited or some kind of database?

Nobody likes money

by fwoty oz on Dec 4, 2009 11:42 AM PST up reply actions  

manually...

entered it into SPSS, just for the purposes of making the IR SOS adjustment though. all of the stats are copy-and-pasteable from various sites around the net, so took care of most of this in Excel.

by (Florida) Danny Tuccitto on Dec 4, 2009 11:45 AM PST up reply actions  

You should present this to FO if you haven't already

Bet they could come up with an automated way of doing it as I’m sure they have all the necessary stats in a separate database.

How do muffed snaps figure into this formula? Let’s say your long snapper screws up the snap and the opposing team recovers—that’s not really a run nor a pass.

Same with a muffed snap during a regular drive.

by smileyman on Dec 4, 2009 11:48 AM PST up reply actions  

i'm pretty sure...

bill or aaron or one of the readers will come across this and forward it along to FO for one of their “extra points.” i’m not much of a self-promoter to begin with, but this was a post that i wanted on NN because of its basis in singletary’s formula.

by (Florida) Danny Tuccitto on Dec 4, 2009 11:57 AM PST up reply actions  

haha...

just noticed the XP’s been signed, sealed, and delivered. thanks bill.

by (Florida) Danny Tuccitto on Dec 4, 2009 2:01 PM PST up reply actions  

If you could find a mine-able data source (flat text file or database) with the relevant simple statistics I could whip something up to do it for you.

Nobody likes money

by fwoty oz on Dec 4, 2009 11:49 AM PST up reply actions  

Hmm, that’s something. Although you’d still be copy pasting 4 or 5 CSVs per team per year.

Nobody likes money

by fwoty oz on Dec 4, 2009 12:13 PM PST up reply actions  

I could probably

write a tool to extract the info into a DB or CSV if I were given the source CSVs

Sharlon Schoop - de favoriete Nederlandse honkbalspeler van McCovey Chronicles.
You always have to be one step ahead of your drunk friends
--Daisy Owl

by Viliphied on Dec 4, 2009 1:41 PM PST up reply actions  

Ya, this is what I was looking at. My thought was to generate the stat for every team in the league for as many years as football-ref had data for. But, having to copy+paste 5 CSV’s per team per year (there’s no download) is what I was hoping to avoid.

Nobody likes money

by fwoty oz on Dec 4, 2009 1:53 PM PST up reply actions  

oh wow they don't

that sucks

Sharlon Schoop - de favoriete Nederlandse honkbalspeler van McCovey Chronicles.
You always have to be one step ahead of your drunk friends
--Daisy Owl

by Viliphied on Dec 4, 2009 2:01 PM PST up reply actions  

glad you guys are...

coming face to face with why doing any kind of meaningful NFL stat analysis is such a pain. unlike baseball, the quality of the data, both informationally and in terms of accessibility, is in the stone age.

by (Florida) Danny Tuccitto on Dec 4, 2009 2:03 PM PST up reply actions  

i should add...

that’s also why FO’s play-by-play database and game-charting project is seriously the best thing to happen to football since the 5-yard chuck rule.

by (Florida) Danny Tuccitto on Dec 4, 2009 2:04 PM PST up reply actions  

seriously

if PFR had downloadable CSVs, it’d be simple, you just download the CSV, load it with the tool and you’re done. You’d still have to download 5 CSVs/Team/Year, but that’s what, like an hour or two’s worth of work? nothing.

Sharlon Schoop - de favoriete Nederlandse honkbalspeler van McCovey Chronicles.
You always have to be one step ahead of your drunk friends
--Daisy Owl

by Viliphied on Dec 4, 2009 2:17 PM PST up reply actions  

The frustrating thing is PFR obviously HAS a database of all this information. So it exists. We just can’t get at it.

Nobody likes money

by fwoty oz on Dec 4, 2009 2:43 PM PST up reply actions  

Here’s 15 years of data in CSV format for $99:

http://www.armchairanalysis.com/nfl-team-stats.html

I don’t know why the NFL doesn’t just make this information downloadable for free and put these handicappers out of business.

Nobody likes money

by fwoty oz on Dec 4, 2009 2:52 PM PST up reply actions  

sorta kinda ish

not really though

Sharlon Schoop - de favoriete Nederlandse honkbalspeler van McCovey Chronicles.
You always have to be one step ahead of your drunk friends
--Daisy Owl

by Viliphied on Dec 4, 2009 3:37 PM PST up reply actions  

That doesn’t appear to have team stats, and also is unofficial, as opposed to the stats on the actual site, which are official.

Sharlon Schoop - de favoriete Nederlandse honkbalspeler van McCovey Chronicles.
You always have to be one step ahead of your drunk friends
--Daisy Owl

by Viliphied on Dec 4, 2009 3:38 PM PST up reply actions  

Punters/kickers

Love this post FD. My question is if a punter drops the ball or gets blocked/ holder on a 3pointer “muffs it” would that not also apply to the formula?

by tanos135 on Dec 4, 2009 11:47 AM PST reply actions  

You beat me by about 10 seconds

Just asked the same question regarding muffed snaps.

by smileyman on Dec 4, 2009 11:48 AM PST up reply actions  

yeah...

those are the gaps in the stat, but i can’t really think of an easy way to incorporate those things. just from a measurement perspective, those things are so unbelievably rare that the amount of extra winning variability that BS rate would explain were i to include them would be microscopic. in other words, from a cost-benefit analysis, the diffculty of gathering non-fumble-lost muffed long snap data, non-fumble-lost muffed QB snap data, etc., outweighs the R-squared benefit.

also, the increase in the sample size of “opportunities” would be so small, that BS Rate would hardly change, if at all, given that we’re already talking about an average fumbling opportunity sample size per team of around 765. adding a muffed snap here or there, or the total number of muffed snap opportunities per team, isn’t going to affect BS Rate to any meaningful degree.

by (Florida) Danny Tuccitto on Dec 4, 2009 11:56 AM PST up reply actions  

in other words...

while i’d like to add that stuff in, i’m not that concerned about their omission affecting the trustworthiness of the stat.

by (Florida) Danny Tuccitto on Dec 4, 2009 11:59 AM PST up reply actions  

Just to spite you, some team is going to muff 9 snaps on special teams this weekend.

I don't know about that, to the groin.

by howtheyscored on Dec 4, 2009 12:00 PM PST up reply actions  

haha

for sure. DAL is going to put tony romo back at holder on FGs.

by (Florida) Danny Tuccitto on Dec 4, 2009 12:01 PM PST up reply actions  

Great job with the post Danny

I read the title and wondered what the “BS” could stand for. To some BS probably doesnt stand for Ball Security, lol.

But looks like Ball Security fits pretty well with formula for winning, especially adjusted the way you did it.

So since BS explains almost 50% of the variance in the data of what deteremines teams winning or losing, what other factors combined in a multi-variate approach will bring up the R squared to a higher value? To get an idea of which components of Formula for Success and other football stats correlate highest with winning…

by fortyniners on Dec 4, 2009 12:03 PM PST reply actions  

When I saw the headline I thoght Adjusted BS rate...

was going to be a little different. You know, the rate of BS is proportional to number of losses in a row using metrics such as how often Coach Singletary uses the phrase “workiing his tail off” and “we just have to correct that.”
I appreciate all your work and look forward to it every week.

by Raj49 on Dec 4, 2009 12:04 PM PST reply actions  

the three that immediately come to mind are...

strength of schedule, pass offesnse DVOA, and pass defense DVOA…of course, you’d have to remove interceptions and fumbles from the DVOA stats to avoid the multicollinearity problem i talked about in the footnotes. also, as i’ve said elsewhere, strength of schedule is great as a retrospective predictor, but pretty crappy as a prospective predictor. i could probably get the R-squared up to about 75% by adding the two DVOAs though.

by (Florida) Danny Tuccitto on Dec 4, 2009 12:07 PM PST up reply actions  

oops...

i was responding to fortyniners here…and below in my p.s.

by (Florida) Danny Tuccitto on Dec 4, 2009 12:09 PM PST up reply actions  

yep, thanks.

pretty much play better, and you’ll usually get the win.

by fortyniners on Dec 4, 2009 12:32 PM PST up reply actions  

p.s.

yeah, like FO, i find the naming of stats to be an opportunity for making fun of the acronyms people come up with when they develop a stat.

by (Florida) Danny Tuccitto on Dec 4, 2009 12:08 PM PST up reply actions  

yep...

having BS in the title was an intentional hook on my part. nice to see it worked. also, thanks.

by (Florida) Danny Tuccitto on Dec 4, 2009 12:09 PM PST up reply actions  

One other question

Do you grade onside kick attempts differently than a regular kick attempt?

by smileyman on Dec 4, 2009 12:22 PM PST reply actions  

do you mean...

the return of an onside kick vs. the return of a non-onside kick? if so, that would be no. a player returning a kick has an opportunity to fumble the ball regardless of whether its of the onside variety or not. if you’re talking about a player on the receiving team muffing a loose onside kick, i’m pretty sure those aren’t counted as fumbles in the NFL stats, so there’s nothing to worry about there.

by (Florida) Danny Tuccitto on Dec 4, 2009 12:24 PM PST up reply actions  

What about

if the kicking team recovers an onside. Is that counted as a TO. (and yes I agree with your earlier statement that it happens to little to effect the formula) this is just more of a curiosity for me.

by tanos135 on Dec 4, 2009 12:31 PM PST up reply actions  

if the kicking team recovers an onside...

then, by rule, they can’t advance the ball. so if the recovering player fumbles, it’s not actually a fumble. the plays blown dead upon recovery. it also wouldn’t be considered a “fumble” by the receiving team because, according to the definition of fumble, the receiving team never had possession of the ball to begin with.

by (Florida) Danny Tuccitto on Dec 4, 2009 12:34 PM PST up reply actions  

I agree

with smiley and thank you FD for the answer.

by tanos135 on Dec 4, 2009 12:37 PM PST up reply actions  

Seinfeld
I’ve come to the conclusion that I’m the person I’ve been waiting for.

Reminded me of the Seinfeld episode where Jerry meets the woman just like him:

Jerry: Now I know what I’ve been looking for all these years……myself! (Kramer is speechless)

I’ve been waiting for me to come along and now I ’ve swept myself off my feet.

by David Fucillo on Dec 4, 2009 12:53 PM PST reply actions  

glad you caught the reference...

it was two-fold though…the prez used that line “we’re the ones we’ve been waiting for” a lot during the campaign

by (Florida) Danny Tuccitto on Dec 4, 2009 12:57 PM PST up reply actions  

some minor quibbles

Interception rate is straightforward, but I am not sure I like your fumble rate calculation, although the quibbles are probably so minor as to not change any results. I would however, throw out 4th down (and end of half) interceptions unless they are returned for TDs (obviously not going to change much)…

Almost all fumbles occur when a player is HIT. The exception are QB/C and QB/Runner exchanges. So I would use “times tackled” as a better denominator for fumble%. So, I would not use imcompleted passes, but rather sacks + QB rushes as fumble opportunities. I would also subtract TDs and any rushes/catches/returns that end up out of bounds.

Alternatively, you could make this simple and just use “plays” as the the denominator. This has some nice properties:
1) You reward a team for running the ball more (less chance of turnover overall)
2) Interceptions and Fumbles have the same denominator, making them comparable (although of course, field position aside a fumble is only 1/2 as bad as an INT).

Another interesting way to do this might be to take time of possession as the denominator – ignoring defensive fumbles

At the expense of losing individual stats (you aren’t checking which player fumbles)

That should keep you busy with play-by-play gamebooks for a while!

FIRE BRIAN SABEAN... UNLESS HE KEEPS DRAFTING WELL. .. AND SIGNS UNDERRATED PLAYERS LIKE AFFELDT OR PHELPS. .. OR ALRIGHT WHO'S PLAYING WITH THE ALIEN MIND-SWITCHING RAY?
-------
PARPG- Indy post-apocalyptic roleplaying game currently in early planning stages.

by zenbitz on Dec 4, 2009 1:47 PM PST reply actions  

Here's the thing

if you throw out end of half or game INTs (because of desparation heaves), you have to throw out any that are returned for TDs. You can’t choose just part of the variable.

I wonder what percentage of fumbles are actually on the handoff vs being hit.

by smileyman on Dec 4, 2009 1:57 PM PST up reply actions  

definitely plenty of ways...

to improve the stat. one thing no one’s mentioned yet is that fumbles by defenders only occur when they’re actually returning an interception or fumble recovery. using defensive fumble recoveries and defensive interceptions in FOPPS, as i do, assumes that all fumble recoveries and defensive interceptions are returned. that’s hogwash of course. a non-trivial number of defensive fumble recoveries occur at the bottom of a 3,000-pound pile, so barring superhuman strength and the ability to keep one’s knee/shin/ankle/thigh/forearm/bicep/chest off of the ground while at the bottom of the pile, um, yeah, those fumble recoveries aren’t being returned. likewise, there are plenty of INTs that occur in the endzone with no return (i.e., result in a touchback) as well as along the sideline in dotting-the-i fashion.

so, yeah, all kinds of ways to improve this. they just require a lot of work because these kinds of “defensive fumble recovery returns” and “interception returns” stats are hard to come by…and i’d venture to guess that, even if i found them, a non-returned INT or defensive fumble recovery would still count as a 0-yard return, not a non-return.

by (Florida) Danny Tuccitto on Dec 4, 2009 2:00 PM PST up reply actions  

Non returned INTs and fumbles

Are counted as 0 yards.

Here’s the perfect example. During the Atlanta game Bly intercepted a pass. He’s credited for an interception, a 31 yard return, and a fumble. The recovering Atlanta player is credited for a 0 yard return.

Incidentally that means that Bly has as many fumbles on the year as he does INTs.

by smileyman on Dec 4, 2009 2:32 PM PST up reply actions  

I still think it's a mistake to count incomplete passes

I would only count QB sacks + rushes + complete passes. The Out-of-bounds stuff is probably trivial. I would probably just throw out defensive fumbles on returns. Obviously a secondary effect.

FIRE BRIAN SABEAN... UNLESS HE KEEPS DRAFTING WELL. .. AND SIGNS UNDERRATED PLAYERS LIKE AFFELDT OR PHELPS. .. OR ALRIGHT WHO'S PLAYING WITH THE ALIEN MIND-SWITCHING RAY?
-------
PARPG- Indy post-apocalyptic roleplaying game currently in early planning stages.

by zenbitz on Dec 4, 2009 4:31 PM PST up reply actions  

i'm not sure...

i was arguing that it wasn’t a mistake.

keep the suggestions coming. the point i was making is that there are obvious places to improve it, provided that they stick with the “quick and appropriate” theme i developed in the post.

by (Florida) Danny Tuccitto on Dec 4, 2009 4:54 PM PST up reply actions  

I don’t see why you WOULDN’T include incomplete passes. Of course it’s a fumble opportunity.

An incomplete pass is just a fumble opportunity that didn’t result in a fumble.

Nobody likes money

by fwoty oz on Dec 4, 2009 10:24 PM PST up reply actions  

WOW This is some well thought out Stastical Computations

  Hats off to you sir! I had to read this TWICE to get a better understanding but once I was able to better understand your thinking, it made GREAT sense. I always considered Ball Security a good measure of a teams ability to execute and succeed, but I have NEVER seen the stat so thoroughly and exhaustively broken down to the very “Nth” degree !!!

  You should start your own website like Football Outsiders and take advantage of your Complete understanding of the statistical ramifications of certain aspects of the game. If you could somehow make this understood by the layman, you could probably make a profit on any website so completely through and painstakingly precise. I would certainly pay to have stats such as these to poor over and this adds a totally different degree of understanding to the game, and the hows and whys of winning and losing by computational math.

  On the other hand, I am not sure the average football fan would be able to fully appreciate the depth and thoroughness of these stats. I think football for some fans is more of an emotional reactionary process instead of a mathematical breakdown of statistical data. I can appreciate your hard work, and hope you DO decide to create a Website dedicated to the weekly statistical changes that effect teams positively and negatively. I am sure that those who like to place the occasional wager would find a website like that VERY profitable and would pay handsomely for your work. I am glad that I can see this kind of exhaustive and through computational work for free, but you really should consider finding someone who can help you create a Pay per View website that would help the average betting layman to have a better understanding of the hows and whys of winning and losing in football. There is certainly a niche of the Football Betting World who would find your work useful and profitable. I am not a gambler, but I can certainly see how these stats could benefit someone who is.

  Thank you for your efforts and keep up the great work! The Niners may not be very good both statistically and effectively, but this sort of computation helps me to understand WHY the Niners do not achieve the goals that all teams set at the beginning of the season. I feel more prepared to review past games using your formula and the way you have used it to explain Singletary’s list of goals or “Singletary’s Formula for Success”. You have made it easier to see the TRENDING of the team both positive and negative. As you have explained it, Singletary is dead on with his formula, and only helps to show how good a coach he is based on HIS FORMULA for success. I believe this can help explain the obvious turnaround the Niners have experienced this year compared to last year, based on Singletary’s formula and how close to his goals the team is able to get week to week. Thank you again for your hard work!!

Another year, another chance to hope for the team !!

by FaStRmAn on Dec 4, 2009 2:35 PM PST reply actions  

Great analysis

After reviewing Adjusted BS, I can see a credible case for Singletary’s insistence that the 9ers oftentimes beat themselves.

We rank very highly in defensive DVOA (#7 right behind of Pit, ahead of Minn), but poorly in defensive consistency (Variance is #24).

Seems like two areas of improvement that are within reach, especially as (if) our offense continues to develop.

Would you agree Florida Danny?

by FF09SF on Dec 4, 2009 3:19 PM PST reply actions  

I have to change my pants now

Hope you’re happy.

On a serious note, that was a fantastic writeup and an ingenious way to go about giving Total Ball Security a statistical backing.

by Cruithear on Dec 4, 2009 3:29 PM PST reply actions  

I'm probably too dumb to understand your formula. (but I still love it)

I have an issue with counting Int and fumbles per attempt to calculate total BS.

The way you have it set up seems to completely eliminate the game-plan factor involved.
Int are much more likely than fumbles and that is exactly why Singletary wants to run the ball more often than pass.

 A team that only passes the ball 100 times a season and makes 2 int should not have a worse BS than a team that passes1000 times and makes 10 int . That’s 2 TO vs. 10 TO rather than 1INT/50 vs.1INT/100. Wouldn’t calculating int and fumbles per total plays or time of possession achieve a much more realistic result?

If Bochy coached the Warriors Bengie Molina would start every game at PG.

by cybermaldonado on Dec 4, 2009 3:31 PM PST reply actions  

I think what you’re saying is that the rate stat is valuable, but would probably be more valuable when paired with a counting stat for context.

I don't know about that, to the groin.

by howtheyscored on Dec 4, 2009 3:38 PM PST up reply actions  

I think that's accounted for
The next step is to combine IR and FR so that we come up with our BS Rate. Because we want to measure Total Ball Security, rather than Total Ball Insecurity, the first thing we have to do is subtract each of these from 100%. Then, in order to get BS Rate, we have to calculate what’s called a weighted average of IR and FR because Pass Attempts and FOPPS are not equal. You can click here for a thorough discussion of weighted averages, but the bottom line is that, if we simply added IR and FR, then IR would be make up 50% of BS Rate, despite the fact that Pass Attempts only makes up about 30% of all ball insecurity opportunities. In other words, we’d be giving IR 20% more of an impact on BS Rate than it deserves. Just to make things as clear as possible, here’s the equation for BS Rate:

Sharlon Schoop - de favoriete Nederlandse honkbalspeler van McCovey Chronicles.
You always have to be one step ahead of your drunk friends
--Daisy Owl

by Viliphied on Dec 4, 2009 3:40 PM PST up reply actions  

and actually

looking at the math, it is.

Sharlon Schoop - de favoriete Nederlandse honkbalspeler van McCovey Chronicles.
You always have to be one step ahead of your drunk friends
--Daisy Owl

by Viliphied on Dec 4, 2009 3:41 PM PST up reply actions  

Showoff.

I don't know about that, to the groin.

by howtheyscored on Dec 4, 2009 3:53 PM PST up reply actions  

I’ll have to come back and look at this later. Friday evening and my brain is in no condition to comprehend this completely despite my background in statistics. lolz

If Bochy coached the Warriors Bengie Molina would start every game at PG.

by cybermaldonado on Dec 4, 2009 3:59 PM PST up reply actions  

the relevant equation

BS Rate = {[(1 – IR) * Pass Attempts] + [(1 – FR) * FOPPS)]} / (Pass Attempts + FOPPS)

Sharlon Schoop - de favoriete Nederlandse honkbalspeler van McCovey Chronicles.
You always have to be one step ahead of your drunk friends
--Daisy Owl

by Viliphied on Dec 4, 2009 4:02 PM PST up reply actions  

BS Rate is a weighted average of FR and IR

that gives greater weight to FR than IR because the average team’s total ball insecurity opportunities come 70% via fumble opportunities and 30% via interception opportunities. that’s the basic idea, and it addresses the issue you’re raising.

by (Florida) Danny Tuccitto on Dec 4, 2009 4:57 PM PST up reply actions  

BS rate

I think that like pornography and the Supreme Court, we all know BS when we see it (even if we don’t understand it).

by seafood lover on Dec 4, 2009 4:25 PM PST reply actions  

Good job. Looks like a good creative measure.

That must have taken some time to compile. You’re building a nice little resume.

by goatfather on Dec 4, 2009 6:41 PM PST reply actions  

Good God Dude

You Kill me.

Try this. The Titans started out 0-6.

During that 0-6 stretch they had (9 INT’s, 15 Fumbles, 9 Fumbles lost).

They have since gone 5-0. During that stretch they had (1 Int, 4 Fumbles, 2 Fumbles lost).

You don’t have to be a NASA scientist to see the difference there, now do you?

’Nother example. Earlier this season the Arizona Republice reported that in the Ken Whisenhunt era, the Cards were 18-0 when they WON the tutnover battle, and 1-17 when they LOST the turnover battle.

Why don’t you guys put down the spreadsheets, turn off the computers and the mind numbing calculations and just WATCH the f’ing games!.

Watch knowing that the team that WINS the turnover battler has a MUCH, MUCH better chance of wining the game that the team that loses the turnover battle.

You don’t have to be a NASA scientist (or a card carrying member of FO) to see/know/understand that!

KISS. Keep It Simple Stupid.

When it comes to BALL SECURITY, it really is that simple.

by GeoMak on Dec 4, 2009 8:30 PM PST reply actions  

so what you're saying is...

if my intention was to numb your mind with calculations, then i was successful, right?

p.s. never did i think simple division would be considered a mind-numbing calculation.

p.p.s. thanks for wasting your time once again reading one of my posts.

by (Florida) Danny Tuccitto on Dec 4, 2009 8:54 PM PST up reply actions  

Don’t feed the troll.

I don't know about that, to the groin.

by howtheyscored on Dec 5, 2009 10:07 AM PST up reply actions  

The point

is to be able to quantify it. Sure you can point to anecdotes like that, and sure we all know that ball control is absolutely important.

But can you point to it statistically.

Until today you couldn’t.

There’s a difference in “knowing” something as an article of faith and “knowing” it because math and science show it to be so.

by smileyman on Dec 4, 2009 9:08 PM PST up reply actions  

Lemme help you boys out here.

Essentially, winning at the NFL level is about TWO things.

1. (that MS addressed): Ball security. You can analyze it to DEATH, but SIMPLY put (I know that word simply drives some people CRAZZYYYYY) but simply put, the team that turns the ball over LESS has a much higher chance of winning the game.

2. (that MS didn’t address) BIG PLAYS. Some define big plays as those 20+ yards. Other (such as myself) use the ‘eyeball test’.

In those two variables are football games won. PERIOD.

Classic case study.

2006. The 5-0 Chicago Bears at the 1-4 Arizona Cardinals. Rookie Matt Leinart was making his second start for the Cards. Rex Grossman starting for the Bears. (For all you Grossman haters – The simple fact is that Grossman was the offensive player of the month for the NFC in September of 2006 as he led the Bears to a 5-0 start. He threw 10 TD passes (as opposed to 3 INT’s ) in those first five games. He was probably the single biggest reason (among many) that the Bears were 5-0 at that time.

When a team starts out 5-0 the odd on them making the playoffs are astronomical (and I’m sure Florida Danny knows the EXACT number there).

But he played one of the worst games EVER, for a QB, in NFL history that night in AZ. 4 INT’s and 2 lost fumbles. 6 TO’s alone by old Rex. SIX! The odds of winning in that situation are almost zilch (I’m sure Florida Danny knows the EXACT odds down to four decimal places too).

The Bears were down 0-20 at halftime. And won 24-23! The Bears were who they though we were (thanks Denny Green)!

How did the Bears win a game they had NO business winning (after Grossman himself coughed it up SIX times)?

SIMPLE!

Four BIG plays!

1. Brian Urlacher rips the ball away from Edgerrin James (who was being held up by four other Bears). If that happens on the street they all go to jail for assault and theft. Charles Tillman scoops up the fumble and runs it in. First Bears TD!

2. Rookie Mark Anderson crashes into Leinart’s blind side jarring the ball loose. Mike Brown scoops it up and walks into the endzone. Second Bears TD!

3. Rookie Devin Hester records his second punt return TD of the season (on his way to six total return TD’s). Third Bear TD!

THREE BIG PLAYS BY CHICAGO WIPED OUT SIX TO’S.

4. Finally this. The Cardinals had a chance to win it in the closing seconds on a Neil Rackers FG. Last season (in ole Sun Devil Stadium) Rackers had a career year. He banged something like 6-8 50+ yard FGs, setting or tying an NFL record that season. He was, however, struggling this season in the Cardinals first season in their new stadium.

Maybe he missed old Sun Devil Stadium. Maybe it was the pressure of a prime-time, MNF game.

End result? He missed. The Cards lost. If he makes it (his potential ‘big play’) all the Bear heroics are for NAUGHT.

That’s a classic example (and a RARE example) of ‘Big Plays’ overcoming a (big) negative TO margin.

It’s real simple folks.

The two BIGGEST indicaors of success in the NFL:+

1. Who turns over the ball LESS.

and/or

2. Who makes the most (biggest) Big Plays!

That’s pretty much it folks.

No membership to NASA required (LOL)!

by GeoMak on Dec 4, 2009 9:52 PM PST up reply actions  

eyeball test?

I have to say that when you use an “eyeball test” it’s a lot easier to never be wrong.

by David Fucillo on Dec 4, 2009 10:06 PM PST up reply actions  

You can't eyeball a big play in an NFL game?

You’re kidding, right?

Dude, get serious. Really.

by GeoMak on Dec 4, 2009 10:12 PM PST up reply actions  

Again, lemme help ya out here

My good friend Brian Billick talked about this very thing on Fox earlier in the year.

Essentially he said this:

A) Throw out ALL the mind-Numbing stats.

B) Football games are won by a combination of ‘TO margin" and ’Big Plays.’

He said, on national TV, what I’ve been saying for YEARS!

Now, understand, that Brian Bilick was once victimized by one of the biggest ‘big plays’ in NFL history.

What big play is that GeoMak, you ask?

This one.

In 1998, Billick was the OC of the Minnesota Vikings under HC Dennis Green. The Vikings offense set a (then) NFL record by scoring 556 points( since broken by the 2007 Patriots).

These were the Vikes of Randall Cunningham, Robert Smith, Randy Moss and Cris Carter.

In the NFC Championship game agianst Atlanta, with a chance to go to the SB, Gary Anderson lined up for a 38 yard FG at the end of the game.

Anderson was the FIRST kicker (that season) to be perfect ALL season ( he made all of his FG’s that year going 39- for 39 and he made ALL 67 extra points that year).

GARY Anderson made EVERY kick he attempted that season . . . EVERY KICK! . . . except the one to WIN the NFC Championship and send the 1998 Vikings to the SB.

He missed (wide left) and Atlanta eventually won the game and represented the NFC in the SB that season.

Turnovers. & Big Plays.
It all comes down to that.

The rest in pretty much nonsense.
Want to argue with Geomak? Fine.
Just understand that you are also then arguing with Brian Billick.

Sorry!

by GeoMak on Dec 4, 2009 10:38 PM PST up reply actions  

Dude, he's not arguing with you

It’s simply another way of looking at the exact same thing, only quantifying it.

If you don’t know what quantifying means that’s fine—you can move on.

If you don’t see the point in it, that’s fine—you can still move on.

Some of us like this kind of stuff.

by smileyman on Dec 4, 2009 10:41 PM PST up reply actions  

You'rre right smileyman

I don’t know what quantifying means.

That’s the point my lttle friend.

I don’t need a War & Peace sized book to understand what I KNOW in a SIMPLE sentence.

Sheesh!!!!!

by GeoMak on Dec 4, 2009 10:44 PM PST up reply actions  

If you don't know what quantifying means

you should probably stay out of any discussion involving statistics.

Just sayin’.

by smileyman on Dec 4, 2009 10:59 PM PST up reply actions  

settle down

I’m simply saying that referring to something as an “eyeball test” is a bit subjective when you just declare something a “big play” but have no objective criteria for what falls under that qualification.

by David Fucillo on Dec 4, 2009 10:44 PM PST up reply actions  

Look

I don’t neeed ‘objective’ criteria to know that:

A: Urlacher stripping the ball and Tillman running it in is a ‘big play.’
B: Anderson stripping the ball and Brown running it in is a ‘big play.’
C: Hester returning a punt 83 yards for a TD is a ‘big play.’
D: Rackers missing a game ending FG is a ‘big play.’

Are you kidding me?

What? I have to pore over HOURS of NFL stats, after that game, to see what does or does not OBJECTIVELY qualify as a ‘big play.’

With the utmost respect, you are embarassing yourself here!

(Sorry. Even though, at my advaced age, I use reading glassee, my eyes are still all I need to know when I see a big play (or not) in an NFL game).

by GeoMak on Dec 4, 2009 10:50 PM PST up reply actions  

embarrasing myself?

Why are you taking such great offense to this? We’ve got a post with material that a lot of people enjoy reading. You express your difference of opinion and I was simply pointing out something and you’re blowing up.

I never said that the plays you’re mentioning weren’t big plays. Not once. I am simply stating that I prefer a little more objective criteria when I’m assessing a situation. When I see objective criteria then I feel like I can have a better discussion because we’re all looking at the same thing.

While you and I can obviously agree many plays are big plays, the objective criteria will help in the gray areas. While a lot of plays are clearly big, there are some plays that might straddle the fence. If I elected to use an “eyeball test,” what’s to say my conclusion on a particular “gray area” play isn’t different from the conclusion you reach?

by David Fucillo on Dec 4, 2009 10:56 PM PST up reply actions  

Umm

You said:

“Eyeball test: have to say that when you use an "eyeball test" it’s a lot easier to never be wrong.”

Say What?

When did this become about ‘never being wrong?’

You guys: Pour over REAMS of stats.
Me: I use my EYEBALLS.

That’s the difference.

I guess you’re right, though. I pretty much am always right when I use my EYEBALLS to tell me waht happened in the game (as opposed to a pile of ‘numbers.’).

Sorry.

I may not be a NASA scientist but I know HOW to watch an NFL game and I know WHAT contributes to teams winning (and losing) -—-Turnovers and big plays.

Perfect Example? Last nights Jets game. Maybe if Sanchez DOESN’T defy his HC and DIVE for the 1st down instead of sliding . . . they probably don’t convert and maybe they lose the game.

Hard to see that in the ‘stats’ (now isn’t it)?

When it comes to ‘stats’ football and baseball are MILES apart. Some people (like me) understand that. Many, many others, however, don’t.

It’s just that simple.

by GeoMak on Dec 4, 2009 11:05 PM PST up reply actions  

You don’t understand the basic concept. This has nothing to do with 1 game.

And actually, you remind me exactly of the anti-stat people on baseball forums.

Nobody likes money

by fwoty oz on Dec 4, 2009 11:13 PM PST up reply actions  

so, um, yeah...

question: how do you put all this all-knowing-ness about football to use? i mean, it seems you like already know everything about football, and we should just come ask you rather than trying to figure it out for ourselves. please, omniscient one, tell us how you’re using your “eyeball tests?” i hope, with a perfect record of correctness like you have, you’re making serious money off of it.

by (Florida) Danny Tuccitto on Dec 4, 2009 11:15 PM PST up reply actions  

I'm just quoting Brian Billick

Who recently said (on FOX) what I’ve been saying for years.

Danny. I respect you. I really do. But please, for the love of God, DON’T tell me you know more about NFL football than Brian Billick..

Please tell me that! (Cause you most certainly do NOT – and neither do the boys at FO).

BTW: If you don’t believe me, use all of your powers of reseach to verfify what Billick recently said on NATIONAL TV (in fact, it was during a 49er game).

Recap (on what Billick said): There are a MILLION stats. The only two that REALLY matter are TO battle and who makes the most ‘Big Plays.’

Sorry.

by GeoMak on Dec 4, 2009 11:23 PM PST up reply actions  

Question for you then

Is a 20 yard pass a big play?

How about a 10 yard pass?

How about a 1 yard run?

by smileyman on Dec 4, 2009 11:54 PM PST up reply actions  

maybe if we just quit replying to him he will go away

"Pat is still just scratching the surface." - Coach Singletary on LB Patrick Willis

by 49erLou on Dec 5, 2009 11:36 AM PST up reply actions  

“, the team that turns the ball over LESS has a much higher chance of winning the game.”

That’s the basis of this. The idea is to quantify it. You can’t say “well team A had 1 int and team B had 2 ints so team A had a better chance of winning”. Not if team B threw 3x as many passes as team A.

Nobody likes money

by fwoty oz on Dec 4, 2009 10:28 PM PST up reply actions  

Give this a thought

Teams that score more than average points have a much higher chance of winning games.

But it’s definitely possible for Team A to score 30 points a game and go 12-4 and Team B to score 25 points a game and go 14-2.

When you’re looking at either team, points per game would still be interesting to look at, ya?

This stat just quantifies ball security in a way that you can compare to other teams.

Nobody likes money

by fwoty oz on Dec 4, 2009 10:35 PM PST up reply actions  

Winning & Losing in the NFL

Last week the Cards lost to the Titans.

The Cards won the TO battle (+1).

They lost the game, however,

Why?

Last (very important word – last) drive of the game.

Vince Young led the Titans on a 99 yard, 18 play drive to WIN the game.

I believe they converted three(or four) 4th down plays on that drive.

That’s pretty hard to do. Convert mutliple 4th down plays. But they DID!

Game – Set – Match.

All the stats in the WORLD really don’t matter anymore.

One (game ending) drive. Who will make the BIG PLAYS (Tennesse) and who won’t (Arizona)?

It’s really just that simple.

by GeoMak on Dec 4, 2009 11:18 PM PST reply actions  

Danny

The Titans have now gone for 0-6 to 5-6.

Is this because?

A) The ‘spark’ from new starting QB Vince Young?

B) The fact that RB Chris Johnson has three 85+ yard TD’s in the past 11 games. NO other RB in NFL history has ever had three 85+ yard TD’s in their career, let alone in an 11 game strectch?

C) The fact that they turned the ball over 18 times (in their first 6 losses) while only turning it over 3 times (in their 5 victories)?

What say you?

A? B? C? All of the above? None of the above? A combination of the three?

There has to be SOME reason wht they have gone form 0-6 to 5-0?

by GeoMak on Dec 4, 2009 11:32 PM PST reply actions  

Let’s try re-reading what has been said. You really are not understanding the basic concepts. I don’t intend to be rude but you aren’t making posts that deserve responses.

Here: The baseball team with the highest OPS rarely wins the most games. OPS is still a very valuable stat at measuring hitting performance. There’s no difference here.

Nobody likes money

by fwoty oz on Dec 4, 2009 11:39 PM PST up reply actions  

Just stop it

You have no clue what you’re doing here.

Quantify—express as a number or measure or quantity; “Can you quantify your results?”

Florida Danny is taking turnover ratio and making it a number that you can easily measure towards success.

It’s no different than using DVOA, or 3rd down percentage completion, or QB rating, or any of the other myriad statistics.

It’s a tool that helps us understand in a more scientific way how the game of football works.

Florida Danny isn’t saying anything differently than what you’re saying with those Belichick quotes.

He’s expressing it in a way that can be measured and applied to every game.

But you really should stop arguing against it, because you’re really making yourself look foolish.

by smileyman on Dec 4, 2009 11:53 PM PST up reply actions  

Hey Danny..

Can you qualify the effect of GeoBeck in a tabloid fueled culture, and how the GeoBeck demographic in the Digital Age has declined in value when past being able to drive over 35 MPH?

Well, we're waiting....

by drummer on Dec 5, 2009 3:52 AM PST reply actions   2 recs

haha

the glenn beck photo-shoot induced manufactured tears pic…

we should start using that in the game threads when something bad happens to the niners

by (Florida) Danny Tuccitto on Dec 5, 2009 9:49 AM PST up reply actions  

If you want to see me curse, you’ll post pictures of that jerk.

I don't know about that, to the groin.

by howtheyscored on Dec 5, 2009 10:08 AM PST up reply actions  

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