|
|
Around The Horn...
How Accurate Are First
Impressions?
|
|
Hi Folks, Greg Alan here.
In Week #2 Around the Horn takes a
more statistical turn as I'd like to share some special research with you. Let's
dig in...
One week is just that, one game for each team. Not much
to go on. However, PASS YDS PER ATTEMPT (PYPA) is one measure that does a good job at predicting a team's
offensive success over an entire season (using only one week of data).
Week #1 PYPA is a better predictor than points scored, rushing yards and plenty of other
measures. In fact, when you combine PYPA with pass attempt data, history shows you have
a solid leading indicator. Again, PYPA is even a better leading indicator than
points scored.
THE SECRET FORMULA
On opening day if an NFL team throws the ball 25 or more times and, in the process,
is able average 8.25 or more yards per passing attempt, 96% of the time, that team will end up having a reasonable offense over the following
16 weeks. In fact, 62% of the time,
the team will end up being a high-end NFL offense.
Below I'll show you what teams met the 25-8.25 criteria in 2007.
Keep in mind, this is 100% object analysis (no biases) based on a single and
very powerful objective measure.
|

|
PYPA PREDICTS GOOD THINGS
|
Player
|
Team
|
Attempts |
YDS/Att
|
|
Tony
|
Romo
|
Dal
|
24
|
14.4
|
|
Jason
|
Campbell
|
Was
|
21
|
10.6
|
|
Tom
|
Brady
|
NE
|
28
|
10.6
|
|
Matt
|
Schaub
|
Hou
|
22
|
10.2
|
|
Peyton
|
Manning
|
Ind
|
30
|
9.6
|
|
Matt
|
Hasselbeck
|
Sea
|
24
|
9.3
|
No surprises here as Indy and New England make the cut!
Tony Romo and Dallas technically fell one pass attempt short, but lets include them in the elite circle. Even if Romo lost 20-yards on his next thrown, Dallas would have easily made the 25-8.25 criteria.
Also, the same deal with Seattle. Even if Hasselbeck lost yardage on his next throw, Seattle would
be in.
STUD OFFENSES
INDY
NE
DALLAS
SEA
OFFENSES THAT COULD SURPRISE
HOUSTON
WASHINGTON
To learn more about this finding, please read below...
|
|
----
Here is my original
PYPA research that lead me to the 8.25, 25 finding....
NFL Week #1 is finally here. Now it’s time to watch as much live NFL
action as you can. In addition, after the games, you can check out all the
highlights. If you're really working overtime, you
might examine every line of every NFL Box Score.
|
|
After you take all that in, is it easy to spot which squads will have a fairly
decent offense and which will have a hard time moving the ball? If an offense
only generates a FG in Week #1, that’s not a good sign. Clearly, if a team
gets shut out on opening day, that’s really a bad sign! Or is it? Before you
answer, you might want to take a look at this study. The findings could surprise
you!
|
|
We examined every NFL regular-season game played over a six-year period. We looked at Week #1 offensive output and compared it to
rest-of-season production. That gave us 180 case studies to explore. The table
below illustrates just a handful of our case studies.
|
|

|
|
TABLE I:
NFL Case Studies
|
Case Study |
Week #1
Total YDS |
Avg. Total Yards
Week #2-17 |
| #1 |
201 |
337 |
| #2 |
407 |
363 |
| #3 |
250 |
339 |
| #4 |
380 |
300 |
| . |
. |
. |
| . |
. |
. |
| #179 |
205 |
355 |
| #180 |
396 |
344 |
| NFL Average |
332 |
335 |
|
|

|
|
In addition to the above, we reviewed 15 other variables for each Team-Year
combination. Suffice it to say, we did a lot of number crunching. So what did we learn?
|
|
First, let’s look at those teams that only generated 0-3 points on opening day.
We’ll pit those inept offenses against teams that really “showed us something”
in Week #1. Specifically, offensive units that came out on opening day and put
up 41 or more points! Let’s review Table-II and see how the Week #1 mavericks
and duds performed during the rest of the NFL season.
|
|

|
|
Table-II:
Using Points Scored as a Predictor
|
Point Scored
in Week #1 |
Average Total Yards
Week #2-17 |
| 0-3 |
317 |
| 41 or more |
325 |
|
|
Guess what? As you can see from the above table, over the remainder of the NFL
season, there is barely a difference between those teams that looked grand on
opening day and those teams that just couldn’t move the ball. It’s amazing, but
true. That leads up to our first finding.
|
|
FINDING #1: Simply looking at extreme Point Production Totals in Week #1 provides little help in
forecasting total team offense in Weeks #2-17.
|
|
If offensive Point Production isn’t a good a predictor, then what is? We’ve all
heard about the importance of a good running game in the NFL. But, is offensive
rushing production in Week #1 a solid predictor of team offense?
|
|

|
|
TABLE-III:
Using Total Rushing Yards as a Predictor
|
Rushing Yards
Week #1 |
Avg. Total Yards
Week #2-17 |
| 0 to 55 |
335 |
| 56 to 184 |
334 |
| 185 or more |
337 |
|
|

|
|
TABLE-IV: Using Yards per Rush as a Predictor
|
Yard/Rush
Week #1 |
Avg. Total Yards
Week #2-17 |
| 0.0 to 3.2 |
331 |
| 3.2 to 4.2 |
335 |
| 4.2 to 5.5 |
337 |
| More than 5.5 |
331 |
|
|

|
|
After consulting Table-III and Table-IV, we see rushing
metrics offer us very little predictive capability. Amazingly, teams that rack
up 185+ rushing yards on opening day, barely average more total yardage during
the rest of the season, than teams that generate 0-55 rushing yards on opening
day.
|
|
FINDING #2: Don’t
assume a team displaying a dominate rushing attack in Week #1 will have an
outstanding offense the rest of the season. Conversely, if a team doesn’t amass
big yardage on the ground in Week #1, don’t count that offense out.
|
|
If Point Production and
Rushing stats aren’t good guideposts for predicting offensive capabilities, what
objective measures are?
|
|
FINDING #3: As it turns out, Passing Yards per Passing Attempt (PYPA) is
one of the best objective predictors of future offensive production. However,
even PYPA has limits.
|
|
TABLE-V, Using PYPA as a Predictor
|
|
Week#1 Pass Yards Per
Pass Attempt (PYPA) |
Avg. Total Yards
Week 2-17 |
| 0.00 to 4.50 |
316 |
| 4.50 to 5.70 |
326 |
| 5.70 to 8.25 |
338 |
| more than 8.25 |
350 |
|
|
If a team’s PYPA is over 8.25 in Week #1, on
average, that team will generate 350 yards of offense per game during the rest
of the NFL season.
|
|
To further enhance forecasting accuracy, we will combine the PYPA statistic
with Passing Attempts.
|
|
Finding #4:
If, on opening day, an NFL team throws the ball 25 or more times and, in the process,
is able average 8.25 or more yards per passing attempt, you should take note. It
turns out, 96% of the time, that team will end up having a reasonable offense over the following
16 weeks. In fact, 62% of the time,
the team will end up being a high end NFL offense.
|
|
In addition to identifying teams that should do reasonably well, the PYPA statistic can be used
to find teams that will have problems on offense.
|
|
To find teams most likely to struggle on offense, locate ones that have a PYPA less than 5.1 and
gained 0-80 rushing yards in Week #1. Usually, 3 out of 4 teams meeting the
‘5.1-80’ criteria will perform below NFL norms. In addition, they will usually
only average about 300-315 yards of offense per game the rest of the
season.
|
|
Some Ways to Exploit this Research:
As Week #1 ends, that’s the time to put these
principles into practice. Think about these findings and see how they might work in your league.
|
|
First, look for some waiver wire pickups. Using these findings, pick up
an available defense that will be playing a weak offense several times in the coming weeks.
|
|
Also, look for available player
talent on a team that shows promise according to these guidelines. This research
suggests opportunities exist to find sleepers and avoid duds.
|
|
In addition, look for value and try
to trade for quality talent on a team that may have struggled based on
traditional stats in Week #1, however, had a decent PYPA.
|
|
Also consider how you might exploit
a ‘big-name’ player on your roster, if his team is likely to struggle on offense
based on these findings. In making the trade, be sure to get quality for your
‘big-name’ talent.
|
|
Finally, after you use this research
to fit your situation, be sure to strike while the iron is hot!
|
|
|