Those of you that have had a chance to read some of my past articles may have come across a write-up discussing the predictive power behind Play-book Execution Penalties, which are flags thrown when plays break-down, usually on offense. Penalty calls that fall into this category include infractions such as: Intentional Grounding, Ineligible Receivers, Illegal Shifts and Motions, Too Many Men on the Field, and so on.

PBEP's are not the only measure of team penalties that have been shown to be a profitable tool for spread handicapping: Offensive Holding calls are also the basis for a situation that has produced big profits over the past 7 years-- a situation which has been highly effective even with only one Primary condition involved.

The condition I am speaking about is simple, and involves looking at teams that currently have a higher per-game average for Offensive Holding Penalties Against (OHPA) than their current opponent.

As an example, a team that has played 4 games and been flagged 9 times for Offensive Holding during this stretch, would have an OHPA of 2.25 (9 / 4) and would therefore be subject to this situations logic when facing an opponent with an OHPA average of 2.24 or less.

As you might expect, teams with a higher OHPA have not been a good wager over the past 7 seasons. You might be surprised; however, at just how badly they have fared.

Since 2001, teams with a higher OHPA have been a brutal 518-602 (46.3%) ATS when playing between Week 4 and 15, creating a profit of $3,220.00 at 10/11 odds with $110.00 wagers against the team in question. Not bad for a relatively simple situation with 1 Primary condition (OHPA > OP OHPA) and a 'Secondary' stipulation (i.e., 'tightener') excluding games very early, and very late in the season.

If there is one thing I have learned through the process of handicapping hundreds of NFL games over the past decade-or-so and studying countless trends during this same time period, it's that, the stats that are 'off the beaten track' are usually the ones that produce the most profitable 'stand-alone' trends'--meaning, those that are based one single condition or at least a minimal amount of conditions.

You will be hard-pressed to find another situation based on the more common measurements of team skill, such as rushing and passing stats, that could produce a similar result of +/- 85 wins ATS over a 1000-1100 game stretch, especially when it involves only a single 'building block', or, 'Primary' condition.

The reason for this is actually fairly simple: Most of us know that Vegas sets the NFL line based predominantly on public perception of team strength. This is a point which even most novice handicappers are aware of these days. Sportsbooks get their 10% 'Vig' regardless of who wins and losses and it's always been in their best interest to set lines that produce balanced action which helps to minimize their immediate risk and maximize long-term profits.

With the knowledge that the point spread is more a product of public sentiment, than actual team skill levels in many cases, it becomes fairly safe to assume that the statistics that help to shape public opinion will probably be less effective at handicapping the spread than other, equally effective stats that perhaps 'fly-below the radar' of the vast majority of handicappers out there. Those who follow the stock market will be familiar with this concept, which is known as the efficient market theory.

As an example: if everyone made their wagers based solely on season-to-date points differential for each team, Vegas would correct their lines for this fact and using a method of choosing teams based on points scored alone, would ultimately yield a fat 0 dollars profit, if not a loss, over the long-haul.

This example is an over-simplification of course, and bettors will typically take many more things into consideration when making wagers. Having said that, there are certain stats and variables that are used more often-than-not by the average handicapper, week in and week out.

With-out a doubt, rushing and passing stats are the measures of choice for most novice-to-intermediate handicappers along with other obvious ones, such as, points scored and allowed; 'power' numbers; injury report data and recent head-to-head results. Most people base their wagering decisions on these kinds of stats because they are both easy to find and easy to understand.

As with the financial markets; however, following the 'herd' is more likely to lead you (and your bankroll) over the side of a cliff, rather than to the 'pot of gold', and the same rules apply when handicapping the sports-betting market.

This is not to say that basic statistics which focus on such things as the efficiency of a team's rushing and passing game are to be ignored. On the contrary, I use these fundamental measurements (expressed as yards-per-play differentials) as part of a number of my successful situations. But, a number of other conditions usually need to be added in order to make them truly effective in predicting spread winners.

Getting back to penalties for a moment--beyond the basic penalty yardage totals shown for each team in the final boxscore, the specific types and frequency of certain penalties that teams take are essentially ignored by 99.5% of handicappers, and for the reasons discussed above, these key stats will also not factor too much into the line as a result.

Penalty calls are not the only facet of NFL team play that suffers from a lack of attention, despite their ability to reveal profitable situations versus the spread.

There happens to be quite a few other statistical gems that also fall into the 'overlooked' category and one such area concerns special teams play and more specifically, the king of this category--KRYF, which stands for Kick-off Return Yardage (Average) For.

KRYF is a critical stat that is on my 'shortlist' of numbers that no good NFL handicapper should be with-out.

It acts as a barometer of overall special teams strength on the most important special teams play of all: the Kick-off return.

Kick-offs are a critical event because of their ability to switch a games momentum in a heart-beat and they provide an opportunity for a team to quickly gobble up crucial yardage that can leave them with decent field position, which is key to any chance of a victory, whether it be SU or ATS.

Nothing deflates a team that just finished putting points on the board more, than an opponent who runs back the ensuing kick-off for 40 yards and we all know the affect that a player like Chicago's kick-return specialist, Devin Hester, can have on a game's outcome in the blink of an eye.

The league average for KRYF is usually around 22 yards-per-return. Good teams will find themselves with an average near 25 while lousy return teams will be down near 19 yards-per-return.

KYRF is a stat that I use a lot, and it just happens to be the basis for one of the 2 remaining Primary conditions yet to be discussed. Including the original one involving OHPA, this powerful 'trifecta' of negative factors spells doom for the team unlucky enough to meet all of the criteria involved.

Here is how KRYF factors into things: I have found that teams that have a higher OHPA as well as a lower KRYF than their current opponent, have been a dismal 245-332 (42.5%) ATS since 2001, which almost doubles the profit produced from looking at OHPA alone, to $6250.00.

As with OHPA, it makes sense that teams at a disadvantage with regards to KRYF are a poor bet against the spread. The surprise here, once again, is just how profitable it has been historically, when betting against this team based on these 2 simple factors alone.

Now, we are not done quite yet. The final significant stipulation that I like to add also involves special teams, in this case-- a comparison of Gross Punt Yardage and Net Punt Yardage concerning the current opponent of the team in question is included.

Subtracting Net Punt Yardage (the yardage achieved by a punt after the return is factored in along with any penalties against the punting team) from Gross Punt Yards (the distance a punt actually travelled from where the ball was snapped) is an excellent way to look at the ability of a team to: A) Execute a punt properly, and B) efficiently cover the ensuing return.

Teams with a poor punt coverage unit or that take a higher-than-average number of penalties during the punt itself; will see a wider gap between their GPYF and NPYF. Teams that have a below-average punter will also have a lower NPYF by extension, as shorter punts do carry a higher risk of big returns if coverage personnel do not have enough time to get into proper position.

The average gap between a team's GPYF and their NPYF happens to be 6 yards. By excluding opponents that have a GPYF at least 7 yards higher than their NPYF, we effectively remove opponents that have either poor coverage skills on punts, or a weak punter. Ultimately, this is yet another blow against the team already stinging from the other factors previously discussed.

In summary then: Teams that have a higher per-game average for Offensive Holding Penalties Against (OHPA) along with a lower per-game average for Kick-off Return Yardage For (KRYF)--both in relation to their current opponent--are 142-244 (36.8%) ATS since 2001, so long as this opponent's Gross Punt Yardage figure is no more than 7 yards bigger than their Net Punt Yardage per-game average.

Based on these 3 Primary conditions (along with the earlier tightener that confines things to Week 4 thru 15), we have a trend that has been a consistent winner since '01 and has produced a profit of $8,780.00 at 10/11 odds during this time period.

Rounding things out, are 2 final limitations, one of which excludes teams who have faced a tough schedule season-to-date (SOS > 0.600) while the other excludes underdogs of >= 7 points. With the addition of these final 2 conditions, the record is reduced to 89-190 (31.9%) ATS--a killer situation that has been a deadly predictor of results ATS, 7 years running.

A brief look at the stats below will show that this is a very balanced trend that has played on every single team in the league, aside from one. And, it is split fairly evenly between favs and dogs as well as home and away teams.

Here are all the details.

(Notes: ASMR stands for Average Spread Margin Rating. A positive rating indicates a trend that is stronger than average versus the line, negative--weaker than average. TDIS% is the percentage of teams in the league that have been involved in this situation at one time or another. WT% is the percentage of teams that are .500 or better and SPR is the average spread for teams in this situation. For more details, please consult Page 13 of my 2007 NFL Game Sheets Guide.)

Situational Trend #109 Summary

Primary Conditions (Building Blocks)
1) Offensive Holding Penalty Average Against (OHPA) > Opponent.
2) Kick-off Return Yardage Average For (KRYF)