There is an adage in the NFL which says a team is never as good or as bad as the score of their last game. In other words, just because a team won by 20 last week does not mean that is the new norm, and vice versa.
I do not believe momentum exists in the NFL. I have been clear how I feel about momentum and have worked to dig up supporting statistics. However, lines skewed due to recent outcomes are a different story.
This phenomenon is very similar to momentum, but actually creates a discrepancy because momentum does NOT exist. When a team wins big, for example, most of the betting public (even Vegas sometimes) overvalues them the following week. This is because of the myth of momentum.
There are times when a team does drastically improve their play midway through the season. This is relatively rare, and most blowout wins do not indicate a team turning a new page. They are the result of some good fortune. A fortuitous bounce, a toe on the line, a broken tackle, or a bad call here or there can quickly turn a close game into a laugher.
Because it can be difficult to determine whether a win/loss was deserved, the public tends to overreact when the final score is not indicative of how a team played. If we learn some of the red flags, we can better distinguish good performances from lucky ones and more accurately evaluate teams the following week.
Don’t Get Fooled by Non-Offensive Touchdowns
Pick 6s, scoop-n-scores, and kick/punt returns flip a football game on its head and put up chunks of points in no time at all.
.@AaronDonald97 is a BEAST. 💪💪@RamsNFL scoop the Mahomes fumble and SCORE. #LARams
📺: #KCvsLAR on ESPN pic.twitter.com/SNWICl5rRB
— NFL (@NFL) November 20, 2018
Coughing the ball up at an inopportune time and watching the opposing defense celebrate in the endzone can absolutely demoralize a team. 7-point swings in a sport with an average score in the 20s have a major impact on the game’s spread – often being the difference between covering and falling short.
Non-offensive touchdowns (NOTDs) are so powerful that teams are nearly guaranteed to win when they get one. Check out the following chart which shows the ATS and SU win percentages since 2004 for teams that have scored a NOTD.
| Year | ATS % | SU % | Avg Line |
| 2004-2018 | 71.1% | 70.9% | -1.1 |
Home, away, favorite, dog, good team, bad team – it doesn’t matter. Get a NOTD and your chances to win are right around 70%. Since 2004, teams with a NOTD have a 35.7% ROI on the spread and a 32.1% ROI on SU bets.
So it’s simple, right? Just bet teams that are going to score NOTDs. The problem is that these are downright impossible to predict. In fact, when you bank on NOTDs, you are setting yourself up to be on the wrong side of the spread.
Let me give you a completely hypothetical example. The Patriots are 6-0 and are the class of the NFL. The lowly Bills are 2-4, but out of nowhere, Buffalo rises up and knocks off New England 31-13 in Week 7. Thinking that Buffalo has turned a page, you put $100 on them next week. That is a Benjamin you likely are not getting back.
You see, if you did not watch highlights or look at the box score, you would not know how the Bills won. Turns out the Bills gained a 2-touchdown lead in the 3rd quarter with the help of 2 NOTDs. The Patriots were then forced to pass on every down to catch up which made the job of the Bills’ defense quite easy.
Buffalo did not dominate the game from start to finish, they simply got lucky with a couple of 3rd quarter NOTDs. This is exactly the type of scenario we need to be cognisant of because it will likely skew next week’s line. Understanding how teams won and not just how much they won by is vital.
Beware of Favorites Following Lucky Wins
Earlier I mentioned the Bills bet would be a -EV bet. Here is where I begin to prove why. Since 2004, the NFL has seen a very strong “anti-cheap wins” trend, meaning that teams following up cheap wins usually struggle the next week. The first filter I will use to pull data is favored teams that are following up a win in which they scored a NOTD.
As a frame of reference, I will display the numbers for ANY favorite following a win since 2004, regardless of whether they scored a NOTD last time out or not.
| Years | ATS % | SU % | Avg Line |
| 2004-2018 | 50.4% | 69.2% | -5.8 |
Neither the ATS nor the SU win rates are profitable for these favorites. An explanation for why this is can be found here, where I discuss the lack of week-to-week momentum in the NFL.
Keeping in mind that all favorites following a win are 50.4% ATS, here are the numbers for favorites off a win in which they scored a NOTD.
| Year | ATS % | SU % | Avg Line |
| 2018 | 47.8% | 75.0% | -6.1 |
| 2017 | 47.1% | 60.0% | -5.5 |
| 2016 | 63.6% | 65.2% | -5.0 |
| 2015 | 40.5% | 63.2% | -5.3 |
| 2014 | 51.3% | 69.2% | -5.4 |
| 2013 | 50.0% | 69.0% | -5.9 |
| 2012 | 50.0% | 72.7% | -5.5 |
| 2011 | 54.3% | 77.8% | -7.2 |
| 2010 | 51.4% | 62.9% | -5.0 |
| 2009 | 39.0% | 70.7% | -6.4 |
| 2008 | 46.3% | 74.1% | -6.5 |
| 2007 | 48.9% | 72.3% | -7.5 |
| 2006 | 43.2% | 56.8% | -6.1 |
| 2005 | 53.1% | 66.7% | -5.7 |
| 2004 | 45.5% | 66.7% | -6.5 |
| Total | 48.2% | 68.4% | -6.0 |
The ATS win rate for these favorites is 2.2% lower when the team was aided by a NOTD in their previous win. The SU win rate is also lower and the average line is stiffer … not a good combination. Neither win rate is even close to being profitable.
While this information is definitely helpful it only instructs us on which teams to fade, not which to bet. We know to fade these particular favorites, but with an ATS win rate right around 50%, neither side is profitable. My mission is to find situations in which favorites following a win cover at such a low rate that it is profitable to bet the dogs.
Effect of Previous Game’s Line and Margin of Victory
I was curious as to whether it mattered if a team was a favorite or underdog in their previous game. For example, are teams more or less likely to win after they pull an upset due to a NOTD? This table uses the same criteria as the previous one, but this time sorting by whether a team was favored or not the week prior. Here are the numbers, again since 2004.
| Previously | ATS % | SU % | Avg Line |
| Favorites | 47.4% | 69.3% | -6.3 |
| Dogs | 48.3% | 63.9% | -5.1 |
| Total | 48.2% | 68.4% | -6.0 |
As you can see, the line is a bit stiffer when a team was favored the previous week and the ATS win rate was a tad lower. We finally found a system which would be profitable to bet against, but the earnings would be negligible.
Favored teams off a win in which they were also favored and scored a NOTD are only winning ATS 47.4% of the time. This means their opponents are winning 52.6% ATS, slightly higher than the break-even point. This 0.2% edge would have only netted $100/game bettors a measly $170 since 2004. We can obviously do better.
Next, I had the idea of checking whether a team’s margin of victory in the previous game (the one in which they scored the NOTD) had a bearing on the next week’s performance. I kept the same search (favorites after a win in which they scored a NOTD, since 2004) but sorted the results by margin of victory. Take a look.
| Margin | ATS % | SU % | Avg Line |
| < 7 | 50.5% | 68.4% | -5.3 |
| 7-13 | 52.6% | 68.6% | -5.7 |
| 14+ | 45.6% | 68.3% | -6.5 |
| Total | 48.2% | 68.4% | -6.0 |
Gotta love what this table shows us. When the average margin of victory was less than 2 touchdowns, teams were right around the break-even point ATS. When a NOTD helped them win big their last time out, these favorites really flopped ATS.
It is important to note that the SU win rates for the three categories are all extremely close. This is because there is no week-to-week momentum in the NFL, so last week’s margin of victory does not affect your chances of winning SU this week.
Last week’s margin of victory does affect this week’s line, however. Vegas makes money whenever they get roughly the same amount of action on either side of a bet. It is in the bookies’ best interests to create a line that perfectly splits the public opinion, putting 50% of the money on either side.
Even if Vegas does not skew the line in the favorite’s direction to begin with, it will eventually trend that way if enough people bet the favorite to cover. A 6-point win does not raise eyebrows. A 21-point win definitely will. Take advantage of the public’s ignorance by betting against favorites who won by at least 14 last week with the aid of a NOTD.
A $100/game bettor who jumped on this trend in 2004 would be up $1,360, or 3.9% ROI.
Improving the System Even More
While the 54.4% ATS win rate and the 3.9% ROI are good, by introducing more filters we can create an even more powerful and profitable system. The title of this article is “Fade Favorites Following Flat Finishes,” but so far I have not addressed teams following “flat finishes”. While scoring a NOTD can allow you to coast to the finish line, it does not guarantee it. I need to account for this directly.
I decided to add the following filter: a team must have scored 3 or fewer points in the 4th quarter of their previous game. This means that the NOTD could not have come in the 4th quarter. Because they were gifted 7 points earlier, this team was able to have a poor showing in the 4th and still win the game. This shows a lack of dominance.
Before I show the numbers with my new filter, I first want to show the numbers for ALL teams who scored just 3 points or fewer in the 4th quarter. Since the only realistic amounts in this range are 0 and 3, I sorted the results into these categories. Here are the numbers, of course since 2004.
| p:P4* | ATS % | SU % | Avg Line |
| 0 | 31.3% | 28.4% | 1.5 |
| 3 | 55.8% | 55.8% | -0.3 |
* SDQL notation meaning points in the previous game’s 4th QTR
I was shocked that teams were winning so much despite only scoring 3 points in the 4th quarter. I was also a bit surprised that it was so difficult to win when you got blanked in the 4th quarter. I knew the win rates would be low, but 31.3% ATS and 28.4% SU seemed very low to me.
For emphasis on how beneficial NOTDs are, I want to show the same chart, but this time only for games in which the team in question had a NOTD in one of the first 3 quarters. It’s game-changing to say the least.
| p:P4* | ATS % | SU % | Avg Line |
| 0 | 52.0% | 51.4% | -0.1 |
| 3 | 67.1% | 65.9% | -1.0 |
Would ya look at that. Teams who scored 0 points in the 4th (the kiss of death) are now right around break-even because they lucked out and were on the right side of a NOTD (the kiss of life). Do you see why favorites often lose following games like this? They just won a game they did not deserve to win. The public thinks they played great, however, and backs them in the next game because of it.
Adding My Next Filter – The Flat Finish
I learned from these charts that scoring 3 points in the 4th quarter is actually not detrimental to a team’s chances of winning. Scoring 0 in the 4th definitely is. For my next table, I will only use p:P4=0 and not p:P4<=3 like I originally intended.
You may be thinking this system is getting a bit obscure. My justification is that with each filter I add, I can produce a logical reason for why it keeps improving my system. The simplified versions of this system are still profitable, but I can increase ROI when I build upon the basics.
Allow me to recap what this table is about to show. We are looking at favored teams who won their previous game with the help of a NOTD despite not scoring in the 4th quarter of that game. Take a look.
| Year | ATS Record* | ATS Win % | SU Record* | SU Win % | Avg Line |
| 2018 | 0-3 | 0.0% | 1-2 | 33.3% | -3.8 |
| 2017 | 3-2 | 60.0% | 4-1 | 80.0% | -6.9 |
| 2016 | 1-1 | 50.0% | 2-1 | 66.7% | -7.3 |
| 2015 | 3-3 | 50.0% | 3-3 | 50.0% | -5.7 |
| 2014 | 3-3 | 50.0% | 3-3 | 50.0% | -4.2 |
| 2013 | 2-1 | 66.7% | 2-1 | 66.7% | -3.2 |
| 2012 | 3-3 | 50.0% | 5-1 | 83.3% | -4.0 |
| 2011 | 4-3 | 57.1% | 5-2 | 71.4% | -5.9 |
| 2010 | 4-7 | 36.4% | 5-6 | 45.5% | -4.5 |
| 2009 | 0-4 | 0.0% | 2-2 | 50.0% | -5.0 |
| 2008 | 2-3 | 40.0% | 3-2 | 60.0% | -6.4 |
| 2007 | 2-5 | 28.6% | 4-3 | 57.1% | -7.1 |
| 2006 | 1-3 | 25.0% | 1-3 | 25.0% | -7.6 |
| 2005 | 3-4 | 42.9% | 5-3 | 62.5% | -6.1 |
| 2004 | 1-7 | 12.5% | 3-5 | 37.5% | -5.4 |
| ‘04-’10 | 13-33 | 28.3% | 23-24 | 48.9% | -5.8 |
| ‘11-’18 | 19-19 | 50% | 25-14 | 64.1% | -5.2 |
| Total | 32-52 | 38.1% | 48-38 | 55.8% | -5.5 |
* excluding pushes and ties
You likely noticed I broke the totals row into two time spans: 2004-2010 and 2011-present. I did this because beginning in 2011 we saw a drastic shift in what this system is useful for. From 2004-2010, bettors made a lot of money from betting against this system. These favorites were only winning at a 28.3% clip ATS. It was a no brainer.
Beginning in 2011, these favorites started winning at a much higher rate. They are now in that no man’s land of 47.6%-52.4% in which it is not profitable to bet either side. This is still great news for us. Profiting from betting sports is just as much about avoiding the bad bets as it is jumping on the good ones.
These favorites were terrible earlier in the decade and we could profit from betting against them. Now they have pulled up to break-even. These favorites have never – I repeat, never – been profitable in the long-term. At best they are break-even bets that we should avoid. At worst, they are highly profitable to bet against. This is valuable information to possess.
Adding Another Filter – Home Field
Those of you who read my articles consistently know that when I am trying to flesh out a system, checking for a home-field advantage (or lack thereof) is normally the first place I start. It wouldn’t feel right if I did not check to see whether home field affected these lucky, flat favorites.
This system will now have 5 sets of criteria and will generate beaucoup bucks. Remember, in the last table we looked at favorites following a win in which they did not score in the 4th quarter but were aided by an early-game NOTD.
We would be treated to an astounding 18.2% ROI if we bet against that system each game since 2004. You might not believe me, but I think I can squeeze out even more profits with this home-field filter. Let’s take a look and see what measuring only home teams does to the numbers.
| Year | ATS Record | ATS Win % | SU Record | SU Win % | Avg Line |
| 2018 | 0-2 | 0.0% | 1-2 | 33.3% | -4.3 |
| 2017 | 1-2 | 33.3% | 2-1 | 66.7% | -9.7 |
| 2016 | 1-1 | 50.0% | 1-1 | 50.0% | -9.5 |
| 2015 | 2-2 | 50.0% | 2-2 | 50.0% | -5.5 |
| 2014 | 2-2 | 50.0% | 2-2 | 50.0% | -4.8 |
| 2013 | 2-0 | 100.0% | 2-0 | 100.0% | -4.2 |
| 2012 | 1-1 | 50.0% | 1-1 | 50.0% | -5.8 |
| 2011 | 2-3 | 40.0% | 3-2 | 60.0% | -6.3 |
| 2010 | 4-6 | 40.0% | 5-5 | 50.0% | -4.8 |
| 2009 | 0-2 | 0.0% | 1-1 | 50.0% | -3.0 |
| 2008 | 1-2 | 33.3% | 2-1 | 66.7% | -6.5 |
| 2007 | 1-4 | 20.0% | 3-2 | 60.0% | -6.9 |
| 2006 | 1-3 | 25.0% | 1-3 | 25.0% | -7.6 |
| 2005 | 1-0 | 100.0% | 1-0 | 100.0% | -16.0 |
| 2004 | 1-4 | 20.0% | 3-2 | 60.0% | -6.0 |
| ‘04-’10 | 9-21 | 30.0% | 16-14 | 53.3% | -7.3 |
| ‘11-’18 | 11-13 | 45.8% | 14-11 | 56.0% | -6.3 |
| Total | 20-34 | 37.0% | 30-25 | 54.5% | -6.7 |
When these teams are at home, their average line is stiffer. This speaks to the weight the betting public grants home-field advantage. The beauty of this system is that it was profitable to bet against from 2004-2010 but it has also been profitable to bet against from 2011 on.
If you’d have bet each against each of these favorites since 2004, you’d have netted an ROI of 20.2%. Wall street brokers would faint at the thought of that return. Even if you were late to the party and did not start playing this system until 2011, your ROI would be 3.4%, a respectable return for any investment.
Adding My Final Filter – Previous Line
Remember when I found that favorites who were also favorites in their previous game fared worse ATS? Guess what happens when I also apply that filter. That’s right, the numbers get even better. Take a look.
| Year | ATS Record | ATS Win % | SU Record | SU Win % | Avg Line |
| 2018 | 0-1 | 0.0% | 1-1 | 50.0% | -5.0 |
| 2017 | 1-2 | 33.3% | 2-1 | 66.7% | -9.7 |
| 2016 | 1-1 | 50.0% | 1-1 | 50.0% | -9.5 |
| 2015 | 2-2 | 50.0% | 2-2 | 50.0% | -5.5 |
| 2014 | 1-2 | 33.3% | 1-2 | 33.3% | -4.5 |
| 2013 | 1-0 | 100.0% | 1-0 | 100.0% | -6.5 |
| 2012 | 0-1 | 0.0% | 0-1 | 0.0% | -5.5 |
| 2011 | 2-3 | 40.0% | 3-2 | 60.0% | -6.3 |
| 2010 | 2-5 | 40.0% | 3-4 | 42.9% | -5.2 |
| 2009 | 0-1 | 0.0% | 1-0 | 100.0% | -3.5 |
| 2008 | 0-0 | — | 0-0 | — | — |
| 2007 | 0-2 | 0.0% | 1-1 | 50.0% | -6.2 |
| 2006 | 0-3 | 0.0% | 0-3 | 0.0% | -9.2 |
| 2005 | 1-0 | 100.0% | 1-0 | 100.0% | -16.0 |
| 2004 | 0-2 | 20.0% | 2-0 | 100.0% | -8.2 |
| ‘04-’10 | 3-13 | 18.8% | 8-8 | 50% | -7.0 |
| ‘11-’18 | 8-12 | 40% | 11-10 | 52.4% | -6.5 |
| Total | 11-25 | 30.6% | 19-18 | 51.4% | -6.7 |
From 2004-2010, betting against these favorites would have yielded an 81.2% win rate ATS. That’s astronomical! That’s a 55.1% ROI! From 2011 to the present, the percentage has regressed to 60%, a percentage that most bettors would do unspeakable things to attain. At 60%, the ROI betting against these favorites since 2011 is 14.5%.
As a side note, when I apply the “previous margin of victory being at least 2 touchdowns” criteria, it causes nothing but a trivial change in the numbers.
Feel free to take my research and add some of your own. I would bet you could find similar systems. Such trends exist because many bettors are too impulsive or ignorant to avoid betting sucker lines, so bookies keep posting those lines. That is where we, the educated few, take advantage.
Remember: fade favorites following flat finishes. Teams off flat finishes are not as good as they appear.
Kreighton loves sports, math, writing, and winning — he combines all of them as a writer for WagerBop. His favorite sports to review are MLB, NFL, NBA, NCAAF, and NCAABB.
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