Best Hidden Factor for NFL Futures

WHAT IS THE BEST “HIDDEN” FACTOR FOR DETERMINING NFL SEASON WINS PROPS:

We are quickly approaching the start of the NFL season. What you will be getting mostly now, will be a lot of season wins forecasts. Most of those will be based on the obvious, draft picks, free agent signings, or free agents lost, etc. The numbers will be scrutinized publically to the point of exhaustion, with a lot of “stuffed suits” and so-called experts weighing in. The problem is, they all approach the predictions with similar, if not exacting methodology, as described above, and state their objective view based on how they see it playing out.

Today in the newsletter, we will look at an entirely different methodology, one that sits tucked firmly under the radar, as it sits on an island, awaiting discovery, and in my attempt to always be “stealthy” regarding my handicapping philosophy, I have looked at many, many approaches, out of the main stream, and it is what attributes to my success as a handicapper.

I discovered several years ago, a methodology, that is first and foremost logical, and then backed up the theory with a trial and error highly successful means to the end, with 20 NFL seasons of data, So here we go:

INTER CONFERENCE GAMES THE KEY:

The NFL schedule is 16 games, and 25% of that schedule is comprised of inter-conference games. That is certainly a significant chunk. The beauty of it is, the NFL schedule is such, that these 4 games change every year, as inter-league play is rotated conference by conference through all 4 possibilities. here in lies the most predictive element I have found to forecast a team in the best spot to move up or down.

DOOMSDAY:

Arguably, in the long haul, a team should finish 2-2 in the 4 games straight up. Maybe in a given season, when they face a weak conference they rise to 3-1, or 4-0, and visa versa if they play the strongest conference. This is the key element.

Since the start of the 1995-96 NFL season there have been 49 teams that ran the inter-conference table at 4-0 SU. The theory is, a team that went 4-0 in these games may have had an easy path, and with a more difficult schedule in front of them in these 4 games the following season, it may be quite difficult to reach the same win total.

THE VERIFICATION:

The 49 teams that ran the table over the period, met this fate:

38 of them lost more games

9  of them won more games

2 of them won the same amount of games

34 of the 49 lost 2 more games or more 69.4%

The 38 teams that lost more games, did so to an average net wins over the previous season of -3.95!

So the fact is 78% of these teams lost an average of just about 4 more games the following season!

I’m not sure about you, but I have looked at 100s of season win forecasting tools, and none come remotely close to this!
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DOES THE DOOR SWING BOTH WAYS?:

Supporting evidence then should mean, that if a 4-0 team loses a significantly greater amount of games the next season under this hypothesis, then shouldn’t an 0-4 team win a lot more?

It certainly would make this hypothesis a lot truer, and acceptable if that were the case.

PAYDAY:

We now look at the 0-4 SU teams, and reverse what was said of the 4-0 SU teams, and here are the facts:

Since the start of the 1995-96 season, there have been 53 teams that went 0-4 SU in their previous inter-league schedule.

38 of the 53 won more games the next season

12 of the 53 teams lost more games

3 of the 53 won the same amount of games

34 of the 53 teams won 2 or more games the following season (64.1%)

The 34 teams that won more games, did so to an average additional wins of a whooping 4.1!

It certainly spells out the same outcome, and our theory is looking mighty strong!

COMBINING THE 4-0’s and the 0-4’s:

When we put this all together into one, since they are indeed the same thing we get:

Since the start of the 1995-96 season, there have been 103 teams that won all, or went winless in their 4 inter-conference games the previous season.

THESES TEAMS COMBINED TO:

positive theory results in 76 of 102 case studies (74.5%)

negative results in 21 of 102 case studies

neutral results in 5 case studies

The average wins or losses above or below the previous season in the 76 positive outcomes was 4!

Think about that for a second. Out of all case studies, with a positive outcome(75%) the results from the previous year were positive by 25% of the schedule, 4 games up or down!

I can say with certainty, that no one can come close to this stealthy way to forecast a team’s season win totals, using just 1 predictive variable, tested on both sides, over a 20 year period, with stunning credibility.

4-0 teams to play under from last year:

Dallas
Buffalo
Baltimore
Philadelphia

0-4 teams to play over from last year:

Atlanta
Tennessee
NY Jets

Best of Luck,
East