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I Sixty Two-hundred

NFL Prediction and Investment Analysis - "Against the Spread"

The goals of this web-site are to realistically analyze NFL teams, games, AND the odd-makers. Ratings etc. are meant to show true abilities and situations of NFL teams\games, and predictions "ATS" are meant to include the "skew" and biases of the odd-makers and the betting public. Whatever your interest, we're just glad you're here.

In the interests of full disclosure: Last season was a dismal 52.6% "ATS" over-all regular season through the play-offs. Though we don't expect this to continue, please remember, luck, randomness, and the changing NFL game all affect the outcomes.

Judge the value of the I60200 System's NFL-ATS analysis for yourself. All current season predictions are listed below. Take the time to read how and why the I60200 System works, and then view the explanations of the listed category headers, along with prediction results using data from the last 6 NFL seasons(2004 to 2009). Email me at I60200nfl@gmail.com with comments and questions, or anything you see that needs to be fixed or changed.

The following power rankings should be pretty accurate now(believe it or not).

Power Rankings and Ratings through week 5:

RankTeamPower
1bal1.218
2pit1.188
3nor1.139
4nwe1.123
5det1.116
6sfo1.108
7gnb1.104
8was1.098
9dal1.095
10cin1.062
11ten1.056
12oak1.052
13phi1.048
14buf1.037
15sdg1.027
16hou1.026
17car1.017
18mia1.013
19min1.004
20nyg1.002
21nyj0.991
22den0.986
23atl0.978
24sea0.969
25kan0.954
26ari0.943
27chi0.927
28cle0.918
29ind0.905
30tam0.903
31jac0.887
32stl0.87
Power is derived by calculating each team's offensive and defensive points production and prevention for each game, comparing it to the league average each week, and then adjusting for strength of opponent. For each game calculated, there is a MAX and a MIN power that a team cannot go beyond, so a blow out win is great, but it can't become unrealistically excessive(in any game, a team can't be 1000%, or a ridiculously similar amount better than another team in offense or defense), likewise, getting blown out or shut out can't give a team a 0 or other unrealistic power rating for offense or defense.

Next, all lucky type plays, good or bad, such as interceptions, fumbles lost, blocked punts, kick off return touchdowns, missed field goals etc. are valued, and each team's power is adjusted by a portion of this luck value(to distinguish between aggressive or sloppy team play vs dumb luck). If a team has been overly lucky, their power will be adjusted lower due to the fact that they can't be expected to continue to be so lucky. For the same reasons, an unlucky team's power will be increased.

A power rating of 1 is considered league average, so a team with a rating of 1.2 can be thought to be 20% better than the average team, and a team with a rating of .85 can be thought to be 15% worse than average.

A few things to keep in mind about the ratings. This is average power year to date, so a "hot" team won't jump above a consistently good team, all power is based on the ability to score and prevent points, so wins have no affect on the ratings, and player and coaching changes are not factored in.

You may also want to consider that a ranking system of 1 to 32 can be misleading. Rank and rating are 2 different things. You can see that the power rating of some teams are equal and/or very similar to the group of teams they're listed close to. A team ranked at #5 could have a rating that is virtually identical to a team ranked #10, yet a 5 rank difference infers a large difference. In other words, I'd pay more attention to the ratings than the rankings.

To use the ratings for points/margin of victory prediction, realize that the ratings are the average of both offense and defense, so its sort of double powered, meaning that it represents both the potential to score points AND the potential to prevent points being scored.

Here's an example of a fictitious "team A" playing an average team:

Team A has a 1.2 rating, so team A has a better defense AND a better offense by 20% over an average NFL team.
Average points scored or allowed in the NFL at this point is approximately 23.5. So:
Team A is 20% better in offense than average, so .20 * 23.5 = 4.7 points above average that team A should score.
also
Team A is 20% better in defense than average, so .20 * 23.5 = -4.7 points below average that an average team should score.
So all together, a 1.20 rated team should have a margin of victory above an average team of 9.4 points(difference between 4.7 and -4.7)

Here is the simpler, just as accurate, and more realistic way to calculate margin of victory.

Given the scenario of "team A" with a rating of 1.2 vs "team B" with a rating of 1.1, first calculate the percentage of advantage as follows:

(team A rating)-(team B rating)=% advantage. In this case its 1.2-1.1=.1, or a 10% advantage for team A.

Since the advantage is in both offense AND defense, we need the total of league AVERAGE points scored and league AVERAGE points allowed. Right now it's about 47(23.5+23.5). So just multiply the advantage(10%) by 47.

In this case, 47*.10=4.7, so team A should win by 4.7 points.

Predictions:

Each week all predictions are shown as soon as possible, yet are not official until stated so. Line moves and hype changes can affect the predictions up until game time. Though most of the 2 and 3 bet/unit predictions won't be lost as a prediction, the recommended bet amount can change as the line and hype does. The 1 unit/bet amount predictions are the most volatile, therefore these predictions can "drop" or "pop up" anytime during the week up until game time.

Week 6 predictions against the spread(be sure to check the recommended units/bets before team name):

Year
Wk
(#bets)Team
opponent
ScoreO/Uhypesu
ats
road
war
public
achv
blown
out
blew
out
desp-
erate
clinchpridediv
dog
pwr
adv
pwr
fav
pwr
dog
pwr
home
right
line
line
adv
fishy
trap
bad
luck
TotalAdvntgResultweek's
Profit
2011(3)MIN+300.4190.5640.591.5732.126??
6@chi0-0.15-0.4-0.55
|
2011(3)STL+1500.570.5430.5840.42.0972.097??
6@gnb00
|
2011(2)@TAM+4.500.5890.6040.5560.42.1491.614??
6nor00.5350.535
|
2011(2)@NYG-3.500.5890.40.6111.61.6??
6buf00
|
2011(1)CLE+6.500.6040.41.0041.004??
6@oak00
|
2011(1)HOU+7.500.5890.6041.1930.65??
6@bal00.5430.543
|

This week's thoughts:(purely personal opinions I can put here because its my web-site, even though it may have absolutely nothing to do with the predictions)

Here's a page showing who the public is betting on that may be of interest. I've done NO analysis on this website(sportsinsights.com), but it may have some value. See it here.



Lot's of work has been done in the off-season, so here's some information about it below.

Here are some NFL myths I uncovered while crunching data here. There are some possible traps we should avoid at the least, or even better, take advantage of when possible.

Last season was 52.6% ATS over-all regular season through the play-offs. Considering the luck and randomness in the NFL, that record isn't surprising, but that doesn't make it any easier. Was that just a down year? Am I missing crucial information? Both? Regardless, I'm dedicated to squeezing all I can from any advantages, so another round of programming and analysis was and is being done. Here's some of what's been done so far and some information that may be of interest:

Each team is now tracked based on who is starting at the QB position, and how they have affected their team in previous games.

A totally new team ability/performance prediction system has been completed that "sucks the luck" out of previous games, and accounts for who is the starting QB. Looks very promising at 58+% over 5 years.

A regression to the mean over/under line prediction program is completed(56% accurate over 5 years).

All "luck" type plays and penalties are now tracked to calculate the "luck" factor, and EP is now used to calculate the amount of luck involved in each play.

EP has been added as a new statistic used in our formulas and tracks every play for every team. Read about it here.

SR has been added as a new statistic used in our formulas and tracks every play for every team. Read about it here.

The Kelly Criterion has been analyzed and added as a feature. Read about it here.

Variance and standard deviation have been calculated for virtually every statistic I track. These can and are being used in various new formulas.

Statistical info you may want to get familiar with is here.

Stat correlations This is a list of statistics correlation to future margin of victory(nerds only, it's ugly) here.

Check back here when you can, I'll post more soon...

NFL 2011 season weekly analysis:

YearWeekBank
50000
1unit
bets
2unit
bets
3unit
bets
4unit
bets
bet
amt
unit
Ws
unit
Ls
week
result
week
profit
win
streak
lose
streak
max
exposure
ytd
profit
ytd
win%
20111476006660024-2-24000-24006600-240033.3%
201125140042 (x2)880062438003800011200140057.1%
201135730051 (x3)88007165900970007400730068.2%
201145780061 (x2)1 (x3)121006515001020004800780063.6%
201155520043 (x2)1100046-2-26000-26003200520058.1%
|

NFL 2011 season weekly details:

Year
Wk
(#bets)Team
opponent
ScoreO/Uhypesu
ats
road
war
public
achv
blown
out
blew
out
desp-
erate
clinchpridediv
dog
pwr
adv
pwr
fav
pwr
dog
pwr
home
right
line
line
adv
fishy
trap
bad
luck
TotalAdvntgResultytd
Profit
2011(1)OAK+3230.690.690.69+1000 1000
1@den200
|
2011(1)TEN+1.5140.690.690.69-1100 -100
1@jac160
|
2011(1)@MIA+7240.690.690.69-1100 -1200
1nwe380
|
2011(1)@STL+3.5130.690.690.69-1100 -2300
1phi310
|
2011(1)MIN+8.5170.690.690.69+1000 -1300
1@sdg240
|
2011(1)SEA+5.5170.690.690.69-1100 -2400
1@sfo330
|
Year
Wk
(#bets)Team
opponent
ScoreO/Uhypesu
ats
road
war
public
achv
blown
out
blew
out
desp-
erate
clinchpridediv
dog
pwr
adv
pwr
fav
pwr
dog
pwr
home
right
line
line
adv
fishy
trap
bad
luck
TotalAdvntgResultytd
Profit
2011(2)@TEN+5.5260.40.5840.9841.516+2000-400
2bal13-0.53-0.53
|
2011(2)OAK+3.5350.3230.5910.9141.446+20001600
2@buf38-0.53-0.53
|
2011(1)DAL-3270.3230.5840.9071.10701600
2@sfo24-0.2-0.2
|
2011(1)@ATL+2.5350.40.5840.9840.984+10002600
2phi310
|
2011(1)SEA+1400.3230.5910.41.3140.758-11001500
2@pit240.5560.556
|
2011(1)@CAR+10.5230.3230.40.7230.723+10002500
2gnb300
|
2011(1)@MIA+3130.285-0.20.0850.617-11001400
2hou23-0.53-0.53
|
Year
Wk
(#bets)Team
opponent
ScoreO/Uhypesu
ats
road
war
public
achv
blown
out
blew
out
desp-
erate
clinchpridediv
dog
pwr
adv
pwr
fav
pwr
dog
pwr
home
right
line
line
adv
fishy
trap
bad
luck
TotalAdvntgResultytd
Profit
2011(3)KAN+14170.5910.6040.5560.42.1512.151+30004400
3@sdg200
|
2011(1)NYG+829-0.110.5640.4451.157+10005400
3@phi16-0.71-0.71
|
2011(1)WAS+4.5160.4000.40.8001.000+10006400
3@dal18-0.20-0.20
|
2011(1)@SEA+3130.6040.556-0.20.5841.5440.944+10007400
3ari100.60.6
|
2011(1)@OAK+2.5340.40.40.932+10008400
3nyj24-0.53-0.53
|
2011(1)DET-3260.534-0.530.60.6020.85508400
3@min23-0.05-0.2-0.25
|
2011(1)@TEN-7170.9910.9910.610-11007300
3den140.3810.381
|
Year
Wk
(#bets)Team
opponent
ScoreO/Uhypesu
ats
road
war
public
achv
blown
out
blew
out
desp-
erate
clinchpridediv
dog
pwr
adv
pwr
fav
pwr
dog
pwr
home
right
line
line
adv
fishy
trap
bad
luck
TotalAdvntgResultytd
Profit
2011(3)TEN-1310.4570.60.6111.6681.783+300010300
4@cle13-0.11-0.11
|
2011(2)DEN+12230.5910.5640.41.5551.555-22008100
4@gnb490
|
2011(1)DET+2.5340.5910.60.41.5911.007+10009100
4@dal300.5840.584
|
2011(1)CAR+6.529-0.080.5640.40.8750.997+100010100
4@chi34-0.710.59-0.12
|
2011(1)@PHI-9.5230.6040.40.5841.5880.997-11009000
4sfo240.5910.591
|
2011(1)NYJ+4.517-0.300.5910.40.6850.912-11007900
4@bal340.305-0.53-0.22
|
2011(1)WAS-3170.5910.60.591.7810.821+10008900
4@stl100.6040.556-0.20.96
|
2011(1)ATL-5300.0890.0890.623-11007800
4@sea28-0.53-0.53
|
Year
Wk
(#bets)Team
opponent
ScoreO/Uhypesu
ats
road
war
public
achv
blown
out
blew
out
desp-
erate
clinchpridediv
dog
pwr
adv
pwr
fav
pwr
dog
pwr
home
right
line
line
adv
fishy
trap
bad
luck
TotalAdvntgResultytd
Profit
2011(2)TEN+3170.400-0.580.5910.60.591.5921.608-22005600
5@pit38-0.20-0.40.584-0.01
|
2011(2)CIN-1.5300.3730.60.41.3731.587+20007600
5@jac20-0.21-0.21
|
2011(2)NYJ+7.5210.5890.5910.6111.7911.224-22005400
5@nwe300.5670.567
|
2011(1)OAK+4.5250.4270.40.8271.040+10006400
5@hou20-0.21-0.21
|
2011(1)ARI+3100.60.61-11005300
5@min34-0.4-0.4
|
2011(1)NOR-6.5300.5350.591.1250.725-11004200
5@car270.40.4
|
2011(1)@DET-5240.6110.6110.611+10005200
5chi130
|


How the I60200 System works.

Overview:

The I60200 system utilizes a number of specifically designed computer programs that gather, analyze, and store pertinent information from various sources. Every individual program's criteria and parameters are set to produce predictions with a win percentage rate at a minimum of 55%(verified using the last 6 NFL seasons data).

If a particular team in a particular game meets the required criteria of any of the analytical programs, a percentage value is assigned to the program's relevant sub-category for that team. Since these values are an indication of a team's advantage(or disadvantage) in a particular area, they're called advantage values or simply advantage, and the categories themselves are called indicator categories or indicators.

Lastly, all advantage values in every indicator category for each team are combined into a total advantage. If a team's total advantage is greater than their opponent's total(by a predetermined minimum amount), that team is flagged as a prediction choice and is given a recommended bet amount based on overall advantage. This combination and comparison process is a sort of checks and balances system designed to increase reliability, and in most cases increases win percentage rates above the individual indicators.

About Indicators and Categories:

Each indicator sub-category is directly related to one or more of the following main categories:

  1. Public Over/Under-rated

  2. Team Motivation

  3. Team Ability

  4. Odds-maker Hints & Shouts

In order, I'll attempt to explain the types of indicators that make up each main category.

Public Over/Under-rated:

This category covers what influences the betting public's opinion about each team. The information used within this category pertains primarily to sports media opinions and news, as well as past/current team performance data. The value in these indicators lies in the fact that the sports media industry and team performance influence the betting public, and in turn, the betting public influences the spread.

First off, we use programs that gather and analyze the public media influences of each team to calculate what we call a public rating. If there's a large difference between the calculated public rating and calculated reality(using team statistics and performance data), an over-rated or under-rated value is generated. In these cases, the indicator advantage value is based on the over-rated or under-rated amount.

There are also various programs that sift through team data looking for situations and performances that the public tends to over react to, and if found, will save an advantage value to the applicable indicator categories.

Along with this, programs are run that look for popular/mythical strategy situations where some of the uninformed betting public may feel they have an advantage, but the opposite is actually the truth. The theory behind these programs is that the odds-makers won't allow an easy advantage to be had and will tend to skew the line to take away or reverse any popular scheme advantages. In these cases, either the team will be given a negative advantage value or their opponent will gain in value.

Another specialty program deals strictly with opening day games. It uses sports media's documented opinions and ratings to determine what the public may be thinking. This operates on the premise that no one really knows about a team until there's some current season performance data to judge them by. In most first game cases, how can a team realistically be set as the favorite or the underdog? To put it another way, teams getting points on opening day have a good chance of raising an indicator.

Team Motivation:

This category uses both current team performance data and upcoming game situations and location. Though it seems to be the most accurate of all the main categories, it tends to uncover fewer indicators than the others.

Current game results data is filtered for cases where teams may be motivated to atone for a poor performance, or are overconfident due to a recent scoring binge.

Who and where a team is playing is checked for anything where revenge and/or rivalry may be involved.

All games with playoff possibility implications are checked for motivational(or lack thereof) factors.

Another specialty program is run that checks for teams with no playoff chances, playing for pride only, and are in a unique position that has shown to cover the spread at a relatively high rate.

Each of the above indicator types have an assigned advantage value that is stored if a team fits the correct criteria.

Team Ability:

This category uses current season team statistics and performance data almost exclusively. It's the most detailed and intricate of all the main categories and tends to produce a large number of indicators and become more accurate as the season progresses and more data is accumulated. Please note: All programs are designed specifically to cover the spread, so straight up wins are never taken into consideration within the team ability category.

At the heart of this category is a relatively large program that's run for each team and takes into account detailed team information such as offensive and defensive current season performances, average scoring abilities, home and away advantages, strength of schedule, and current opponent.

Since odds-maker spreads and team play vary depending on team/game situation, there's a specific program run for each team/game type, at home, away, as favorite, and as underdog.

Lastly, a program is run that seeks to find teams that match up well against certain opponent types due to familiarity, coaching styles, or other similar factors.

Again, each program will store an advantage value for each team that meets its criteria.

Odds-maker Hints & Shouts:

Here we use the spread itself along with other data that can be used for comparison purposes. Basically we strive to uncover what the odds-makers may be unknowingly telling us. In all these programs, we always assume that given their resources and experience, the odds-makers know more about the teams, games, and odds than anyone else could ever hope to.

The first program we run simply checks the spread in each game and looks for small hints like a half point hook to entice us the wrong way, or spreads that have a proven win percentage advantage. We call these odds-maker hints. Though this program uncovers more indicators than any other individual program, it can be the most dangerous. Playing the line is a semi-popular form of handicapping, so the fear is that the odds-makers can skew the line to eliminate or reverse these advantages at any time. It's for this reason that a relatively small advantage value is given for each of these indicator types. This serves as insurance and protection against a time period where these advantages are taken away or reversed(our data shows this has happened in recent seasons).

Next, we calculate a realistic spread based on current season team performances and statistical data and compare it to the actual spread. If there's a significant difference, we assume that the odds-makers know something we don't. This is called something is fishy or fishy. In these cases we choose against our line prediction.

Similarly, we generate a public spread, which is a calculated spread using public influences, basic points data, and favorite/home team public tendencies. Next, we compare this public spread to the actual spread, and if there's a large variance, we assume the public is wrong and instead choose the public's predicted losing team. We call this a public trap, a trap, or an odds-maker shout. The basic theory behind this is, if it looks too good to be true, it IS too good to be true. Bet predictions based on these indicators are the toughest to understand and the toughest to follow through with(it's called betting ugly), but with win percentages over 63% for the last 6 seasons, they're one of the most accurate indicators we're capable of producing.

Next, we compare our calculated spread, the public spread, and the actual spread. If the odds-maker's actual spread is between our spread and the public's spread(within certain limits), we assume we're on the right side(the odds-maker's side) of the line. We call this right side line or right line.

Lastly, we'll analyze all of these generated indicators for each team and search for combinations that have shown increased win percentage chances. Though all indicators show sufficient accuracy individually, certain combinations of indicators have proven to have a higher win percentage rate, so advantage values are increased accordingly in these cases.

The last 6 seasons:

Please see the chart below showing the accuracy of I60200 indicators using data from the last 6 NFL seasons. Keep in mind, the information is not based on combined and compared advantage totals(which should be more accurate), but are the number of indicators and respective win percentages grouped by main category.


YearPublic
Over/Under Rated #,%
Team
Motivation #,%
Team
Ability #,%
Oddsmaker
Hints & Shouts #,%
2004239, 53.1%121, 55.3%301, 58.8%150, 58.6%
2005232, 55.1%112, 57.1%313, 56.8%160, 55%
2006237, 64.1%115, 70.4%328, 57.6%171, 60.2%
2007257, 56.8%138, 58.6%320, 59%193, 60.6%
2008262, 59.9%147, 61.2%291, 59.7%170, 61.7%
2009247, 58.7%144, 52.7%305, 59%178, 55%
Total1474, 58%777, 59%1858, 58.5%1022, 58.6%

As you can see, there are quite a few indicators generated per season. When combined and compared during the season, they boil down to an average of 120 regular season game predictions(about 7 per week), and just over 200 recommended bet predictions per year(11+ per week). Hopefully this relatively high number of games/bets can help to smooth out the sometimes bad affects of randomness or luck.

Summary:

These programs have been heavily tested with real NFL data, and because of the number of indicator categories checked, and the combine and compare(checks and balances) design, I see no reason not to expect continued success.

At this point, I assume you're either very interested in, and/or highly skeptical of(and rightfully so) such high win percentages, so please continue and learn why I think it works so well, and what the results are for the last 6 NFL seasons.