With so much noise surrounding the new Ray Rice video released Monday, it begs the question whether the Ravens have had enough time to prepare for their divisional rival Steelers. 

Last week the Ravens offense stalled against the Bengals. Joe Flacco went 35 of 62 for 345 yards and an interception, with 80 of those yards coming on a TD to Steve Smith in the fourth quarter. Without Rice the Ravens started veteran Bernard Piece who fumbled in the second quarter and didn't play again. Justin Forsett took over and ran 11 times for 70 yards and a touchdown. 

The Steelers' offense on the other hand was led by Ben Roethlisberger; who had a career-best 278 yards in the first half and finished with 365, including a 35-yard touchdown pass to Antonio Brown that preceded a 38-yard scoring run by Le'Veon Bell in the second quarter.

Bell finished with 109 yards rushing while catching six passes for 88 yards, and he's looking forward to facing a Baltimore defense against which he totaled 166 yards and a touchdown on the ground as the clubs split a pair of meetings last season.

Transparency:
Steelers + 10 open 7 point Teaser $15.60 / $12.00

Wow did we get it wrong last week. The Chiefs, Bucs, Rams and Giants are plenty worse than we had originally thought. The Chiefs, Bucs and Rams each lost at home to teams we previously ranked below them. And then there's the Giants. I have generously ranked the Giants (2 , 2) 29th this week but they very well could be the worst team in the NFL. Led by Eli Manning who could be the 29th ranked QB in the NFL, playing behind the 32nd ranked offensive line in the NFL. The Giants are flat out atrocious. 

Teams that impressed me:

Panthers: Kelvin Benjamin had an impressive debut. Benjamin caught six of eight targets for 92 yards and a touchdown Sunday. Imagine what Benjamin can do with Cam Newton under center.

Falcons: Think Matt Ryan is happy everyone's healthy? Ryan was 9-of-11 for 224 yards on throws at least 15 yards downfield Sunday. Nine completions were a career high.

Cardinals: The most aggressive defense in the league last year, Arizona picked up where it left off. The Cardinals sent extra rushers after Philip Rivers on 57 percent of dropbacks.

On the Giants side of the ball, the O-line appears to be an area of concern. Free-agent pickup Geoff Schwartz, expected to start at guard, will be out for at least the first seven games with a dislocated toe and the rest of the starters form a major question mark.

Detroit's front four could give the Giants' offensive line major problems. Ziggy Ansah (eight sacks), Ndamukong Suh (5 1/2) and Nick Fairley (six) might end up creating flashbacks for Manning, who was sacked a career-high 39 times last year.

While the battle of the trenches seems to be a big question mark for the Giants offense, the Lions 2013 season doesn't make us think that they are going to run away with this. The 2013 Lions won just 7 games, were ranked 30th in give-aways and 25th in total defense allowed per play. Not to mention a loss in December to the Giants.

The line is everything here. At +6 the Giants are being presented as a team several notches below the Lions. If the Giants offensive line can manage to protect Eli, we like the Giants to cover. 

Giants +6 -105 $12.86 / $12.24

Get your bagels and lox ready because today is football Sunday. 

Nothing gets us more excited about a football Sunday than the thought of perfect betting. Because right now, without having any of the games started, we are all perfect. Not a loss to think about, not a frustrating back door cover to bother us, just a wide open fairway and 18 holes of perfection to get our motors running.

That feeling of perfect betting is a lot like that confident feeling before your tee shot off hole one. The thought that today could be that day. 290 with a slight draw. Gap wedge to 8 feet. Birdie. The ability to make every shot great. 

Wake up stupid. Reality sets in once you get up to that tee. However you hack it, duck hook, duff, two breakfast balls into some hazard, that optimism, that sense of faith, good-bye! 

Welcome to the real football Sunday, where most of you losers will whine about trying your best. You'll complain about "da whitchin hour" and how you lost 3 bets in the last 5 minutes of the game. The goal of this post to make sure that shank doesn't happen, so we can go home and fuck the prom queen.

The math here is very simple. The line suggests that the Titans and Chiefs are equivalent.  In my mind this just can’t be true. Yes, the Chiefs won games early in 2013 against a very weak schedule, stumbled down the stretch and blew a 31-10 lead in the Wild Card game against the Colts. But they also won 11 games in 2013, didn’t turn the ball over (2nd in NFL), and they have a quarterback who doesn’t lose as a starter. In my opinion people are thinking too far ahead. They look at the Chiefs schedule which includes @DEN, NE, @SF, SEA, DEN, @ PIT and writing this team off before the season even starts. Chiefs go 9 – 7 in 2014 and this is 1 of their victories.

The model likes both money lines. The 6-point teaser here makes a lot of sense. Jets and Bears have a 78% and 79% probability of covering (basically to win), respectively. Therefore, to win both the odds are 62%, which is more favorable at -110 than betting each team individually at -250 and -300. 

There isn't a question that the Panthers were a better team last season. The Panthers were better than most teams last season. But questions surrounding Carolina's wide receivers and the health of Cam Newton make me question whether 2014 is going to be a set back year for the Panthers. Changes also abound for the Buccaneers, who fired Greg Schiano following last season's dismal 4-12 record and brought in Lovie Smith after he was canned by Chicago despite a 10-6 campaign. Journeyman Josh McCown, who thrived as an injury replacement for Jay Cutler with the Bears last season, was signed in the offseason to take the reins at starting quarterback. The model likes the Bucs here simply because we rank them a notch above the Panthers. Had we ranked them the same, as many of you will, the bet would still be the Bucs given the +100 vig. My prediction is this is a win for the Bucs and the start of a long season in Carolina. 

I think the model got this game right. There is not question the 49ers are 1 of the league's elite teams. There also isn't a question that the Cowboys have one the league's most porous defenses, but with a money line of +170 at home, it just makes sense taking a team that can score at will.  Over the course of the season we will lose a lot of underdog money lines, we are supposed to, but we will continue to bet them when we think we are getting the right odds. 

Not only does the model like the money line based on rankings, STL (3, 3) at home against MIN (2, 2), but the matchup is favorable for the Rams. The Rams defense, who are stingy against the run, should be enough to stop Adrian Peterson and force Matt Cassel to beat them through the air. Cassel and the Vikings offensive line will have their hands full against a front 4 who were 2nd in the NFL in sacks last year. The Rams are talented and should beat one of the league's worst teams at home. 

This game has the makings of a battle. And in battles we don't like anything more than the home dog. The Falcons are trying to forget about an injury ridden 2013 season and they have to do so against one of the sexist offenses in the NFL. The Saints had a great season that ended in the divisional round of the playoffs to the Seahawks. However, the Saints are notorious for their struggles on the road (though being in a dome helps), take the points and don't look back. 

I couldn’t have rated the Patriots any better and the Dolphins any worse, yet still the model thinks the spread is just too big for the home dog. Dolphins split with the Patriots last year including a 4 point victory at home in December. Best stat from last year, the Patriots were 15th in the NFL when converting in the Red Zone and Miami’s defense was ranked 5th when trying to stop the opposing team. I like the stat and I like the home dog with too many points. 

Nothing makes me more excited about football gambling than an 8,000 person survivor league. Each year I enter five to ten entries with the hope that I can turn a modest amount of money into a small fortune. And every year I find myself on the wrong side of the winner's circle, eliminated because a 70%+ favorite loses at home to a garbage team. Survivor is the best example of why even math can't outpace luck. Favorites are going to lose; and not just small favorites, big favorites as well. That's what makes survivor so frustrating is that no matter how good the math is, to win 24 to 27 consecutive games (which is what's required in ronandmike.com) you need to get flat out lucky. I don't doubt each year my path that I create has a greater chance of winning than the ultimate winner's did, but the truth of the matter is we're dealing with 1 in 8,000 shots; if you're smarter than the rest maybe 1 in 2,000 shots. The odds to win are very much stacked against math in the Survivor league, because we don't have the fortune of playing hundreds of entries over hundred of years and taking advantage of higher expected values than the rest. 

What we can do is make smart decisions. The first step of making smart decisions is mapping out the entire season. I have attached my Survivor Map for Week 1.

The Survivor Map is definitely something you need to print out (legal sized paper) to get the full effect. Ultimately my goal is to visualize the entire season, trying to see only the games where a favorite exists. In my version of the Survivor Map, I highlight in green only teams that have a greater than 65% chance of winning during the first 8 weeks, a greater than 60% chance in weeks 9 through 13, and a greater than 57% chance in weeks 14 through 17. By doing this we take 512 possible teams and narrow it down to 135. 

A couple things to notice right off the bat. As you can see in the column directly to the right of the team name is a column labeled  "Opps". Opps is the amount of opportunities you have to pick a particular team. This is very important because it helps us quickly point out certain weeks where we might have to take a particular team, because no other options are available. For example, the Cardinals are a team we will likely take this year, but based on their schedule, the only opportunity to take the Cardinals in a strong favorite position will be week 6 at home against the Redskins. For now, I'm going to pencil in the Cardinals for that week because I view them as a top 24 team. However, if things change by week 6 and the Cardinals are a lot worse than expected or the Redskins are a lot better, I will have to change my approach.

Something important to keep in mind is our rankings of each team. Our rankings for each team over the course of the season will change, therefore, our Map will look a lot different from week to week. 

For this weeks version of Survivor Friday's lets not over think it. It is a long season and I want to be around next week. The biggest favorites of the week based on my model are:

1. Eagles 85% (8 opps)
2. Bears 82% (7 opps)
3. Steelers 77% (2 opps)
4. Jets 77% (3 opps)
5. Broncos 76% (12 opps)

Vegas has the same top 5 but in a slightly different order:

1. Eagles -530
2. Broncos -340
3. Bears -300
4. Steelers -290
5. Jets -260

For me, a degenerate with 6 entries, I will be diversifying my picks between the Jets, Steelers and Bears. I don't like the idea of taking the Eagles or Broncos because of the fact that there will be 7 and 11 opportunities, respectively, to take them in the future. I also feel pretty confident in my rankings of the teams my picks will be playing. The Jets play the Raiders (2 , 2), the Steelers play the Titans (3 , 2), and the Bears play the Bills (2 , 2). Each is playing one of the bottom teams in the NFL. Each team is playing at home as well.

The NFL has a name for it, "Kickoff Game". Since 2002, the NFL has had its opening game of the season on a Thursday Night to commence the start of American football. In 2004, the league implemented a scheduling tradition that the previous year's Super Bowl champion would host the Kickoff Game. For the next 8 years (from 2004 to 2011), the reigning Super Bowl champion won the Kickoff Game. However, the streak ended in 2012, when for the first time in the Kickoff Game's history the Super Bowl XLVI champion lost (Giants vs. Cowboys). Then last year, due to a scheduling conflict, the XLVII champion, Ravens, had to play on the road in Denver and lost in embarrassing fashion (49 - 22). Results are fairly consistent: Home team is 10 - 2, Past Champion 8 - 2, Past Champion at Home 8 - 1.    

Flash forward to Thursday night, when the Super Bowl champion and the pre-season #1 ranked team, Seahawks, host the Packers. The Seahawks are coming off the greatest regular season in its franchise's history and topped it off with 3 straight in the playoffs, including domination over Peyton and the Broncos in the Superbowl. In 2013, the Seahawks ranked 1st in rush defense, total defense, points against, defensive red zone conversions, and take-aways. On the other side of the ball, Russell Wilson ran an efficient offense that ranked 9th in yards per play and 4th in passing per play. Let’s not forget about Lynch, who pounded the football. The team averaged 137 yards rushing per game which ranked 4th in the NFL. 

The Packers, on the other hand, had a setback year after an injury to Aaron Rodgers had him sidelined him 7 games. In the games Rodgers played, the Packers were 6 - 3 (losses were @ 49ers, @ Bengals, Bears). Even with Rodgers on the bench for almost half the season, the Packers were near the top of every offensive category including rushing; rookie running back Eddie Lacy established himself as one of the leagues premier rushers. Questions all lie on the defensive side of the ball for the Packers, where they were ranked near the bottom of all major statistical categories. What will help is a new, slimmer offensive line led by Julius Peppers.

Based on our current rankings, Packers (4 , 3) Seahawks (4 , 5), the Seahawks have a 73% probability of winning at an expected margin of 7 points, which is in-line with the odds makers spread and moneyline set for the game (read NFL 2014 Season Over-Unders for more detail on how the Ranking System works). The Rank Analysis above on the left details the multiple scenarios (this box will look the same for each match-up analysis). As you can see in the Betting Analysis, there isn't a bet that yields an expected value above $5. In general I wouldn't bet anything less than $5, however, as a promise to my readers, I will always bet Thursday Night, Sunday Night and Monday Night games. Based on the analysis, the best bet is Seattle -6 -110 (Expected Value $3, Risk 3%). Risk 3% will likely be on the very low side of the wagers I take this year, but we don't love the game so it makes complete sense.

The NFL season is upon us and nothing makes me more excited for week 1 than betting team over-unders. For me I think it's both the thrill of predicting the right outcome and the idea that math could matter. Let's start with simple math. Less than or equal to 8. That will be the average amount of wins this year in the league (less than because of possible ties). Did you know the average line this year is 8.2 wins? When I saw this it was actually what I was expecting, most average bettors ride overs. But what I wasn't expecting was that the average vig on the over (or the cost to bet the over) was significantly higher than the under. On average this cost was 3 times higher. These two things don't add up. It means there are some inefficiencies with several of these odds makers' lines.


The goal of this post will be to calculate the most likely probability of each team winning greater or less than the odds makers’ over-under and correctly betting the outcomes with the greatest expected value. To do this correctly, we first need to figure out what each team’s week-by-week probabilities are of winning. 

I have developed a ranking system over the past 5 years. The concept, which isn't rocket science, is that in general a teams total wins at the end of the season is the best statistic to determine how good or bad a team is. Of course a lot goes into winning a football game and over the course of a season multiple factors contribute to the success of a team, like injuries and strength of schedule to name a few, but in the long run (over 30 years of data) these abnormalities smooth themselves out.

So I went through 30 years of data and labeled each team with a ranking of 1 to 5 driven entirely by the amount of wins the team had during the season (1: 0 - 3 wins, 2: 4 -6 wins, 3: 7 - 9 wins, 4: 10 - 12 wins, 5: 13 - 16 wins). Now if you can imagine, 7,680 games of data, each labeled with a Home Team Ranking versus a Away Team Ranking. For example, we know that during the course of the past 30 years a team ranked 3 has played another team ranked 3 (3H_3) 767 times. During these match-ups the home team won 58% of the time with a median margin of 3 points. Heres another one, a home team 4 has played an away team 3 (4H_3) 647 times. During these match-ups the home team won 77% of the time with a median margin of 7 points. 

As you can see in the exhibit above, I have given each team a ranking for this season. Its important to note that when ranking teams you need to remove the strength of schedule factor and rank teams based on how good they are. You will also notice I give each team a sub ranking. In my analysis below and in the future I weigh my outcomes (60% base and 40% sub). So for example if the Seahawks (4 , 3) are playing the Dolphins (3 , 2) I will actually calculate the probability in each scenario (4H_3, 4H_2, 3H_3, 3H_2). Weighing the probabilities gives us a little more of a diversified approach. 

Now that you know how the ranking system works we can calculate the expected probability of each team winning each week. As you can see below:

The next step is to take this data and create a random generator. The reason we generate different scenarios versus just adding up the probabilities to get an average is because a football game is binary, a team wins or loses. So to just add up .85 + .65 really doesn't tell us anything besides the average amount of games the team will win is 1.5. 

After running 5,000 iterations for each team the following data was concluded below:

As you can see above we have determined several things. The most important being the median amount of games each team is expected to win and the probabilities of each team going over and under the odds makers' line. 

A couple of things to point out on the far right columns of the exhibit above. As you can see both the Over and Under columns have columns labeled value and risk. If you frequent this site in the coming months its important to understand what these mean. Value is the expected value of a $100 wager. We will always be focusing on those bets with the highest expected value and ignore those with negative value. Risk is the amount of your bankroll you should wager and should be used to compare and size more than one bet. 

My season bets below: