2014 NFL Betting Picks - Week 9
Pick 1: San Diego +1.5 
Pick 2: Indianapolis -3 
Pick 3: Philadelphia -2
Pick 4: Kansas City -9.5
Two losing weeks in a row starts to get me a bit nervous. Regardless of the long-term strategy, we need to pick up the pace this week with 4 solid picks. I felt that all three picks last week were the right ones given the circumstances and the data. This week I'm also feeling comfortable with the games that were selected by the probability of covering the spread as well as the final pick. Below you will find the free nfl point spread picks for the non-premium picks and members should be receiving the premium picks shortly.
This week we again use 18% of bankroll split evenly across our 4 premium games giving us a bet of about $420 per game. Below are the computer-based NFL point spread predictions for week 9 of the NFL:
How to read the table:
Pick 2: Indianapolis -3
Pick 3: Philadelphia -2
Pick 4: Kansas City -9.5
Two losing weeks in a row starts to get me a bit nervous. Regardless of the long-term strategy, we need to pick up the pace this week with 4 solid picks. I felt that all three picks last week were the right ones given the circumstances and the data. This week I'm also feeling comfortable with the games that were selected by the probability of covering the spread as well as the final pick. Below you will find the free nfl point spread picks for the non-premium picks and members should be receiving the premium picks shortly.
This week we again use 18% of bankroll split evenly across our 4 premium games giving us a bet of about $420 per game. Below are the computer-based NFL point spread predictions for week 9 of the NFL:
| Game | Vegas Line | Estimate | Prediction-Vegas | Confidence |
|---|---|---|---|---|
| SAN DIEGO @ MIAMI | -1 | 3.9 | 4.9 | 61.0% |
| INDIANAPOLIS @ NY GIANTS | 3 | 8.4 | 5.4 | 60.8% |
| PHILADELPHIA @ HOUSTON | 2.5 | 5.5 | 3.0 | 58.5% |
| NY JETS @ KANSAS CITY | -10 | -23.6 | -13.6 | 57.5% |
| OAKLAND @ SEATTLE | -15 | -20.0 | -5.0 | 54.3% |
| DENVER @ NEW ENGLAND | 3 | 6.3 | 3.3 | 54.1% |
| WASHINGTON @ MINNESOTA | 0 | 2.9 | 2.9 | 50.0% |
| TAMPA BAY @ CLEVELAND | -6.5 | -5.8 | 0.7 | 50.0% |
| BALTIMORE @ PITTSBURGH | 0 | 2.3 | 2.3 | 50.0% |
| ARIZONA @ DALLAS | -3.5 | 0.1 | 3.6 | 49.7% |
| NEW ORLEANS @ CAROLINA | 3 | -5.0 | -8.0 | 49.1% |
| JACKSONVILLE @ CINCINNATI | -11 | -18.5 | -7.5 | 48.4% |
How to read the table:
- Vegas Line: A NEGATIVE number implies the point spread favors the HOME team
- Estimate: NFL Pickles' point spread prediction
- Pred-Vegas: Subtraction: POSITIVE implies VISITING team will cover point spread.
- Confidence: The probability that the point spread pick is on the correct side.
Comments
Just like last week when they were all over Indy against Pittsburgh.
Same thing tonight.
Public was all over San Diego this week and, well, errrr....
Humans are not robots, they have ups and downs. If the games were decided by the stats then in theory we could figure out the likely winners consistently. But this year especially you can see that these teams are very inconsistent sans a few.
The guys making the lines can sucker the public in by knowing how the public is thinking. With stats you can see where the line doesn't make sense, but that doesn't mean you are still on the right side!....
You are right about humans playing games, not robots. The counter argument could be that you are using historic data of games, also played by humans, to make decisions.
Jaime has referenced a few times the term 'vegas finish'. If I understand it correctly, it's when a game is completely a blowout, and ends up finishing near the line. These games drive me crazy. Last night's game started to worry me, just because I've been screwed so many times by these Vegas finishes. Indy was up by 30(?), and my wagers looked like a certain win. Next thing you know, it's 16 points, and the Giants are getting the ball back.
I truly prefer betting games straight up, because teams play to win, not to win by 7.5, or to cover a +3.5 line. I think straight up games are where the human factor aligns closer with what the computer generates. Unfortunately, being able to predict that Denver will take out Oakland this week isn't rewarded very well.
Fine if the teams play exactly to their stats but....
As we know they don't week in and week out, and so you need to combine BOTH statistical analysis as well as the situations the teams are in.
The other thing KILLING statistical analysis in the NFL is INJURIES. It is getting impossible to compare teams performances with teams fielding different players each week. Comapring Team A in week 5 when team A had two backups on the offensive line, versus Team A in week 1 when healthy are two distinct animals. This is the biggest challenge for me as a statistical handicapper.
The only approach that I think will work is to dive down into a play level analysis of each game to get a full understanding of how valuable each individual player is per team and then base your team ratings on those. This has the benefits of providing you a great starting point at the beginning of the season when rosters have been shuffled.
I'm no where near that point since I'm still using team based stats for my models but it's a good goal to have.
Stats are not perfect but the hope is that they give us a slight advantage over the market.
Injuries are my weakness. Many of you that have followed me know that I try to stay away from games where there are significant injuries, i.e. injuries from main QB or RB. I wish I had player level data, but even if I did would need time and help in making sense of it.
When the line doesn't make sense could be an opportunity or could be something that the model is completely ignoring. That's why you need humans, I agree. But too much human intervention and you stray away from stats which defeats the purpose. All I do is stay away from a game that has injuries, is not at home, there's huge weather issues or some other thing not accounted by my models that will significantly change the outcome of the game.