Sharing and comparing my method for trying to beat the spread

I live in the Midwest which is Big Ten country. Once conference play starts virtually every Big Ten game is televised in my region and I commit myself to try and watch all of them. I have three televisions set up as some games are being played at the same time. I have no bias or affiliation to any Big Ten team as I am a lifelong Notre Dame fan (I include ND games in my viewing schedule as well). My comments and reports are qualified only by my love of the game and an extreme commitment to watching and following Big Ten football.

Monday, September 14, 2015

BIG TEN FOOTBALL WHAT HAPPENED WEEK 2


WHAT HAPPENED

The Big Ten went 12-2 over the weekend. Not bad, but the schedule wasn’t near as competitive as the week 1 slate. My only prediction qualified as a play and turned out to be a loser. Bummer. I hate falling behind early. Plenty of opportunities ahead, though.
My record:  0-1


THE PLAYS
Notre Dame 34  Virginia 27   (Notre Dame -12.5)
I predicted Notre Dame to win, 38-10. I was wondering if Notre Dame looked so good in week 1 because the Irish are good or if Texas is bad. Turns out, Texas is bad. Well, Notre Dame isn’t as good as I thought they were, anyway. And it cost me a loss here. But as I said in my prediction write-up, I would’ve liked to have had more to go on than just one week of play. Week two predictions always involve a bit of guesswork and you can only use the info that’s available. I know now that ND is a good, but not great team. And losing starting QB Malik Zaire can only diminish their status. At least in the short term. His backup did step up and win the game so, who knows, he could eventually turn out to be as good as Zaire after he gets some more playing time under his belt. Where I went wrong in this game was overvaluing ND’s defense and/or defensive scheme. If you’re gonna blitz every down you better get there. And while the Irish didn’t “get there” very often, they were on many occasions able to force the Virginia QB into throwing floating pop flies, which is usually good enough for most teams. But the Irish secondary was, I dunno, taking pictures or something instead of making a play on the ball.



ATS

FTC DOLLARS
In this section I track the results of my Crystal Ball selections that qualify as “plays” ATS (any prediction that differs from the closing line by seven or more points). I’ve also included the results of some unsuspecting prognosticators that I found on line. The standings are based on how many “FTC” dollars are won. For a more detailed explanation of this section, please refer to the “FTC $ Q&A” tab at the top of this post.

Nothing to compare yet in this post but next week I’ll be comparing predictions on an oddly placed conference game as Rutgers travels to Penn St.


NOTRE DAME
I predict Notre Dame games along with the Big Ten conference games. Other than the occasions when Notre Dame plays a Big Ten team, these predictions aren’t included in the standings/comparisons as my competition doesn’t make predictions for Notre Dame vs non-Big Ten conference games. Listed below is my stats for Notre Dame games that aren’t included in the standings.

PLAYS
SPREAD RECORD
CLOSEST
WITHIN 7
STRAIGHT UP
W
L
T
W
L
W
L
W
L
W
L
0
1
0
0
1
0
1
0
1
1
0

SPREAD RECORD Simply displays the ATS record.
STRAIGHT UP- The outright winner, disregarding the spread.
WITHIN 7-This category tracks how many times a predicted point spread was within seven points of the final score differential. Why does this matter? Because one can never lose in the play category if the prediction is within 7 points. 35 percent is about average in this category. Close to 50 percent is excellent.
CLOSEST - It’s possible to be on the correct side of the spread yet not be as accurate as the oddsmakers. EX: If I predict Michigan by 12, the spread is 6, and Michigan wins by 7, I get a win in the spread record category. I get a loss in the closest category because the spread (7-6=1) was closer than my prediction (12-7=5).

Any games that go into overtime will be considered a tie when calculating the “closest” and “within 7” category. The actual score will be used, however, for the other two categories.



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