Week 2 College Football six pack predictions


College football returned a little too early for me. See, I had big plans to mine college football player data to build statistical models that would surely lead to better predictions. (This is just a fancy way of saying I wanted to compare rosters regarding the players’ ranking.) Last year’s disappointing showing against the computer’s random number generator demanded change. Unfortunately, real life got in the way, so I didn’t get the data model built. This means I’m left with the normal, “Go with the gut” strategy, which means please, please don’t use these predictions to bet real money. Now that the disclaimer is out of way, let’s go.

Utah at BYU (-1)

BYU’s offense should find the end zone this week a little more often than the previous one – well, that’s sort of glossing over the fact that just finding the end zone once bests last week’s zero trips over the goal line as LSU blanked BYU 27-0. Utah scored 30+ points on a team that was not the same caliber as LSU (sorry North Dakota). Look for BYU to bounce back and win.

Winner: BYU (-1)

Computer prediction: Utah

TCU (-3) at Arkansas

Who is the best college football team out of Texas right now? Is it TCU? Anyway, their opponent Arkansas, hailing from the SEC where apparently “it just means more” (yep I am weary of this ad already), can’t seem to climb out of mediocrity. Ah, the motorcycle ride that derailed hopes and dreams. Arkansas will make one more play to win this game.

Winner: Arkansas (+3)

Computer prediction: TCU

South Carolina at Missouri (-2.5)

Just when you think you can’t pick a Will Muschamp coached team on the road, a scenario like this one presents itself: It’s early in the year. The opposing team doesn’t seem to play much defense, so a few defensive stops should seal the deal since the Gamecocks may actually put up some points this week. (I am sure to regret this pick.)

Winner: South Carolina (+2.5)

Computer prediction: Missouri

Auburn at Clemson (-5.5)

One of the joys in life is listening to local sports talk radio while driving to work, lunch, or wherever, because the chances of listening to opinions that bring on some gut-busting laughter are as probable as me buying wings on a football Saturday: 99.5%. The latest example – this Auburn team has the most talent than any previous version. Yep, the most talent, ever. More than one person said this, too. Seriously, I almost wrecked my car from laughing, but hey, I guess it’s theoretically possible that Auburn rolls to an undefeated season this year. Their defense looked great against an undersized team last week. Let’s see how they do against a Clemson team that actually matches up with them physically. Clemson ends the dream.

Winner: Clemson (-5.5)

Computer prediction: Auburn

Stanford at USC (-7)

Do I believe in Sam Darnold? Yes, and I think there are more scenarios where USC claims victory, but I think the Stanford defense will force a costly turnover to earn the victory.

Winner: Stanford (+7)

Computer prediction: Stanford

Oklahoma at Ohio State (-7.5)

Baker Mayfield is a problem for Ohio State, and I trust him more to make more plays than J.T. Barrett. Is that enough? Barrett threw for multiple touchdowns last week, but Ohio State should have dominated that game from the opening whistle, and the offense didn’t look sharp in the beginning. However, no one should short change Ohio State’s talent. Plus, Urban Meyer is one of the best coaches in the game. Ohio State will have enough offensive weapons to counter Mayfield, and the defensive line will make things tough.

Winner: Ohio State (-7.5)

Computer prediction: Oklahoma

Enjoy the games!



(Attribution for the sports logos: By Clemson University Uploaded by Zscout370 at en.wikipedia [Public domain], via Wikimedia Commons, By Stanford University (12-03-2016 Game Notes MBB) [Public domain], via Wikimedia Commons, By USC Trojans (http://www.usctrojans.com/) [Public domain], via Wikimedia Commons,  By The original uploader was Buckeyes1186 at English Wikipedia (Transferred from en.wikipedia to Commons.) [Public domain], via Wikimedia Commons, By University of Oklahoma [Public domain], via Wikimedia Commons )



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