Predictions, best bets and odds for every college football match in Week 12: Athletic’s model projects every game

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Austin Mock’s projection model is derived from play-by-play data, adjusted for opponent, home/away, at rest, and then produces a point projection for (xPF) and points against (xPA) for each team at the FBS level. From there, the model then produces a projected split and a total based on all of the model’s inputs for each game. For the past two seasons, this model has outperformed the sports betting market. To learn more about the model, check out Austin’s introductory article on his model.

In Fuego. Maybe that’s how you define my model’s performance over the past three weeks. After a small rough patch, the model responded with three consecutive profitable weeks that all brought in at least 1.80 units of profit, including 2.90 units last week.

I mentioned earlier in the year that most bettors tend to remember bad losses and that I would try to recognize both bad hits and ‘bad wins’ and, my goodness, did we got lucky Friday night last week. Let’s summarize.

In what was almost a bad beat, Wyoming scored with four seconds left on a 74-yard pass to get back in the count. The Cowboys had been outnumbered all game, but Boise State fired a field goal with 59 seconds left to go up 16. Luckily for us, the bad beat lasted less than a minute.

Outside of this game, things went pretty well. North Carolina and Pitt went to overtime but never sniffled, Vanderbilt came out slow but went through the backdoor as Kentucky came out pretty flat in the second half and sat in the lead, as I l had predicted. All in all a great week.

Last week’s record: 4-1 (+2.90 units)

Summary of the season: 45-36-36 (+5.65 units, 6.1% ROI)

Bets of week 12

All bets must win one unit on the favorites and risk one unit on the underdogs. All odds are sourced from BetMGM and are locked when the pick has been made.

UAB +4.5 (-110) at UTSA

The betting market has been all over UAB this week as you could have gotten that line at +6 earlier in the week and we have now brought that key number down to +4.5. I still love him. There is not much that separates these teams according to my model and I am not giving UTSA 4.5 points for home advantage. Certainly, when it comes to games, I can see things turning sour for UAB as they are more efficient at handling the ball and the UTSA rush defense has been excellent so far this season. On the other side of the ball, UAB is more sensitive to the pass while UTSA is very effective in the air. With all that being said, I still have an advantage over UAB here. It should be closer to a field goal as I expect the Blazers to give UTSA everything they can manage to keep their undefeated season alive.

Model projection: UTSA 28.2, UAB 25.6

Troy +9.5 (-110) vs Appalachian State

I would really like to have +10 here, but +9.5 still shows enough advantage to have a game here. Troy has a pretty solid defense and they will need a big defensive effort to stay in numbers in this one. Because the Trojans aren’t building up an effective offense (the last 30 by my model), they find themselves playing in a lot of tight games. Troy can’t afford to waste scoring chances if he wants to cover this one, but in what should be a low scoring affair, I think that number is just too high. Appalachian State still needs to clinch the Sun Belt East Division so the Mountaineers don’t fold here, but I think Troy at home is fighting pretty well here.

Model projection: Appalachian State 28.1, Troy 22

Kent State to Akron under 74.5 (-110)

Hold your nose. This one is pretty crude. This is one of those games where there is no possible way to watch it live on TV. Go do something else. Literally anything. I promise you, it’s not worth it.

Let’s start with Kent State. Over the past two weeks, they’ve played games that ended with 99 and 84 points. Combine that with Akron playing a game with 85 points and you’ll find an inflated total the following week. Sure, Kent State likes to play fast but Akron likes to play slow. A common theme this year, if you’ve been following my articles on a weekly basis, is the betting market overreacting to the previous week. This is another example, in my opinion. This game could easily fly over that number, but given how slow Akron is and how bad his offense is, I can’t ignore that advantage.

Model Projection: Kent State 40.2, Akron 29.4

Texas Tech +10.5 (-110) vs. Oklahoma State

Attention, but I think Texas Tech is live in this location. Oklahoma State’s offense isn’t great. This team really relies on their defense – the top 10 in my model – to win football games. They are coming off a 63-point outburst against TCU at home. This week, however, they go on the road and the offense has been non-existent on the road this year. In four games on the road, Oklahoma State’s offense averaged just 24.5 points per game and 336 yards. Texas Tech’s defense is by no means good, but if they can catch the struggling Oklahoma State offense early, the Red Raider offense is good enough to rack up the points. Add to that the fact that Oklahoma State has Bedlam next week and it has all the ingredients for an upset. I’ll gladly take the 10.5 points here and sprinkle it on the moneyline.

Model projection: Oklahoma State 30, Texas Tech 23.9

USC +3 (-105) vs. UCLA

USC is currently 4-5 with three games remaining. They play UCLA, BYU and Cal while needing two wins to become bowl eligible. I expect everything and the kitchen sink to be thrown at that UCLA team with the Trojans planning to go bowling. Jaxson Dart should start and the full starting reps should have the talented freshman ready to compete in this cross-town rivalry game.

OK, that was a bit subjective. What is the model thinking? First off, my role model doesn’t like either defense in this game, but USC’s defense is much better against the rush than against the pass (119th pass defense in EPA/Play) and the he UCLA offense is one of the best running teams in the country. Both offenses should score points here, but USC might be able to slow Chip Kelly’s rushing offense just enough to pull off the upset. Get a cart here? Thanks very much.

Model projection: UCLA 33.9, USC 32.3

Full Week 12 Model Projections

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Team propagated BetMGM Total BetMGM O/U

-1.5

-0.7

61

59.5

-1

-1.5

63.1

61

-16.2

-19.5

62.2

60.5

-1.6

-1.5

52.2

52

-11.6

-15.5

51.2

52.5

-7.5

-8.5

58.3

60.5

-8.3

-10.5

42.1

41

-14.2

-15.5

51.7

50

-2.6

-4.5

53.8

53

-6.1

-9.5

50.1

52.5

-1.3

-3

58.8

59.5

-17.8

-20.5

54.3

58.5

-14.3

-16.5

64

65.5

-6.2

-7

46.2

44.5

-1

-1.5

50

49.5

-17.7

-19.5

55.2

57

-2.8

-1.5

46.4

45

-1

-1.5

53.2

54

-24.3

-30.5

56.1

55.5

-3.2

-3.5

46.1

46.5

-7.3

-8.5

67.9

69.5

-8.9

-10.5

63.3

64.5

-1.4

-1.5

53.3

54.5

-14.2

-17

60.7

59.5

-9.8

-12.5

38.3

38.5

-4.5

-4

60.3

61

-19.7

-21.5

64.4

64.5

-10.9

-13.5

69.6

74.5

-4.3

-4

52.3

53.5

-25.4

-28.5

57.5

57

-10.4

-14.5

60.8

61.5

-32.5

-37.5

55.1

56

-13.1

-14.5

55.8

56.5

-15.7

-18.5

67

66.5

-6.2

-7

44.3

43.5

-8.6

-9.5

43.6

42

-24.5

-27.5

47.9

48

-32.5

-35.5

60

59.5

-7.9

-ten

59

57.5

-6.1

-10.5

54

56.5

-3.1

-4.5

51.5

50.5

-2.7

-3

56.3

58.5

-6.9

-10.5

49.4

47.5

-9.4

-ten

47.1

47

-15

-17.5

47

47.5

-23.6

-28.5

59.4

61.5

-4.4

-5.5

57.8

60

-12

-11.5

62

64.5

-9.6

-11.5

51.1

50.5

-18.9

-21.5

50.6

50.5

-2.4

-2.5

56.9

56.5

-18.1

-23.5

59.1

61.5

-1.6

-3

66.1

65.5

-28.4

-36.5

62

64.5

-12.3

-14

68.2

66.5

Miami (FL)

-6.8

-8

56.4

55.5

-5.7

-4.5

57.9

56.5

-5.3

-6.5

43.9

43.5

-3.8

-5.5

52.2

52.5

(Photo by Reggie Pearson Jr. and Eric Monroe: John E. Moore III/Getty Images; The Athletic may receive an affiliate commission if you open an account with BetMGM through the links in the article above.)

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