College Basketball Predictor: NCAAB Lines and Spreads

NCAAB Predictor

DateTeam 1Team 2Score PredictionConfidenceBetting predictions Team 1 WinBetting predictions Team 2 WinFinal Score

22nd Mar 2025,

11:30 EDT

Dayton
1.740
Chattanooga
2.150
79:77
62.1%
52%48%

22nd Mar 2025,

12:10 EDT

McNeese St.
3.240
Purdue
1.374
90:83
86.3%
57%43%
11:22

22nd Mar 2025,

14:00 EDT

Bradley
George Mason
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22nd Mar 2025,

14:40 EDT

Arkansas
3.480
St. John's
1.333
77:85
65.7%
42%58%

22nd Mar 2025,

17:15 EDT

Michigan
2.281
Texas A&M
1.665
76:81
59.9%
45%55%

22nd Mar 2025,

18:10 EDT

Drake
Texas Tech
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22nd Mar 2025,

19:10 EDT

Creighton
3.990
Auburn
1.210
78:75
54.1%
53%47%

22nd Mar 2025,

19:45 EDT

Brigham Young
2.000
Wisconsin
1.833
67:87
44.7%
30%70%

22nd Mar 2025,

20:40 EDT

Gonzaga
Houston
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22nd Mar 2025,

21:40 EDT

UCLA
2.846
Tennessee
1.454
74:94
69.1%
30%70%

Value bets for today based on Scores Predictor:

DateTeam 1Team 2Score PredictionTotalBookmaker TotalFinal ScoreValue Bet

22nd Mar 2025,

11:30 EDT

Dayton
1.740
Chattanooga
2.150
79:77
156154.50Bet over 154.50

22nd Mar 2025,

12:10 EDT

McNeese St.
3.240
Purdue
1.374
90:83
173141.50
11:22
Bet over 141.50

22nd Mar 2025,

14:40 EDT

Arkansas
3.480
St. John's
1.333
77:85
162145.50Bet over 145.50

22nd Mar 2025,

17:15 EDT

Michigan
2.281
Texas A&M
1.665
76:81
157142.50Bet over 142.50

22nd Mar 2025,

19:10 EDT

Creighton
3.990
Auburn
1.210
78:75
153149.50Bet over 149.50

22nd Mar 2025,

19:45 EDT

Brigham Young
2.000
Wisconsin
1.833
67:87
154155.50Bet under 155.50

22nd Mar 2025,

21:40 EDT

UCLA
2.846
Tennessee
1.454
74:94
168131.50Bet over 131.50

Value bets for today based on Scores Predictor and Kelly Criterion:

What is Kelly Criterion?

The Kelly Criterion is a bet-sizing technique which balances both risk and reward for the advantage gambler. It determines the optimal % of your total capital (ie bankroll) that you can bet on a single outcome or game. Here is the formula for the Kelly Criterion copied from Wikipedia:

Where:

  • f* is the fraction of the current bankroll to wager;
  • b is the net odds received on the wager (“b to 1”); that is, you could win $b (plus the $1 wagered) for a $1 bet
  • p is the probability of winning;
  • q is the probability of losing, which is 1 − p.

As an example, if a gamble has a 60% chance of winning (p = 0.60, q = 0.40), and the gambler receives 1-to-1 odds on a winning bet (b = 1), then the gambler should bet 20% of his bankroll at each opportunity (f* = 0.20), in order to maximize the long-run growth rate of the bankroll.

If the gambler has zero edge, i.e. if b = q / p, then the criterion recommends the gambler bets nothing.

If the edge is negative (b < q / p) the formula gives a negative result, indicating that the gambler should take the other side of the bet.

DateTeam 1Team 2Optimal Stake PartBet OnFinal Score

22nd Mar 2025,

12:10 EDT

McNeese St.
3.240
Purdue
1.374
0.38
McNeese St. ML
11:22

22nd Mar 2025,

14:40 EDT

Arkansas
3.480
St. John's
1.333
0.19
Arkansas ML

22nd Mar 2025,

19:10 EDT

Creighton
3.990
Auburn
1.210
0.37
Creighton ML

22nd Mar 2025,

19:45 EDT

Brigham Young
2.000
Wisconsin
1.833
0.34
Wisconsin ML