A lot of talk in the forum has been with regards to college basketball and the fact that the higher overlays this year have been losses, as opposed to last year when the higher overlays generally performed very well.
Is this just random variation or perhaps the model struggles at higher overlays due to injured players and the like? Well we thought we’d find out.
Shown below is the analysis of the College basketball since the start of the 2005/2006 season for betting overs and unders.
ALL
Prob #Bets #Won %Won $Bet $Profit %ROI
45.0% 50.0% 29 13 44.8% $1,755.57 $156.86 8.9%
50.0% 52.5% 164 83 50.6% $11,313.28 $778.17 6.9%
52.5% 55.0% 1061 553 52.1% $75,592.22 $3,215.07 4.3%
55.0% 57.5% 1309 666 50.9% $131,974.51 $1,906.40 1.4%
57.5% 60.0% 642 358 55.8% $95,004.01 $9,778.26 10.3%
60.0% 62.5% 271 142 52.4% $52,796.98 $1,711.57 3.2%
62.5% 65.0% 109 69 63.3% $26,113.11 $6,222.92 23.8%
65.0% 67.5% 51 27 52.9% $15,069.52 $1,230.48 8.2%
67.5% 70.0% 20 9 45.0% $6,707.23 -$1,181.55 -17.6%
70.0% 100.0% 21 10 47.6% $9,535.93 -$554.67 -5.8%
3677 1930 52.5% $425,862.36 $23,263.53 5.5%
Odds #Bets #Won %Won $Bet $Profit %ROI
1.50 1.75 7 6 85.7% $1,069.66 $561.78 52.5%
1.75 1.80 11 9 81.8% $1,477.92 $245.88 16.6%
1.80 1.85 59 31 52.5% $7,585.87 -$689.62 -9.1%
1.85 1.90 191 107 56.0% $25,147.16 $1,130.81 4.5%
1.90 1.95 1941 1022 52.7% $227,107.66 $13,561.47 6.0%
1.95 2.00 889 452 50.8% $96,900.41 $1,870.84 1.9%
2.00 2.05 324 168 51.9% $36,107.08 $2,647.40 7.3%
2.05 2.10 96 57 59.4% $10,924.59 $2,486.98 22.8%
2.10 2.15 106 56 52.8% $12,122.78 $2,008.61 16.6%
2.15 5.00 53 22 41.5% $7,419.22 -$560.64 -7.6%
3677 1930 52.5% $425,862.36 $23,263.53 5.5%
Overlay #Bets #Won %Won $Bet $Profit %ROI
0.0% 7.5% 1194 631 52.8% $77,120.17 $3,135.54 4.1%
7.5% 10.0% 798 382 47.9% $72,374.74 -$3,884.83 -5.4%
10.0% 12.5% 585 315 53.8% $68,130.16 $5,236.22 7.7%
12.5% 15.0% 369 211 57.2% $52,136.69 $7,433.49 14.3%
15.0% 17.5% 263 134 51.0% $44,155.16 $1,233.40 2.8%
17.5% 20.0% 171 95 55.6% $33,109.03 $3,492.36 10.5%
20.0% 22.5% 115 61 53.0% $24,721.28 $1,854.80 7.5%
22.5% 25.0% 57 40 70.2% $13,728.45 $5,629.60 41.0%
25.0% 30.0% 77 39 50.6% $21,992.81 $348.18 1.6%
30.0% 100.0% 48 22 45.8% $18,393.88 -$1,215.22 -6.6%
3677 1930 52.5% $425,862.36 $23,263.53 5.5%
Av.Game Year #Bets #Won %Won $Bet $Profit %ROI
0 2 17 6 35.3% $2,217.06 -$743.50 -33.5%
2 3 51 26 51.0% $7,736.31 $50.22 0.6%
3 5 248 143 57.7% $37,311.13 $6,439.45 17.3%
5 7.5 305 147 48.2% $42,139.82 $1,011.08 2.4%
7.5 10 431 231 53.6% $54,078.34 $3,070.19 5.7%
10 15 844 453 53.7% $95,444.76 $7,169.38 7.5%
15 20 807 426 52.8% $85,845.07 $4,531.85 5.3%
20 25 601 303 50.4% $61,219.26 -$877.63 -1.4%
25 30 344 181 52.6% $36,126.01 $1,941.86 5.4%
30 1000 29 14 48.3% $3,744.59 $670.63 17.9%
3677 1930 52.5% $425,862.36 $23,263.53 5.5%
Expected Total #Bets #Won %Won $Bet $Profit %ROI
50 100 11 4 36.4% $2,124.49 -$207.71 -9.8%
100 120 371 188 50.7% $52,494.75 $2,120.18 4.0%
120 125 332 189 56.9% $39,706.76 $5,573.78 14.0%
125 130 459 232 50.5% $53,519.48 $374.31 0.7%
130 135 577 307 53.2% $63,379.49 $3,993.30 6.3%
135 140 571 298 52.2% $60,341.81 $3,446.57 5.7%
140 145 505 263 52.1% $56,916.36 $3,644.13 6.4%
145 150 379 204 53.8% $42,840.42 $1,604.92 3.7%
150 155 219 121 55.3% $22,875.44 $2,672.27 11.7%
155 1000 253 124 49.0% $31,663.34 $41.78 0.1%
3677 1930 52.5% $425,862.36 $23,263.53 5.5%
Total Line #Bets #Won %Won $Bet $Profit %ROI
50 100 3 1 33.3% $453.12 -$95.31 -21.0%
100 120 280 135 48.2% $35,059.80 -$600.89 -1.7%
120 125 316 177 56.0% $35,694.55 $4,809.03 13.5%
125 130 506 261 51.6% $55,938.05 $1,481.86 2.6%
130 135 682 365 53.5% $75,791.91 $5,578.91 7.4%
135 140 606 325 53.6% $66,279.18 $7,459.18 11.3%
140 145 532 273 51.3% $61,753.34 -$80.23 -0.1%
145 150 371 190 51.2% $44,532.89 $2,533.96 5.7%
150 155 208 118 56.7% $24,719.16 $2,587.90 10.5%
155 1000 173 85 49.1% $25,640.35 -$410.91 -1.6%
3677 1930 52.5% $425,862.36 $23,263.53 5.5%
One can see good profits are made across all odds, and with the exception of probabilities greater than 67.5%. As far as overlays go, overlays less than 10% lost slightly, whilst overlays greater than 25% lost.
This adds to the theory that the highest of overlays are not profitable. This is a bit of a concern, as a good model should increase profit with increased overlay. Quite clearly there is something missing in the model, and the most likely answer is player injuries and/or players returning after being absent.
The 3rd last table, shows the average matches that both teams have played throughout the year and the profits that are seen. Clearly it shows that for the first 2 rounds, it is wise not to bet on any of the teams on the unders and overs, however, the sample size is only a mere 17 bets.
And the final two tables, look at the expected total as well as the total line. Interestingly when the expected and line is small or large, less profit is made.
So what does this mean? It means that one should be careful when betting on overlays greater than 25%. I don’t recommend not betting on overlays that are greater than 25%, such a decision is not really practical for many when searching for best odds. But the problem occurs when greater overlays result in greater bet sizes. So perhaps the best option might be to cap the overlay at 25%, so that one isn’t over betting on the higher overlays.
Either way, we will look at the analysis, separating by overs and unders next, and this might well provide even more interesting results.
Sportpunter’s free College Basketball predictions are shown here
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Lets say that something (like injury you mentioned Jon) happens that model can’t include. As sharps are more popular in NCAAB, we can expect them to move odds opposite our direction. Model shows greater overound but we can expect this to be false. I think that 25 cap is very good option.
Thanks for analysis, i love them