College Basketball Totals Analysis

Model, Sport Models | | February 17, 2010 at 12:01 pm

basketball1A 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%291344.8% $1,755.57 $156.868.9%
50.0%52.5%1648350.6% $11,313.28 $778.176.9%
52.5%55.0%106155352.1% $75,592.22 $3,215.07 4.3%
55.0%57.5%130966650.9% $131,974.51 $1,906.40 1.4%
57.5%60.0%64235855.8% $95,004.01 $9,778.26 10.3%
60.0%62.5%27114252.4% $52,796.98 $1,711.57 3.2%
62.5%65.0%1096963.3% $26,113.11 $6,222.92 23.8%
65.0%67.5%512752.9% $15,069.52 $1,230.48 8.2%
67.5%70.0%20945.0% $6,707.23 -$1,181.55 -17.6%
70.0%100.0%211047.6% $9,535.93 -$554.67-5.8%
3677193052.5% $425,862.36 $23,263.53 5.5%
Odds#Bets#Won%Won$Bet$Profit%ROI
1.501.757685.7% $1,069.66 $561.7852.5%
1.751.8011981.8% $1,477.92 $245.8816.6%
1.801.85593152.5% $7,585.87 -$689.62-9.1%
1.851.9019110756.0% $25,147.16 $1,130.81 4.5%
1.901.951941102252.7% $227,107.66 $13,561.47 6.0%
1.952.0088945250.8% $96,900.41 $1,870.84 1.9%
2.002.0532416851.9% $36,107.08 $2,647.40 7.3%
2.052.10965759.4% $10,924.59 $2,486.98 22.8%
2.102.151065652.8% $12,122.78 $2,008.61 16.6%
2.155.00532241.5% $7,419.22 -$560.64-7.6%
3677193052.5% $425,862.36 $23,263.53 5.5%
Overlay#Bets#Won%Won$Bet$Profit%ROI
0.0%7.5%119463152.8% $77,120.17 $3,135.54 4.1%
7.5%10.0%79838247.9% $72,374.74 -$3,884.83 -5.4%
10.0%12.5%58531553.8% $68,130.16 $5,236.22 7.7%
12.5%15.0%36921157.2% $52,136.69 $7,433.49 14.3%
15.0%17.5%26313451.0% $44,155.16 $1,233.40 2.8%
17.5%20.0%1719555.6% $33,109.03 $3,492.36 10.5%
20.0%22.5%1156153.0% $24,721.28 $1,854.80 7.5%
22.5%25.0%574070.2% $13,728.45 $5,629.60 41.0%
25.0%30.0%773950.6% $21,992.81 $348.181.6%
30.0%100.0%482245.8% $18,393.88 -$1,215.22 -6.6%
3677193052.5% $425,862.36 $23,263.53 5.5%
Av.Game Year#Bets#Won%Won$Bet$Profit%ROI
0217635.3% $2,217.06 -$743.50-33.5%
23512651.0% $7,736.31 $50.220.6%
3524814357.7% $37,311.13 $6,439.45 17.3%
57.530514748.2% $42,139.82 $1,011.08 2.4%
7.51043123153.6% $54,078.34 $3,070.19 5.7%
101584445353.7% $95,444.76 $7,169.38 7.5%
152080742652.8% $85,845.07 $4,531.85 5.3%
202560130350.4% $61,219.26 -$877.63-1.4%
253034418152.6% $36,126.01 $1,941.86 5.4%
301000291448.3% $3,744.59 $670.6317.9%
3677193052.5% $425,862.36 $23,263.53 5.5%
Expected Total#Bets#Won%Won$Bet$Profit%ROI
5010011436.4% $2,124.49 -$207.71-9.8%
10012037118850.7% $52,494.75 $2,120.18 4.0%
12012533218956.9% $39,706.76 $5,573.78 14.0%
12513045923250.5% $53,519.48 $374.310.7%
13013557730753.2% $63,379.49 $3,993.30 6.3%
13514057129852.2% $60,341.81 $3,446.57 5.7%
14014550526352.1% $56,916.36 $3,644.13 6.4%
14515037920453.8% $42,840.42 $1,604.92 3.7%
15015521912155.3% $22,875.44 $2,672.27 11.7%
155100025312449.0% $31,663.34 $41.780.1%
3677193052.5% $425,862.36 $23,263.53 5.5%
Total Line#Bets#Won%Won$Bet$Profit%ROI
501003133.3%$453.12-$95.31-21.0%
10012028013548.2% $35,059.80 -$600.89-1.7%
12012531617756.0% $35,694.55 $4,809.03 13.5%
12513050626151.6% $55,938.05 $1,481.86 2.6%
13013568236553.5% $75,791.91 $5,578.91 7.4%
13514060632553.6% $66,279.18 $7,459.18 11.3%
14014553227351.3% $61,753.34 -$80.23-0.1%
14515037119051.2% $44,532.89 $2,533.96 5.7%
15015520811856.7% $24,719.16 $2,587.90 10.5%
15510001738549.1% $25,640.35 -$410.91-1.6%
3677193052.5% $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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1 Comment

  1. plsmove says:

    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

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