A bit more NBA analysis

Posted on November 15, 2010 by admin

Shown below is a bit more NBA analysis with regards to line betting for away and home teams.

This is the models suggested bets over the past few years. “AwayLine” refers to betting on the away team at the following line (the line for the away team), whilst “HomeLine” refers to betting on the home team at the line (the away line).

Confusing yes, but it just means betting the home or away team.

There’s not a lot to make of it which is a shame, higher prices overlays on away favourites seem to have done particularly good.

Line#Bets#Won%Won$Bet$Profit%ROI
-50-540518144.7% $74,670.72 -$9,860.37 -13.2%
-5-244122851.7% $77,170.80 -$3,040.56 -3.9%
-2022011954.1% $40,907.01 $3,896.33 9.5%
01748748100.0%$-$-#DIV/0!
1336418651.1% $61,225.07 -$3,924.02 -6.4%
3552429957.1% $91,641.80 $7,304.90 8.0%
5758431654.1% $105,507.33 -$2,917.56 -2.8%
7948624249.8% $94,316.71 -$7,744.10 -8.2%
91248226254.4% $100,812.71 $3,491.41 3.5%
125030014648.7% $67,040.16 -$424.36-0.6%
4554272759.9% $713,292.32 -$13,218.34 -1.9%
AwayLine#Bets#Won%Won$Bet$Profit%ROI
-50-51446444.4% $20,687.88 -$1,596.41 -7.7%
-5-222311551.6% $37,883.63 -$476.98-1.3%
-201186555.1% $21,133.10 $1,541.78 7.3%
01374374100.0%$-$-#DIV/0!
1319710151.3% $33,964.80 -$1,703.13 -5.0%
3533318054.1% $60,577.68 $1,167.36 1.9%
5742021751.7% $82,932.90 -$4,464.32 -5.4%
7935517649.6% $76,077.98 -$4,987.75 -6.6%
91234918753.6% $82,160.84 $1,070.51 1.3%
125022911751.1% $56,589.09 $1,016.77 1.8%
2742159658.2% $472,007.91 -$8,432.17 -1.8%
HomeLine#Bets#Won%Won$Bet$Profit%ROI
-50-526111744.8% $53,982.85 -$8,263.96 -15.3%
-5-221811351.8% $39,287.17 -$2,563.58 -6.5%
-201025452.9% $19,773.91 $2,354.55 11.9%
01374374100.0%$-$-#DIV/0!
131678550.9% $27,260.28 -$2,220.89 -8.1%
3519111962.3% $31,064.12 $6,137.54 19.8%
571649960.4% $22,574.42 $1,546.76 6.9%
791316650.4% $18,238.73 -$2,756.35 -15.1%
9121337556.4% $18,651.87 $2,420.89 13.0%
1250712940.8% $10,451.07 -$1,441.13 -13.8%
1812113162.4% $241,284.41 -$4,786.17 -2.0%
AwayLineOverlay>=17.5%#Bets#Won%Won$Bet$Profit%ROI
-50-5352160.0% $9,055.66 $1,697.94 18.8%
-5-2804252.5% $22,606.92 $745.543.3%
-20512854.9% $13,970.46 $1,600.46 11.5%
0100#DIV/0!$-$-#DIV/0!
13733547.9% $21,704.58 -$877.38-4.0%
351327657.6% $40,295.24 $3,799.76 9.4%
5721410549.1% $61,731.76 -$3,286.60 -5.3%
791969950.5% $58,811.50 -$2,352.06 -4.0%
91219510051.3% $64,458.72 -$746.31-1.2%
12501337153.4% $45,018.08 $2,269.83 5.0%
110957752.0% $337,652.91 $2,851.19 0.8%
HomeLineOverlay>=17.5%#Bets#Won%Won$Bet$Profit%ROI
-50-51215545.5% $38,137.68 -$5,483.86 -14.4%
-5-2894247.2% $26,338.09 -$2,438.52 -9.3%
-20412765.9% $13,108.17 $3,846.26 29.3%
0100#DIV/0!$-$-#DIV/0!
13642945.3% $17,547.38 -$1,087.02 -6.2%
35684363.2% $19,738.55 $5,543.05 28.1%
57422457.1% $12,244.18 $1,502.44 12.3%
79381744.7% $9,911.26 -$1,321.39 -13.3%
912362055.6% $9,077.54 $1,335.39 14.7%
125018844.4% $4,762.50 -$465.66-9.8%
51726551.3% $150,865.36 $1,430.70 0.9%

Posted in News, Sport News | 2 Comments

NBA Sports Betting Model

Posted on October 26, 2010 by admin

Sportpunter are about to release predictions for NBA with a brand new sports model.

NBA is one of the most bet sports in the world and with many games being played every day, the possibility of high turnover is great. Bookies will generally offer lines of 1.95 and better and liquidity isn’t regularly a major problem.

We have analysed the last 4 years of data using hold out samples of every year, and the following are the results. Keep in mind that this is the very early stages of the model. There are still plenty of other variables that we will be adding to it over the course of the season, but I’ve decided to release the predictions now as the season starts tonight (26/10/10).

And so now onto the analysis:

Line Betting

Overlay #Bets #Won %Won $Bet $Profit %ROI
0 0.075 463 218 47.1% $    30,579.81 -$      2,670.33 -8.7%
0.075 0.1 411 196 47.7% $    37,544.81 -$      2,397.97 -6.4%
0.1 0.125 415 204 49.2% $    49,046.83 -$      1,630.20 -3.3%
0.125 0.15 363 173 47.7% $    52,293.83 -$      3,440.39 -6.6%
0.15 0.175 324 142 43.8% $    55,308.76 -$      7,361.34 -13.3%
0.175 0.2 271 151 55.7% $    53,334.85 $      4,682.80 8.8%
0.2 0.25 482 245 50.8% $  113,096.65 -$            41.62 0.0%
0.25 0.3 325 164 50.5% $    93,989.38 -$         952.13 -1.0%
0.3 0.4 333 169 50.8% $  120,960.89 -$      1,976.26 -1.6%
0.4 1 215 113 52.6% $  107,136.50 $      2,569.09 2.4%
3602 1775 49.3% $  713,292.32 -$   13,218.34 -1.9%

So not that great results. However with a minimum 17.5% overlay a 0.9% ROI was made. But still a small profit.

Shown below is match number for line betting:

Match# #Bets #Won %Won $Bet $Profit %ROI
0 10 723 687 95.0% $     16,417.84 -$   1,118.60 -6.8%
10 20 479 254 53.0% $   101,078.79 $    2,644.10 2.6%
20 30 453 256 56.5% $     91,347.35 $    5,119.21 5.6%
30 40 436 214 49.1% $     82,024.54 -$   2,254.54 -2.7%
40 50 400 203 50.8% $     70,212.27 -$   2,386.61 -3.4%
50 60 411 219 53.3% $     71,438.12 -$       850.71 -1.2%
60 70 428 197 46.0% $     73,903.51 -$   7,315.95 -9.9%
70 80 436 238 54.6% $     69,936.70 -$   1,993.13 -2.8%
80 90 448 236 52.7% $     89,485.02 $    1,148.05 1.3%
90 5000 340 223 65.6% $     47,448.16 -$   6,210.17 -13.1%
4554 2727 59.9% $   713,292.32 -$ 13,218.34 -1.9%

So early matches is does well, whilst struggling from match 30 (of each team) and onwards. Using a 17.5% ROI min. overlay this is shown below

Match#, Overlay>=0.175 #Bets #Won %Won $Bet $Profit %ROI
0 10 35 17 48.6% $     11,991.91 -$       802.19 -6.7%
10 20 236 128 54.2% $     75,562.74 $    4,164.97 5.5%
20 30 222 121 54.5% $     67,222.83 $    3,491.21 5.2%
30 40 186 100 53.8% $     55,030.50 $    1,811.21 3.3%
40 50 147 75 51.0% $     42,253.13 -$       552.74 -1.3%
50 60 163 84 51.5% $     46,545.70 $        479.45 1.0%
60 70 166 77 46.4% $     45,366.55 -$   3,476.44 -7.7%
70 80 155 84 54.2% $     43,973.47 $    1,267.82 2.9%
80 90 198 104 52.5% $     65,387.43 $    3,750.64 5.7%
90 5000 118 52 44.1% $     35,184.01 -$   5,852.05 -16.6%
1626 842 51.8% $   488,518.27 $    4,281.89 0.9%

This shows better results, and reasonable profits throughout the season until the final matches. Presumably, these are the playoffs where it doesn’t do as well. So it makes 2.2% ROI without the final end of the season. I’m not sure however as this stage, why this is the case.

TOTALS

Overlay #Bets #Won %Won $Bet $Profit %ROI
0 0.075 507 247 48.7% $    33,237.67 -$      1,282.57 -3.9%
0.075 0.1 454 218 48.0% $    41,579.86 -$      1,827.24 -4.4%
0.1 0.125 388 195 50.3% $    45,877.17 -$         890.34 -1.9%
0.125 0.15 415 218 52.5% $    60,085.24 $      2,303.57 3.8%
0.15 0.175 332 148 44.6% $    56,212.59 -$      6,722.61 -12.0%
0.175 0.2 288 149 51.7% $    56,821.42 $      2,390.14 4.2%
0.2 0.25 438 225 51.4% $  102,933.24 $      2,437.00 2.4%
0.25 0.3 280 149 53.2% $    80,059.75 $      4,300.85 5.4%
0.3 0.4 257 137 53.3% $    92,639.37 $      5,186.56 5.6%
0.4 1 118 62 52.5% $    60,841.90 $      3,144.00 5.2%
3477 1748 50.3% $  630,288.21 $      9,039.36 1.4%

Better results with totals, with 1.4% ROI being made, and a 4.4% ROI being made with overlays 17.5%+ which equates to about 345 bets a year.

Match# #Bets #Won %Won $Bet $Profit %ROI
0 10 731 691 94.5% $     18,563.54 -$       654.80 -3.5%
10 20 464 260 56.0% $   100,121.97 $  11,777.17 11.8%
20 30 413 220 53.3% $     73,884.28 $    4,041.46 5.5%
30 40 400 193 48.3% $     69,437.21 -$       470.12 -0.7%
40 50 400 197 49.3% $     74,868.48 $        741.11 1.0%
50 60 403 199 49.4% $     67,550.22 $    2,126.65 3.1%
60 70 385 196 50.9% $     66,644.49 -$       997.44 -1.5%
70 80 417 220 52.8% $     66,179.22 -$   1,887.76 -2.9%
80 90 415 211 50.8% $     63,349.98 -$   4,580.94 -7.2%
90 5000 320 207 64.7% $     36,933.73 -$   1,664.59 -4.5%
4348 2594 59.7% $   637,533.11 $    8,430.73 1.3%

Results show great results early, with great profits being made up to around match 60, 2/3rds of the year. Results drop off in the latter half of the season, similar to line betting. With min 17.5%+ overlay as shown below, results are improved a little and a profit was even made for betting in the playoffs. I don’t think one can read too much into below because of the smaller sample size, but results for totals seems promising.

Match#, Overlay>=0.175 #Bets #Won %Won $Bet $Profit %ROI
0 10 45 23 51.1% $     14,328.68 -$       658.90 -4.6%
10 20 234 135 57.7% $     73,876.11 $  10,425.28 14.1%
20 30 168 88 52.4% $     46,446.51 $    3,509.33 7.6%
30 40 144 72 50.0% $     39,222.07 $        405.70 1.0%
40 50 167 90 53.9% $     48,856.41 $    2,866.70 5.9%
50 60 142 83 58.5% $     38,072.68 $    5,520.38 14.5%
60 70 144 68 47.2% $     39,584.95 -$   2,141.00 -5.4%
70 80 137 66 48.2% $     37,877.87 -$       842.00 -2.2%
80 90 130 63 48.5% $     35,048.44 -$   1,940.56 -5.5%
90 5000 84 42 50.0% $     23,973.62 $        647.61 2.7%
1395 730 52.3% $   397,287.34 $  17,792.54 4.5%
Posted in Model, Sport Models | 5 Comments

NBL Unders – always underrated, now almost sure things

Posted on October 18, 2010 by admin

NBL has started for the season 2010/2011 and we have seen amazing results with the Sportpunter model. We’ve hit 7 from 8 winners, for a massive start to the season including big head to head wins at 3.12 and 2.51.

But it isn’t the massive head to head wins that have a lot of people talking, but rather the totals. Every game has been low scoring. In fact, all 5 games so far have gone under the official line. In the final game of the week, Adelaide vs Perth, the final score was an incredible 24.5 points below the totals line.

On average from the five games, the scores went under by 14.5 points. Are scores just naturally low scoring or is there a reason for their low scoring?

There is a reason. During the off season the NBL decided to increase the three point line to be in the same format as the NBA. Hence we should see a smaller amount of three pointers attempted, as well as a smaller percentage of them hit. It’s very hard to determine exactly how many points should be accounted for, but one way we can look at it is to look at preseason scores compared to season scores.

In 2009/10 the preseason averaged 172 points per game, as compared to the regular season where 166 points were scored on average. This is 6 points less, and there is reasonable logic to say why preseason might be higher scoring on average than normal. Perhaps because defences are not as tight. However, this is only one season and a very small sample size to come to any real meaningful conclusions.

The 2010/11 preseason averaged 162 points per game with the new rules. This being a full 10 points less than the previous year and 4 points less than last season. So it could be argued that the new three point line rule could make a difference of up to ten points. Perhaps this explains why the unders have gone on average 14.5 points below the official line.

There’s a very realistic chance, that the bookies got caught out by this and have been offering normal lines for the totals. No doubt we will be betting a bit more on the unders, which is generally pretty good value. Be cautious of an over-adjustment for this however after the previous week.

Either way, the sportpunter model has been on fire early, picking up 7 wins from 8 bets, and there should be plenty more opportunities to come from this very weak market.

Click here to sign up to the NBL model in 2010/11

Posted in Blog, Gambling Blog | Leave a comment

Sportpunter NFL is here!

Posted on October 15, 2010 by admin

Sportpunter are releasing their NFL model this weekend, and results have been particularly pleasing. Despite a late start to the season for release of the NFL model, results have been good for the start of the year. Whilst only betting on totals so far this year, we have managed around 5% ROI.

But that of course is not all. We have tested betting on the handicap as well as totals going back four years to the season of 2006, and results are shown below with minimum 5% overlay betting on the handicap.

Results
Year#Bets#Won%Won$Bet$Profit%ROI
200621011454.3% $48,178.72 $4,457.36 9.3%
200720610651.5% $54,708.70 $4,799.53 8.8%
200820310250.2% $50,961.95 $1,513.49 3.0%
200919910351.8% $49,294.92 $2,182.05 4.4%
Total81842552.0% $203,144.28 $12,952.43 6.4%

And below with a minimum 10% overlay

Year#Bets#Won%Won$Bet$Profit%ROI
20061679255.1% $44,850.03 $4,443.41 9.9%
20071769755.1% $52,346.36 $5,684.98 10.9%
20081758850.3% $48,802.17 $1,566.29 3.2%
20091628451.9% $46,464.66 $1,965.85 4.2%
Total68036153.1% $192,463.21 $13,660.54 7.1%

Shown below are results betting on the totals with minimum 5% overlay

Year#Bets#Won%Won$Bet$Profit%ROI
200618410154.9% $40,059.53 $3,106.35 7.8%
20072069847.6% $43,976.85 -$2,522.06 -5.7%
200819010052.6% $34,943.31 $3,885.13 11.1%
20091679456.3% $28,459.79 $4,038.43 14.2%
Total74739352.6% $147,439.48 $8,507.85 5.8%

And below totals with minimum 12.5% overlay

Year#Bets#Won%Won$Bet$Profit%ROI
20061226855.7% $34,390.21 $2,937.32 8.5%
20071396647.5% $38,030.31 -$2,116.35 -5.6%
20081166556.0% $27,913.09 $4,379.08 15.7%
2009986061.2% $22,144.79 $4,063.15 18.3%
Total47525954.5% $122,478.40 $9,263.20 7.6%

Predictions will only be available one hour before the start of play for every day, which for some might mean a late night,  but this has to be done. For one, weather conditions will need to be put into the model. Probabilities do change based on weather conditions. The amount of variables that we have in this model is very large, and we are expecting great results.

The upside, is despite all the good results, predictions will be free of charge (for now). Click here to find all the information so get started with NFL at Sportpunter.

Posted in Model, Sport Models | Leave a comment

Post US Open Blues for Rafael Nadal

Posted on October 15, 2010 by admin

Nadal’s form hasn’t been the greatest since the US Open. That sentence in itself is very debatable. I mean, after all, he won the AIG Open Tennis Championships in Japan and has a 8-2 win loss record. He did however lose both matched to 10-1 outsiders Melzer and Garcia-Lopez, and fended off several match points against, against Troicki in the semi finals in Japan.

Only a brave man would bet constantly against Nadal, but when its not clay, and its post US Open, there could be a case for it.

If we bet to win $1000 on Nadal for all his matches post US Open over the years (in the months of October and November), then we would have made 56 bets, and turned over $427,500 for a loss of $23,397. That’s a loss of around 5.5% ROI.

That’s not a massive loss, but if you were betting to win $1,000 against Nadal on all matches post US open then you would have still made 56 bets, but this time turned over $30,892. But more importantly, this time you would have profiteered $6057 for a % return of 19.6. Even if you do not consider his loss to Melzer last night – which is the reason for my enquiry – a 16% ROI profit would have been made.

The sample size of 56 bets is small, but it is something to think of. Perhaps his motivation isn’t quite the same as normal, or perhaps there is value for him off the red top. Either way, there could be an edge against Nadal and perhaps other high flyer players like Federer post US Open.

Posted in News, Sport News | 1 Comment

Australian Basketball – NBL – Season set to start

Posted on October 13, 2010 by admin

The Australian basketball season for 2010/2011  is set to start, and what better way to get on board the winning bandwagon. It doesn’t really matter if you follow the NBL season that close, it’s very rare that someone does, because the betting history speaks for itself.

Take a look at the betting history. In the four years that we have been giving NBL predictions, we’ve made an incredible 11.4% ROI betting on the head to head and 8.7% ROI betting on the totals. Last year was particularly fantastic with 25% ROI betting on the head to head and almost 20% ROI betting on the totals. Incredible stuff.

With matches generally being played on each weekend, predictions will be available by 5pm on that day, so the timing of probabilities release will be quite consistant. All the main Australian books as well as many international bookies have prices for the NBL. It would have to be arguably the sport with the weakest market, which is the main reason why we can take advantage of it.

The NBL season starts this weekend, so get on board to get your profits soaring.

Click here to see all the sign up information for the NBL in 2010/2011

Posted in Model, Sport Models | Leave a comment

WTA Model analysis – Injuries

Posted on October 8, 2010 by admin

Previously I showed about how the updated WTA model goes with all sorts of different probabilities, odds and overlays; all with very good results.

Now I will look at all the NOBET scenarios and how the WTA model goes betting for or against a player with injuries and the like. For want of reminder, the NOBET’s are as follows:

NOBET1 – Player has recorded 2 retirements in last 2 months
NOBET2 – Player has not won a match (or played) in last 2 months
NOBET3 – Player has not won a match since last retirement
NOBET4 – One of the two players have played less than 10 matches on the particular surface

Shown below are the results for the above NOBET’s. A value of 1 means that model bet on a player that has the above attributes, whilst a value of -1 means that the model bet against that player. A score of zero meant that we bet on a player where neither them nor the opposition has a NOBET attribute.

NOBET1

NOBET1#Bets#Won%Won$Bet$Profit%ROI
-125624.0%$2,977.93-$183.11-6.10%
0214395644.60%$392,293.47$28,011.787.10%
117741.20%$3,693.56-$910.22-24.60%
218596944.30%$398,964.95$26,918.456.70%

NOBET2

NOBET2#Bets#Won%Won$Bet$Profit%ROI
-11478759.2% $48,041.23 $4,144.90 8.6%
0197185743.5% $341,181.29 $23,897.87 7.0%
1672537.3% $9,742.43 -$1,124.31 -11.5%
218596944.3% $398,964.95 $26,918.45 6.7%

NOBET3

NOBET3#Bets#Won%Won$Bet$Profit%ROI
-11034442.7% $18,179.95 $3,627.83 20.0%
0204991244.5% $373,744.77 $24,232.88 6.5%
1331339.4% $7,040.23 -$942.26-13.4%
218596944.3% $398,964.95 $26,918.45 6.7%

NOBET4

NOBET4#Bets#Won%Won$Bet$Profit%ROI
-11588151.2% $43,729.74 $4,516.20 10.3%
0198186043.4% $343,344.15 $22,176.97 6.5%
1462860.9% $11,891.07 $225.271.9%
218596944.3% $398,964.95 $26,918.45 6.7%

Results from above are from 2009, and unfortunetly have a small sample size, although there is something that we can discuss about it.

It seems clear that betting on players who fit the NOBET’s 1 to 3 category still have a negative profit, whist betting against them is, in general, quite successful. The model does take into consideration a player who has NOBET1 to 3, and adjusts their probability, however it seems that it doesn’t do it enough.

Hence there are two options left for me, to manually change the coefficients so that the model accounts for this more so, or have NOBET flags that appear again as before.

There are reasons why, despite the new wta model accounting for the NOBET’s that betting on them still appear unsuccessful. This is because a player might be seriously injured or just marginally injured. The model accounts for all such players as the same level of injury. Hence we might well find ourselves betting more on players who are more injured than the average, and less on players who are less injured than normal.

Also, if we were to bet on a NOBET player, it would be because that player is in some sort of form, but has recently been injured or not played for a while. Perhaps the odds account for this inform play a little too much for a player in this situation.

Either way, this is a small sample size, and it could pay to look back before 2009 to check the results. Also, betting against NOBET’s 1 to 3 seems to have been successful. In fact from 275 bets, betting against a NOBET1-3 has resulted in a 10.9% ROI. It might also be interesting to see if we were to blindly bet against NOBET’s1-3 if it is a successful betting technique or not. More on that later.

As far as new players goes, the model seems to adjust for them quite well. NOBET4 seems to be profitable betting for or against these players. A discussion about how to deal with these scenarios could well be worth it

To sign up to Sportpunter’s WTA model or view the prices, click here.

Posted in Model, Sport Models | 3 Comments

Using Pre Season data to evaluate Season average scores in NHL

Posted on October 6, 2010 by admin

NHL is fast approaching, and Sportpunter are giving predictions for the NHL season again. You can sign up by clicking here.

However, a lot of people ask about preseason. How good is it and what point is there in analysing it? Does the preseason have a lot of impact on the main season? Or is there nothing much to be gained by analysing the pre season play?

Well when looking at total goals scored, we can look back on the years to see how pre season went compared to how the season went throughout the year.

Shown below is a table of the average goals scored in a match for preseason as well as the Whole season not including the end of year playoffs.

YearPreSeaonWhole SeasonDiff
20056.315.690.62
20066.055.530.52
20075.755.220.53
20085.705.450.25
20095.745.320.42
20105.80
Average5.895.440.47

One can instantly see that during preseason the amount of goals that are scored is generally a lot more than during the season. In fact, on average, 0.47 goals are scored per game than in the regular season.

So doesn’t this give some weight to the fact that preseason data is not worth analysing in full? Well not really. As shown by the table below, we can use the preseason data of that year, or perhaps the previous years average season totals to predict the current seasons total goals.

SeasonSeason Av.Pre SeasonPreviosus Year
20065.536.055.69
20075.225.755.53
20085.455.705.22
20095.325.745.45

Whilst there isn’t much data to look at, we can observe the correlation between the average score for the regular season compared to the preseason, and compare that to the average goals scored per game for the regular season compared to the previous season.

An r squared value of 42.8% is found for the correlation between the preseason and the scores that season, whilst an r squared value of only 0.78% is found between the regular season and the previous season.

So for those not statistically inclined, what does this mean? It means that the average preseason scores for a particular year are a lot more correlated than the scores for that year than the previous years.

Strong evidence, that we should pay a lot of attention to the pre season scores in NHL every year.

To sign up to Sportpunter’s NHL model click here, or click here to view the betting history.

Posted in Blog, Gambling Blog | 3 Comments

NHL season set to start

Posted on October 6, 2010 by admin

The NHL season is set to start for season 2010/2011. The past has been very good for us, as shown by the betting history, over a span of five years we have made 7.1% ROI betting on the totals. Last year wasn’t fantastic for us however, and the model has undergone some substantial adjustments, which will hopefully sort this out. More analysis will be shown on the front sportpunter page in the near future. The season begins on the 7/10/10 in just two days, so make sure that you sign up at the Sportpunter website to be part of it this season.

Posted in Sport News | Leave a comment

Sportpunter Soccer Model: One Year On

Posted on October 5, 2010 by admin

Sportpunter’s soccer model has been going live now for just over one year, and we thought it might be good to have a look at the results.

Since the 14/9/09 which is the date that we started going live, the 12 month year resulted in 9624 bets for 3050 winners at 31.7% success rate. That’s a lot of betting, at an average of 26 bets a day. Some people might be turned off by betting so much, but it’s all about turnover. Over these almost 10,000 bets, a 2.8% ROI was made betting on head to head, which is an extraordinary figure.

Similar, but not quite as good results were found betting on the totals. 7228 bets were made for 3527 wins at a rate of 48.8%. A $9591 profit was made at a rate of 1.0% ROI. Still a nice win.

The fact that totals had a hit rate of less than 50% success and returned a profit indicates, that considering that most odds are around even money, a great minimum overlay could result in greater profits.

In February, I wrote some articles about the minimum overlays based on certain leagues. Since that time, in the same period as above, the soccer model has gone very well in this area.

Betting on head to head has resulted in 3765 bets for a %ROI of 2.2%. This is slightly lower than the overall head to head period as given above, but a lot higher than the head to head results since February for all leagues. Totals betting improves significantly when analysing by league. A 2.3% return on investment was made from just over 1000 bets. Interestingly, it lost 0.9% ROI betting on the overs during this period and won a staggering 4.9% ROI from 651 bets on the unders.

Long term sportpunter clients will all know that the smart money is almost always on the unders for almost all sports.

So a simple sportpunter soccer model, encapsulating all the big leagues, can make some serious dough. Sure 2% ROI isn’t a huge win, but most professional punters go by that sort of return, and with 5000 to 10,000 bets a year at this return, then really you should be laughing.

Related Posts with Thumbnails
Posted in Blog, Gambling Blog | 4 Comments