Soccer model performance in relation to league level

soccer4On request, I decided to analyse how the soccer model has gone in the past 365 days with relation to the quality of the league. I have deicded to group the soccer leagues in terms of 5 groups, from 1 being the best most popular and more professional group, to 5 being the least popular and least professional.

Some of the leagues I will admit are in the wrong place, and there will always be debate about what leagues go in which groups, but for the meantime these will be them.

Group1:

england1
england2
france1
germany1
italy1
netherlands1
portugal1
scotland1
spain1

Group2:

austria1
belgium1
croatia1
czechia1
england3
england4
france2
germany2
greece1
ireland1
italy2
netherlands2
norway1
poland1
portugal2
scotland2
slovenia1
spain2
sweden1
switzerland1
turkey1

Group3:

argentina1
australia1
austria2
belgium2
czechia2
denmark1
england5
finland1
france3
greece2
iceland1
israel1
japan1
mexico1
norway2
poland2
russia1
scotland3
slovakia1
turkey2
usa1
wales1

Group4:

chile1
finland2
hungary1
latvia1
lithuania1
romania1
scotland4
sweden2
ukraine1
uruguay1

Group5:

ecuador1
estonia1
peru1
singapore1

And based on the above, here is how we have done in h2h betting over the past 365 days:

Grade#Bets#Wins%Wins$Bet$Profit%ROI
1190457530.2% $168,526.83 $2,729.20 1.6%
23620118632.8% $357,051.03 $10,794.94 3.0%
3294695132.3% $297,795.85 $20,900.42 7.0%
4112940736.0% $123,937.23 $18,421.95 14.9%
533113540.8% $53,637.42 $11,414.58 21.3%

What is pretty clear from the above, is that as the grade becomes worse off, the %ROI becomes greater and greater. Profits are found in all groups which is pleasing, but less so in the more professional grades, which is, where you are able to bet more as well.

This makes sense to me. Lower, less followed grades probably dont have a lot of information are not studies as much as the top grades. Furthermore, the discrepancy between the best player in the team and worst player in the team is greater for the higher leagues than the lower leagues. This means that should a teams best player be missing in the lower grades, it will not make as much difference as it would the better leagues.

But still, profits in all groups is really good to see. As far as totals betting goes, the following are the results:

Grade#Bets#Wins%Wins$Bet$Profit%ROI
190846050.7% $121,616.32 $8,117.31 6.7%
22645127848.3% $340,618.51 $11,060.87 3.2%
32366116349.2% $320,316.32 $16,189.48 5.1%
4116056448.6% $157,177.02 $9,784.38 6.2%
523612151.3% $33,747.91 $1,245.17 3.7%

Better results here, with the totals results being spread relatively even amongst all the leagues. This is great news, and it tells me that the soccer totals model is basically spot on. The great records over the past few weeks has helped greatly.

For all the free soccer predictions, click here.

Posted in Model, Sport Models | 1 Comment

Same country opponents in tennis. Who to bet on?

With Jjuanmonacouan Monaco just defeating Juan Ignacio Chela in Santiago 6-3 7-5, there has been a bit of talk in the past about what effect a tennis match has when both players are from the same country.

Both Monaco and Chela are from Argentina, and no doubt hold a good comradery. So what does this mean on the tennis betting circut? Many believe that this means that the match is more likely to play pretty evenly, and if anything therefore, a bet against the favourite holds some value.

So lets do the stats hey? How would we have gone betting to win $100 on the favourite and the underdog or all tennis matches were both players are from the same county. Ther results are interesting.

As it turns out, according to my dataset, since 2005, this has occured 1074 times where I have odds for both players.

So for the favourites, we would have bet in total $416,824.07 for a handy profit of $4,920.87. That is a 1.2% ROI. For the underdog we would have bet $54,692.30 for a massive $24,440.35 loss. Thats a  44.7% ROI negative swing.

Even if we look at matches where the favourite is at odds of 1.5 or greater (thus reducing any favourite/longshot bias), we achieve a 2.9% ROI profit betting on the favourite and a 31.7% ROI loss betting on the underdog.

So there it is. I’ve debunked that myth. When two tennis players are of the same country and play each other, you are far better off betting the favourite than the underdog.

Sportpunters tennis predictions are available here

Posted in Blog, Gambling Blog | 2 Comments

New Soccer leagues predictions set to start

soccerballThere’s plenty of new soccer leagues set to start within the next month. The following are some of the leagues that will shortly get underway:

  • Chile Primera Division
  • Ecuador Primera A
  • Estonia Meistriliiga
  • Finland Veikkausliiga
  • Japan J-League
  • Norway Eliteserien
  • Norway 1. Divisjon
  • Peru Primera Division
  • Russia Premier League
  • Singapore S-League
  • Sweden Allsvenskan
  • Sweden Superettan
  • USA Major Soccer League

Also shortly to come are the following:

  • Iceland Urvalsdeild
  • Finland Ykkonen
  • Lithuania A Lyga
  • Ireland Premier League
  • Latvia Virsliga
  • Brazil Serie A

As well as the other 48 leagues that we are giving free predictions for already! And if anyone had checked the results for the soccer of late….if you had bet into the scottish premier league, you would have some quite well. Kilmarnock defeated Celtic at odds of 9.60!

In fact since live betting has gone underway, we’ve done amazingly well. Head to head (or 1×2) betting has netting 6.5% ROI from 3987 bets. All free predictions too.

Check out the free soccer predictions here.

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Sportpunter Australian Open tennis Meet Up

A few pictures showing here what a great day it was:

SP Meetup

SP Group

Sp Far

Posted in Blog, Gambling Blog | 2 Comments

Betfair Multi Deal

betfairBetfair have a new deal on their multi’s. If you make a five way multi bet before the 25th of Jan, then if you only get 4 of the multi’s correct, then betfair will refund your stake. Put simply, its a good deal.

If for example, we bet on five tennis players at 1.10 and lets assume that there is an 89% chance that each one of them will get up, this gives the bookmaker with a 2.1% edge.

However, the chances of all five coming home are 0.89^5 = 56%. The chances of four getting home is 5 * 0.89^4 * 0.11 = 34.5%. The odds one would get multing five 1.10 players together is 1.61

Hence, the expected return from a $20 bet is equal to $4.89. That means you have a 24% edge using the free return of the bet if four get through.

Only $20 can be refunded, and the bets have to be all on tennis. Click here to bet with betfair.

Posted in News, Sport News | 2 Comments

Triple J hottest 100 2009 predictions

It’s coming around to Autriplejhottest100stralia Day once again which is one of my favourite days of the year! Why? Not because I love all things Australian – which I almost do – but because I especially love alternative music.

Now I know that this is a gambling website, and I do intend on having some gambling tips in this article, but what I am really talking about is the Triple J Hottest 100.

For those who don’t live on this sunbaked island, Triple J is an alternative youth based radio station that holds the most famous countdown of the best songs of the year. You can read all about the hottest 100 here: http://www.abc.net.au/triplej/hottest100/09/ and you can even get a vote in (which helps when you are betting on the best song as well!)

In the past, I’ve done pretty good out of the hottest 100. Last year I bet strongly on Kings of Leon’s Sex on Fire which started around odds of 1.75 only to drift to 2.00. In 2007 Muse’s Knights of Cydonia only defeated favourite Silverchair’s Sraight Lines by 8 votes, and I lost a small amount on that bet.

But its been good for me in the past. In 2006, I hit on the “all others” option, believing that it was crazy the Augie March’s One Crowded Hour wasn’t listed and picked up odds of 17 to 1.

Previous years to this showed that in order to make it to the number one position, it is all about timing and commercial radio play. In 1998 when the Offspring released Pretty Fly for a White Guy (ahh-haa, ahh-haa), the song got more than twice the amount of votes as the song in second position. The song was released on November 9th, only a month before the Hottest 100 voting began and was an instant success.

Some things die hard though, and about another month later and it was the most hated song on the radio.

Timing is everything.

Which brings me to this years list. If the voting had started and finished at the start of the year, then Lilly Allen’s Not Fair (17.00) would have easily won. Such classic lyrics and catchy tune would have won the hottest 100 by a country mile. But Allen is old hat now, and several other tunes are fresher on people’s minds. You can get 41.00 on the Gossips Heavy Cross, which would have also won had the vote been mid year. Every channel was playing this song non stop. At least 10 remixes from DJ’s wanting to jump on the wagon helped them gain more and more radio airplay. So overplayed they were that the song is virtually not played on radio today.

Similarly, everyone has forgotten that Eskimo Joe’s song Foreign land is actually votable. It was released in April and since then has long been forgotten. Sportingbet haven’t even priced them up, but the song would have been top 5 if the vote count was mid year.

Phoenix was voted by Triple J voters as the best album of the year, and despite having a few big hits from the album, all sound quite similar and don’t exactly stand out. They could well get three top 20 listings, but it is hard to see them get the number 1 spot.

Muse is second favourite (4.00) with their song Uprising. It’s their best song off the album and has had significant airplay. Muse, my favourite band of all time, released this song in early September. But interestingly, in 2007, they hit the number 1 position in the hottest 100 with Knights of Cydonia that was released at prime time – mid/late November. Arguably, Knights of Cydonia is a better song than Uprising (although not as commercially played), so Muse is not a bet for me.

Favourite to hit the number one spot is Mumford & Suns Little Lion Man which has come in massively from odds of 2.80 to 1.50. I wouldn’t have listed this song in my top 3, so a bet on them is in my opinion of little value.

So who has released their song late, that is catchy and that everybody loves? Probably the song Home by Edward Sharpe and the Magnetic Zero’s. Although the album with the song was released mid year, Home has only been played in the last few weeks. So much has this caught bookies by surprise in that bookmakers failed to price up the song, which meant that odds of 126.00 would have been available. Since then it is available at odds of 17.00 or even as short as third place favourite 6.50 at spotingbet. That is some odds movement!

I’m not sure how much commercial airplay it has received, but for me, in a no real standout Hottest 100 list, it provides the best value.

Go for The Gossip as an outsider at 41.00 and hit on Home. Two big outsiders. Don’t forget the prawns on the barbie (or my Australian speciality – Dim-sims cut in half), and don’t go easy on the beverages.

As for my top 10 songs of the year 2009? Here they are:

  1. Röyksopp – The Girl and the Robot
  2. Karnivool – Set Fire to the Hive
  3. Silversun Pickups – Panic Switch
  4. Manchester Orchestra – I’ve Got Friends
  5. Doves – Kingdom of Rust
  6. Muse – Uprising
  7. Lilly Allen – Not Fair
  8. Eskimo Joe – Foreign Land
  9. La Roux – Tigerlily
  10. Edward Sharpe & Magnetic Zeros – Home

Apologies to Sarah Blasko’s All I want, Dead Letter Circus’s Space on the Wall,  every song by Karnivool and Röyksopp and how Phoenix didn’t get on the list I’ve no idea.

Odds are available at Sportingbet, Centrebet and Betchoice.

Posted in Blog, Gambling Blog | 6 Comments

Over/Under bias in NHL Ice Hockey

Many people know about the favourite/longshot bias that occurs in most sports, but little is talked about the overs/unders bias. Is there in fact a bias at all? We shall investigate.

Using data going back to the 2005/06 season, we have calculated the returns should one have simply bet $100 on either of the over or under in the total goals for the match. Which one will come up better? The results are shown below with the first table being the over bets, the second being the unders:

Season#Bets#Wins%Wins$Bet$Profit%ROI
2005/06119757048% $119,700.00 -$7,492.00 -6.3%
2006/07119656347% $119,600.00 -$7,736.00 -6.5%
2007/081250594.548% $125,000.00 -$6,628.00 -5.3%
2008/09126062450% $126,000.00 -$1,575.00 -1.3%
2009/1057527047% $57,500.00 -$3,197.00 -5.6%
Total54782621.548% $547,800.00 -$26,628.00 -4.9%
Season#Bets#Wins%Wins$Bet$Profit%ROI
2005/06119762752% $119,700.00 $2,672.00 2.2%
2006/07119663353% $119,600.00 $3,811.00 3.2%
2007/081250655.552% $125,000.00 $1,291.00 1.0%
2008/09126063650% $126,000.00 -$3,381.00 -2.7%
2009/1057530553% $57,500.00 $808.001.4%
Total54782856.552% $547,800.00 $5,201.00 0.9%

Clenhl2arly, this shows that had one bet $100 on each bet on the over, you would have lost around 4.9% ROI from nearly 5,500 bets. Alternatively, had you bet $100 on the unders, you would have made over $5,000 from nearly 5,500 bets. The bias is definetly there, that unders betting is if anything, the way to go.

Is it possible that this difference is purely due to random variation? Quite possibly, however there is a reason why the bias is there. No-one wants to see a low scoring game, everyone likes plenty of goals and will generally bet with what they want to see. Also, punters will generally remember the high scoring games, the great goals of the year and the best goalscoring players. This in turn biases them towards betting the overs. The fact that in NHL, if the scores are level at end time, we have a playoff, then this I believe, adds more fuel to the fire to say that the bias is there. Because even if the scores are level, there still will be one more goal scored.

For those statistically inclined, the difference is in fact statistically significant. A simple one sample p test shows that the probability of such a result happening due to random variation is less than 1 in a thousand.

So the bias is there, and we have good reason to suggest why it occurs.

Equally interesting, is how the bias works amongst different goal lines. Shown below is the results should one have bet $100 on the overs and unders for different goal lines. Once again, the top table is the over bets, the bottom table is the unders (that makes sense!)

Line#Bets#Wins%Wins$Bet$Profit%ROI
4.5171165% $1,700.00 $342.0020.1%
5719389.554% $71,900.00 $2,630.00 3.7%
5.52513115146% $251,300.00 -$17,590.00 -7.0%
61402670.548% $140,200.00 -$8,088.00 -5.8%
6.574336749% $74,300.00 -$2,168.00 -2.9%
78029.537% $8,000.00 -$2,018.00 -25.2%
7.54375%$400.00$264.0066.0%
54782621.548% $547,800.00 -$26,628.00 -4.9%
Line#Bets#Wins%Wins$Bet$Profit%ROI
4.517635% $1,700.00 -$416.00-24.5%
5719329.546% $71,900.00 -$5,060.00 -7.0%
5.52513136254% $251,300.00 $6,771.00 2.7%
61402731.552% $140,200.00 $3,307.00 2.4%
6.574337651% $74,300.00 -$807.00-1.1%
78050.563% $8,000.00 $1,631.00 20.4%
7.54125%$400.00-$225.00-56.3%
54782856.552% $547,800.00 $5,201.00 0.9%

Most of the bets have a goal line of 5.5 or 6, but the overs for a run line of 5 and below made a nice profit. 736 bets were made for a 4% ROI. I have little doubt, that this is because of an over adjustment by the bookies to a smaller runline due to perhaps several previous low scoring games by the teams involved. Once again, this difference is statistically significant and not due to random variation. Similarly, betting unders with run lines of 7 or above resulted in a 16.7% ROI profit from 84 bets. And once again, this is statistically significant and not due to random variation.

Such over-exaggeration from recent matches has forced the lines to move, and this is where we as punters can pick up on and make several value bets. In this short article, we haven’t even studied the teams and we are already picking up value bets that are statistically significant. I see no reason why this trend should not continue.

What will be interesting, is how the overs and unders work with soccer, basketball and many other sports. Will there constantly be value in all these sports? Let me know with you comments below.

Posted in Blog, Gambling Blog | 10 Comments

Soccer asian handicap analysis

soccer3Since going live on the 14/09/09, the soccer asian handicap model has basically broken even on 2677 bets. Considering the large profits made on the h2h betting, this is surprising, although it must be noted that asian handicapping is somewhat harder than simply betting on the team to win on the head. This is largely due to potential scoring ability of both teams.

More analysis into this area, and using the totals predictions will be used in the asian handicap side of the model in the not too distant future. Results are shown below.

Odds#Bets#Won%Won$Bet$Profit%ROI
11.81426445% $25,888.29 -$1,668.54 -6%
1.81.8520010050% $32,878.86 $1,006.10 3%
1.851.932617453% $53,348.08 $5,724.75 11%
1.91.9534015546% $56,027.04 -$2,772.88 -5%
1.95233314744% $53,565.57 -$1,488.12 -3%
22.0536916244% $57,095.55 -$506.64-1%
2.052.137715842% $55,186.12 -$875.22-2%
2.12.1526411744% $39,293.64 $677.392%
2.152.21687142% $26,647.71 -$1,022.62 -4%
2.21001586441% $26,155.84 -$133.95-1%
TOTAL2677121245% $426,086.70 -$1,059.73 0%
Overlay#Bets#Won%Won$Bet$Profit%ROI
00.07546422448% $30,109.42 -$3.260%
0.0750.140819548% $37,006.19 $495.031%
0.10.12533013641% $38,305.81 -$3,950.31 -10%
0.1250.1531914144% $45,076.27 -$2,131.13 -5%
0.150.17526312046% $44,605.59 $429.601%
0.1750.21858043% $35,052.25 -$1,057.14 -3%
0.20.2251697444% $35,638.76 -$479.79-1%
0.2250.251366850% $32,083.88 $3,483.21 11%
0.250.31867942% $50,825.69 -$978.89-2%
0.31002179544% $77,382.84 $3,132.95 4%
TOTAL2677121245% $426,086.70 -$1,059.73 0%
Line#Bets#Won%Won$Bet$Profit%ROI
-5-1411946% $5,305.07 -$625.04-12%
-1-0.5793241% $10,821.20 $303.183%
-0.5062728445% $89,262.57 $746.721%
00.2542815837% $70,149.66 $3,508.22 5%
0.250.528616457% $40,260.58 -$585.09-1%
0.50.7543421349% $61,379.40 -$1,264.08 -2%
0.75131914445% $57,661.60 $1,932.09 3%
11.252228337% $45,215.30 -$1,238.05 -3%
1.251.51156052% $19,929.37 -$2,307.00 -12%
1.551265544% $26,101.95 -$1,530.68 -6%
TOTAL2677121245% $426,086.70 -$1,059.73 0%

There is not a lot to talk about in the analysis as shown above. Lower odds are favoured, which could be because of smart money moving the odds to lower amounts. This shows that we might be on the right side of the market more often than not. Also the 2.2% ROI loss on odds of 2.15 and above accentuates this.

Overlays of 20% and 22.5% and above have resulted in profits of 2.6% and 3.5% ROI respectively which are good results.

Interestingly, betting on lines of 1.0 or greater showed strong losses: 463 bets for a 5.5% ROI loss. It would be interesting to see how this went betting on home or away teams. So conversely, betting on 0.25 lines or less resulted in a 2.2% ROI profit from over 1000 bets. Either way, the results are marginal at this stage for asian handicap betting. More data, and more analysis is clearly required.

Posted in Model, Sport Models | Leave a comment

Soccer totals analysis

soccer2Since going live on the 14/09/09 we have made 2482 bets on totals for a very small 0.2% ROI profit – basically break even. This therefore is a great reason to have a look at where the sportpunter totals model has gone good and where is has gone bad. The analysis of these bets is shown below:

#Bets#Won%Won$Bet$Profit%ROI
Over104148747% $130,107.14 $304.490%
Under144168948% $197,187.04 $279.840%
TOTAL2482117647% $327,294.18 $584.330%
Odds#Bets#Won%Won$Bet$Profit%ROI
11.81477954% $24,379.68 -$1,369.46 -6%
1.81.8518911259% $25,703.81 $3,588.02 14%
1.851.932214946% $44,835.19 -$2,324.64 -5%
1.91.9538418348% $52,219.54 $16.530%
1.95235317148% $44,853.77 $24.630%
22.0536316445% $49,265.87 -$1,987.09 -4%
2.052.128813145% $35,386.91 -$828.94-2%
2.12.152007538% $24,255.25 -$3,687.20 -15%
2.152.2854755% $10,708.99 $3,352.38 31%
2.21001516543% $15,685.17 $3,800.10 24%
TOTAL2482117647% $327,294.18 $584.330%
OverOdds#Bets#Won%Won$Bet$Profit%ROI
11.8331958% $6,503.67 -$556.57-9%
1.81.85361850% $4,914.23 -$255.14-5%
1.851.91004343% $13,181.89 -$1,409.46 -11%
1.91.951537851% $19,459.60 $1,995.70 10%
1.9521396849% $17,322.86 $564.773%
22.051728449% $22,433.94 $503.332%
2.052.11586843% $19,545.99 -$1,249.42 -6%
2.12.151304837% $14,657.53 -$2,933.88 -20%
2.152.2532751% $5,829.35 $977.2217%
2.2100673451% $6,258.08 $2,667.94 43%
TOTAL104148747% $130,107.14 $304.490%
UnderOdds#Bets#Won%Won$Bet$Profit%ROI
11.81146053% $17,876.01 -$812.89-5%
1.81.851539461% $20,789.58 $3,843.16 18%
1.851.922210648% $31,653.30 -$915.18-3%
1.91.9523110545% $32,759.94 -$1,979.17 -6%
1.95221410348% $27,530.91 -$540.14-2%
22.051918042% $26,831.93 -$2,490.42 -9%
2.052.11306348% $15,840.92 $420.483%
2.12.15702739% $9,597.72 -$753.32-8%
2.152.2322063% $4,879.64 $2,375.16 49%
2.2100843137% $9,427.09 $1,132.16 12%
TOTAL144168948% $197,187.04 $279.840%
Overlay#Bets#Won%Won$Bet$Profit%ROI
00.07558929049% $38,938.52 -$201.92-1%
0.0750.146622648% $42,670.36 $226.651%
0.10.12540618245% $48,350.67 -$2,677.48 -6%
0.1250.1529613947% $41,922.61 $193.090%
0.150.1752239241% $37,678.03 -$4,454.93 -12%
0.1750.21688752% $31,992.66 $2,469.46 8%
0.20.225904853% $19,131.13 $3,428.33 18%
0.2250.25683450% $16,300.20 $1,017.18 6%
0.250.31024746% $26,662.57 $849.103%
0.3100743142% $23,647.43 -$265.15-1%
TOTAL2482117647% $327,294.18 $584.330%
OverOverlay#Bets#Won%Won$Bet$Profit%ROI
00.07526313250% $17,091.95 $1,093.67 6%
0.0750.11989347% $17,655.06 $364.372%
0.10.1251737342% $19,694.67 -$1,155.09 -6%
0.1250.151255544% $17,048.09 -$522.82-3%
0.150.175934751% $15,217.68 $1,359.81 9%
0.1750.2673146% $12,682.85 -$355.99-3%
0.20.225372465% $7,434.07 $2,719.71 37%
0.2250.2523835% $5,279.17 -$923.40-17%
0.250.3341338% $8,861.82 -$1,046.52 -12%
0.3100281139% $9,141.78 -$1,229.25 -13%
TOTAL104148747% $130,107.14 $304.490%
UnderOverlay#Bets#Won%Won$Bet$Profit%ROI
00.07532615848% $21,846.57 -$1,295.59 -6%
0.0750.126813350% $25,015.30 -$137.72-1%
0.10.12523310947% $28,656.00 -$1,522.39 -5%
0.1250.151718449% $24,874.52 $715.913%
0.150.1751304535% $22,460.35 -$5,814.74 -26%
0.1750.21015655% $19,309.81 $2,825.45 15%
0.20.225532445% $11,697.06 $708.626%
0.2250.25452658% $11,021.03 $1,940.58 18%
0.250.3683450% $17,800.75 $1,895.62 11%
0.3100462043% $14,505.65 $964.107%
TOTAL144168948% $197,187.04 $279.840%
Line#Bets#Won%Won$Bet$Profit%ROI
1.7500$-$-
21114843% $13,200.38 $1,367.00 10%
2.2561229648% $73,731.61 $492.661%
2.5103451450% $129,769.15 -$3,742.81 -3%
2.7533715747% $49,293.82 -$551.79-1%
32489137% $41,043.70 $1,060.73 3%
3.25673958% $10,664.44 $812.168%
3.5372054% $5,225.53 $1,874.34 36%
3.752150%$233.88-$61.78-26%
400$-$-
TOTAL2448116648% $323,162.51 $1,250.51 0%
OverLine#Bets#Won%Won$Bet$Profit%ROI
1.7500$-$-
2683044% $7,681.70 $711.019%
2.2543720447% $53,523.91 $2,045.61 4%
2.537918749% $48,014.00 -$1,715.29 -4%
2.75592441% $7,309.10 -$1,545.17 -21%
3521427% $7,428.93 -$982.98-13%
3.25161275% $2,200.17 $625.0628%
3.5211152% $1,853.53 $1,660.58 90%
3.752150%$233.88-$61.78-26%
400$-$-
TOTAL103448347% $128,245.22 $737.041%
UnderLine#Bets#Won%Won$Bet$Profit%ROI
1.7500$-$-
2431842% $5,518.68 $655.9912%
2.251759253% $20,207.70 -$1,552.95 -8%
2.565532750% $81,755.15 -$2,027.52 -2%
2.7527813348% $41,984.72 $993.382%
31967739% $33,614.77 $2,043.71 6%
3.25512753% $8,464.27 $187.102%
3.516956% $3,372.00 $213.766%
3.7500$-$-
400$-$-
TOTAL141468348% $194,917.29 $513.470%

From the first table it shows that overs and unders have been equally profitable or maybe equally level. There doesn’t seem to be any major pattern with reference to better odds to bet. Perhaps a case can be made for betting with larger odds ( > 2.15), however the small sample size and the face that betting at odds of 2.10 to 2.15 negates this argument.

Having a greater minimum overlay definetly helps here. With a minimum 17.5% overlay, 500 bets were made for a profit of 6.4% ROI, and with a minimum 20% overlay 334 bets were made for a 5.9% ROI profit.

Interestingly, and maybe quite expected, most of these profits were made betting unders than overs. It has been the case in many sports, especially for example, baseball or ice hockey, that overs are bet more than unders and hence a bias occurs in the odds. It will be interesting, and we will look at it, to see if such a bias occurs here.

Overs with a minimum 17.5% and 20% overlays resulted in a -1.9% ROI and -1.6% ROI respectively, whilst Unders with the same overlays resulted in a 11.2% a and 10% ROI respectively.

Keeping in mind that the above unders bets were only 313 bets for 17.5%,  and 212 bets for 20% minimum overlays. Hence about 10% of the original number of bets.

Whilst restricting yourself to only 10% of the suggested bets might mean a leaner betting season, it could mean greater profits over the long term. The small sample size is something also to keep into account.

I wouldn’t completely change your betting strategy just yet. An analysis of the potential bias, and perhaps the bias in the greater or smaller leagues, would be well worth looking at first, which we will do.

Also interesting is the lines. Overs are profitable at 2.25 line’s and below. (505 bets at 4.5% ROI), whilst unders are profitable at the line of 2.75 and above (541 bets at 3.9% ROI).

Clearly to me this shows the market overcompensating for recent matches. I’ve seen this happen a lot in other under/over markets like baskeball and ice hockey, and it seems to be happening here. It could be just one high or low scoring match that makes the punters get on board, and the odds are moved to much in one direction for just the one match. This over compensation, gives us a good edge, and we will look at the bias in this in more detail in the future as well.

In conclusion, it would be great if overall the totals model recorded slightly better results, but perhaps restricting yourself to higher overlay under bets, as well as perhaps over bets at smaller lines, then one can obtain a greater profit.

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Posted in Model, Sport Models | 3 Comments

Soccer h2h analysis

Since going live on thsoccer1e 14/9/09, sportpunter’s soccer predictions have gone very well indeed. Head to head betting has been the main avenue of success with 7.2% ROI made on 3451 bets. Totals betting has pretty much broken even in the same time frame, whilst asian handicap betting has lost marginally.

So why not do some analysis into the areas with different combinations on certain variables. This might well help us make more educated bets, not bet on certain matches given certain circumstances and also help me play with the model to produce better results.

So first up in this 3 part series, is the analysis of head to head betting. Whilst not as in depth as totals and asian will be, some will say it doesn’t need to be given the great results. The summary is given below:

Prob#Bets#Won%Won$Bet$Profit%ROI
00.13413%$623.66-$500.41-80%
0.10.24535211% $16,805.12 -$3,356.96 -20%
0.20.383816520% $50,147.00 $1,906.43 4%
0.30.475624833% $59,659.08 $10,980.07 18%
0.40.562824239% $63,689.76 $224.780%
0.50.641518545% $59,765.49 $327.381%
0.60.719110957% $39,813.69 $7,634.84 19%
0.70.8816681% $20,297.35 $6,001.79 30%
0.80.9463576% $16,103.92 $526.603%
0.919889% $4,595.03 $88.812%
TOTAL3451111132% $331,500.10 $23,833.33 7%
Odds#Bets#Won%Won$Bet$Profit%ROI
1238023662% $72,990.08 $5,278.45 7%
22.552222944% $66,091.76 $2,143.26 3%
2.5349219039% $50,778.77 $5,299.75 10%
33.534812636% $30,687.02 $5,695.46 19%
3.543199931% $22,340.90 $3,684.09 16%
44.52555923% $19,230.48 $919.025%
4.552273616% $16,484.11 -$2,267.86 -14%
562715320% $17,456.93 -$164.70-1%
6105618014% $32,747.12 $4,706.04 14%
101007634% $2,692.93 -$1,460.18 -54%
TOTAL3451111132% $331,500.10 $23,833.33 7%
Overlay#Bets#Won%Won$Bet$Profit%ROI
00.07551118536% $27,793.94 -$710.45-3%
0.0750.142515136% $29,669.53 -$1,034.00 -3%
0.10.1559722337% $44,953.42 $4,472.91 10%
0.150.251319037% $49,199.68 $5,591.83 11%
0.20.360918030% $68,067.43 $3,726.22 5%
0.30.43248426% $42,444.75 $966.182%
0.40.51693722% $21,878.11 $1,045.73 5%
0.50.752204420% $31,451.66 $2,880.24 9%
0.751631117% $10,129.65 $1,540.50 15%
110020630% $5,911.93 $5,354.17 91%
TOTAL3451111132% $331,500.10 $23,833.33 7%

As shown above, profits were made in vitually all fields. Big outsiders with probability less than 20% yielded a loss, as too did odds of over 10, and this might be looked at closer. In particular would be interesting is how big outsiders faired when away and home. I would imagine that home based big outsiders (although this very rarely and probably never occurs), would give a positive result.

In fact betting at odds of 4.5 or more only resulted in a profit if 1.1% ROI. Still a profit, but it would seem the best results occur with odds lower than this amount and realistic opportunities for a win. Are outsiders bet more than favourites so that mug punters try to win big? The favourite/longshot bias might well be playing a significant factor here, in that the shorter the odds the more likely of a potential profit, irrespective of any of Sportpunter’s suggested bets. We’ll have a look at that in the future, but for now, it seems that betting on all ranges of odds and probabilities is successful, moreso on favourites.

Higher overlays resulted in greater profits which is great to see. A good model should clearly show this. The 91% ROI profit for 100%+ overlays is interesting, and on closer examination, there are a few daggers or maybe nuggets in a few bets. I note that following bets made with high overlays and strong probabilities:

DateLeagueTeam1Team2OddsProb$BetResult$ProfitOverlayCheck?Error?
23/10/2009wales1RhylCefn Druids782.2%792.160-792.16475.3%XX
7/11/2009wales1Port Talbot TownCaersws4.567.3%579.2812027.5202.7%XX
26/10/2009greece2Ethnikos Asteras FCPAE AO Kerkyra5.2556.1%457.640-457.64194.5%X
22/11/2009ecuador1Manta FCLiga de Quito3.576.4%670.1411675.36167.5%X?
29/11/2009russia1Rubin KazanKuban Krasnodar3.265.7%501.0931102.4110.2%X

Clearly the two wales bets have the odds around the wrong way, and hence these would not have been normal bets. The Greek bet seems legit, the Russia bet is possibly legit, whilst I cannot find odds on the Ecuador bet either confirming or denying its legitimacy.

These will come up from time to time in the program, so its important to look out for them. Either way, in 3500 bets, only 5 bets are suspect which is good. The profit for this according to the betting history would decrease the profit by $1235 only. So we still have great results for higher overlays.

Interestingly overlays less than 10% lost around 3% ROI. There might be a case for having a minimum overlay of 10% or probably better 7.5% considering the large profits made in the next section 10-20% overlays.

Either way, these are great results for head to head betting, and we will look closer at totals betting in the next post.

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Posted in Model, Sport Models | 2 Comments