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Found 6 results

  1. You often see the odds proportional calculation: odds = payout rate / (implied) probability --> (implied) probability = payout rate / odds. This leads to equal bookmaker margins (= (1 / payout rate) - 1) and different risk buffers (= 1 / odds - (implied) probability) for all outcomes. An example: odds 1.2 / 5.0 --> payout rate = 1.2 * 5.0 / (1.2 + 5.0) = 6 / 6.2 = 0.96774 --> (implied) probabilities 0.80645 / 0.19355 --> expected values (= probability * odds) 0.96774 / 0.96774 --> margins 0.03333 / 0.03333 & risk buffers 0.02688 / 0.00645. Impact of an 2% probability error: A) +2% / -2% --> expected values: 0.99174 / 0.86774 B) -2% / +2% --> expected values: 0.94374 / 1.06774 --> Tipsters who constantly finds this kind of error would make a nice profit 6.774%. I never liked this because i don't understand why the bookmaker would use that much higher / lower risk buffers for smaller / bigger odds. Of course he'll get much more wagers on lower odds, but since odds are being calculated with the inverse of probability, the potential damage of a faulty probability assumption corresponds with the odds. Alternatively the equal risk buffer method: odds = 1 / (probability + (whole market margin / number of outcomes)) --> probability = (1 / odds) - (whole market margin / number of outcomes). This leads to different bookmaker margins and equal risk buffers for every outcome. In the example: odds 1.2 / 5.0 --> whole market margin = (1 / 0.96774) - 1 = 0.03333 --> (implied) probabilities 0.81667 / 0.18333 --> expected values (= probability * odds) 0.98 / 0.91667 --> margins 0.02 / 0.08333 --> risk buffers 0.01667 / 0.01667. Impact of an 2% probability error: A) +2% / -2% --> expected values: 1.00400 / 0.81667 B) -2% / +2% --> expected values: 0.95600 / 1.01667 --> Even a tipster who finds such error repeatedly won't get rich. So, if i would be a bookmaker, i wouldn't use the odds proportional calculation but the equal risk buffer method. Statistics suggests that bookmakers use rather the latter. Betting on all pinnacle sports closing odds leads to smaller losses with lower odds and far greater losses with bigger odds. Even laws of market economy suggests that the larger the turnover (-> lower odds vs higher odds) the smaller the margin. Practical use: Over the years i saw a few betting colleagues mourning that although they beat the pinnacle sports closing line by 5% or more they still were in the reds and how unlucky they felt. For me the reason wasn't a lack of luck but the explanation above. Beating a @6+ pinnacle sports closing line even by 5% just equals a probability difference < 0.8% and that's just not enough even for low margins / risk buffers pinnacle sports.
  2. Hi I present to you my predictions from my software. There are 3 types predictions Over 1.5, Over 2.5, & Home Wins I hope these to be useful to anyone. Any questions I do my best to reply. good luck 28/10/2018 Predictions Qualifying Match forecast for 28/10/2018 (All matches are Over 1.5 match goals) Danish SAS-Ligaen Hobro IK v Vejle Italy Serie A Genoa v Udinese Spanish Segunda Division Extremadura UD v Albacete Greek Super League Panetolikos v Asteras Tripolis Spanish Primera Division Alavés v Villarreal Spanish Segunda Division Elche v Real Zaragoza Qualifying Match forecast for 28/10/2018 (All matches are Over 2.5 match goals) Dutch Eredivisie Willem II v FC Utrecht Belgian Jupiler League Standard Liege v Genk Swiss Raiffeisen Super League Xamax v FC Luzern Swiss Raiffeisen Super League St Gallen v FC Zurich Swiss Raiffeisen Super League FC Lugano v Thun Spanish Primera Division Barcelona v Real Madrid Dutch Eredivisie AZ v Heerenveen Swedish Allsvenskan IFK Norrkoping v Östersunds FK Norwegian Tippeligaen Odd BK v Tromso Belgian Jupiler League Eupen v Anderlecht German Bundesliga Werder Bremen v Bayer Leverkusen French Ligue 1 Marseille v Paris Saint-Germain Qualifying Match forecast for 28/10/2018 (All matches are Home Wins) Dutch Eredivisie Ajax v Feyenoord Danish SAS-Ligaen FC Copenhagen v AGF Aarhus Turkey Super Lig Fenerbahce v Ankaragucu Portuguese Liga FC Porto v Feirense Greek Super League AEK Athens v Aris Salonika Spanish Primera Division Sevilla FC v SD Huesca Portuguese Liga Sporting CP v Boavista
  3. Does anyone know how to calculate odds for half with most goal from poisson distribution? Any advice is welcome
  4. This weekend is International Fight Week for the UFC in Las Vegas , Here's my picks for the 1st of 2 cards this weekend Friday's TUF 25 Finale. TUF 25 Finale Headliner (Gaethje vs Johnson) Gaethje to Win - 7/5 (Bet365) Gaethje to Win by KO/TKO/DQ - 5/2 (Skybet) TUF 25 Finale (Taylor vs Lima) Lima to Win - 7/4 (Betfred) Other Main Card Picks Diakiese to Win - 10/27 (Will Hill) Theodorou to Win - 13/16 (Unibet) Prelim Pick's Ladd to Win - 5/6 (Betway) Hill to Win - 4/11 (Betvictor) Ishihara to Win - 4/11 (Will Hill)
  5. I'm wondering what approach people take to selecting a bet and deciding if the odds on offer are value. I have designed an excel spreadsheet where I input my opinion of the goals scored percentage per team and it generates a table that I can compare to the odds on offer from a range of bookmakers and can quickly see where the value is. This is the output table for Chelsea v Man Utd. I can quickly see that the value based on my opinion is on over 1.5 goals. The odds are not big, but in the long run the most important thing is value. For someone who wants bigger odds I can see that the next value bet is 'Both Team To Score' @ 1.91 with William Hill which might appeal to most bettors. This approach has refined my betting dramatically and increase my ROI significantly. It also highlights to people that while Both Teams To Score offers quite a bit of value in my opinion I expect this bet to lose 40% of the time so bankroll management is also important. How do you do it?