goalies_are_different
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Posts posted by goalies_are_different
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Re: Calculating team's total goals in footbal Yes, it works very well for single games in NBA. Yes, the idea is to find a value bet and bet it. It works even better for hockey as there scoring is more independent and random process than in football. When I first tried it with NBA I thought that my game totals and spreads will be way off the market, but surprisingly the game totals are quite accurate and close to the market ones. There are however some games where the differences are huge, and it's probably for a reason. I don't take into account injured players in NBA (time consuming). I can back test it only with football as I have historical odds only for football. But I feel that there is still some work to be done before back testing. Back testing is the easy part, writing a program that will do it will take me two days. (I have some experience testing Joe Buchdahl's Last Six Games system which took me only a weekend)
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Re: Calculating team's total goals in footbal ChiChi, I have been playing the numbers for a while trying to figure out a way of calculating a weight or another 'inflation' factor. I will probably have to find a trained statistician to help me with this. The thing is that if after a complete season I can match the actual results with these Bessel functions, I should be able to do it for a single game. I am now doing kind of a reverse engineering. Take Pinnacle's odds for tomorrow Aston Villa Game, I found out that in order to match the game odds and the 2.5 goals under/over the team totals could only be 1.35 Villa, 0.85 Fulham. Using Bessel functions and Skellam distribution with this geometrical averages, it works surprisingly well for NBA and NHL games. Especially with NBA, the differences are very slight.
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Re: UNDER or OVER (as the actress said to the bishop) 233 bets +6% yield I am very much interested in Under/Over markets, and I sometimes double check my predictions with your picks. In my opinion U/O markets get more and more efficient at the end of the season as there is now solid stats behind every team, that's probably why your results are starting to decline. However, I hope I am wrong and your system bounce back in steady profits.
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Re: UNDER or OVER (as the actress said to the bishop) 233 bets +6% yield I am very much interested in Under/Over markets, and I sometimes double check my predictions with your picks. In my opinion U/O markets get more and more efficient at the end of the season as there is now solid stats behind every team, that's probably why your results are starting to decline. However, I hope I am wrong and your system bounce back in steady profits.
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Re: UNDER or OVER (as the actress said to the bishop) 233 bets +6% yield Don't give up! Your system is an inspiration for the masses. Talking about Bari and Inter, I had a bet on the Under 1.5...:wall:wall:wall Greedy enough not to hedge it. :wall:wall:wall
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Re: UNDER or OVER (as the actress said to the bishop) 233 bets +6% yield Don't give up! Your system is an inspiration for the masses. Talking about Bari and Inter, I had a bet on the Under 1.5...:wall:wall:wall Greedy enough not to hedge it. :wall:wall:wall
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Hi! I am trying to find a decent method of calculating the expected goals of a team in football. After testing several approaches that were backed with mathematical reasoning at certain degree I am up to a very simple and straightforward method that some of you, I believe, are familiar with. Here is an example: Home teams in Seria A scored an average of 1.4 goals a game so far this season. Away teams scored 0.95 goals. Let's have the Bari-Inter game that is played tonight (well, it's actually on, being scoreless after ten minutes as I am writing) Bari score an average of 0.63 and allow an average of 1.36 when playing at home. The figures for Inter are 1.0 and 1.2 respectably (when playing away). If we divide Bari's 0.63 goals by the average goals a team scores at home (1.4) we get 0.45. Dividing Bari's 1.36 goals allowed on average by 0.95 (goals allowed by a home team on average) we get 1.43 We do the same for Inter, with the only difference being that their average goals scored are divided by 0.95 and goals allowed - by 1.4 (that's because Inter are the away team). The figures we get are 1.05 and 0.85 respectably. The final step is: Goals for the home team expected = 0.45*0.85*1.4 (That is the home team 'attacking ratio' by the away team 'defense ratio' by average goals scored by a home team in the league. The result in this example is 0.54 Doing the same thing for Inter we have 1.05*1.43*0.95 which is 1.431 So we have 1.431 goals expected by Inter against 0.54 goals for Bari. What we can do with these two figures is to plug them in to some modified Bessel functions of the first kind and we have the following odds for our game Bari 7.17 (14%) Draw 3.71 (27%) Inter 1.69 (59%) Applying 7.5% bookies margin we have roughly Bari 6.67 Draw 3.45 Inter 1.57 What we can also do is calculate the game total goals. That's easy because scoring in football is Poisson process with goals scored by the teams being independent events. In our case we have total goals expectation of 1.97 goals. Speaking of Under/Over 2.5 goals that translates into 66% chance of Under 2.5 and 34% of Over 2.5 (1.52/2.92) Unfortunately this method of estimating team totals has its flaws. First of all, in the beginning of the season there is no team stats. Another thing is that some teams may have their figures way off the averages (Chelsea scored 3.2 and allowed 0.0 goals at home in their first five games this season). Some teams have their schedule easier, hosting weak teams in early stages of the season (Chelsea had WBA, Stoke, Blackpool, Arsenal and Wolves that allowed 16 goals in these 5 games) So, with Bari and Inter still scoreless after 45 minutes, I would gladly ask, you guys, for your expert opinion on how to tweak the numbers before feeding them to the Bessel functions. I am sticking to this functions because they prove to be extremely accurate if you give them the averages for a complete season. Here are examples with low scoring, high scoring and 'normal' scoring leagues England Premiership 09/10 (2.77 goals/game) Actual results: 51% 1 25% X 24% 2 Bessel: 52% 1 24% X 23% 2 Holland 2nd Division 09/10 (3.2 goals/game) Actual results: 46 % 1 23 % X 31 % 2 Bessel: 47% 1 23% X 30% 2 France 2nd Division 08/09 (2.31 goals/game) Actual results: 47% 1 29% 2 24% X Bessel 47% 1 27% X 26% 2
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Re: Return to Oz and the Michael Wray Experiment. Hi, Merlin! I did some quick calculations, and it seems that flat betting is the best approach in particular. I will try to post the detailed results this weekend if I have time.
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Re: Return to Oz and the Michael Wray Experiment. Great job, Merlin! A quick question came up as I was browsing the thread. Have you considered recalculating your selections under different staking plan? It all depends on the odds of the selections, but with selections shorter than 1.50, I wonder what the results would have been if every stake is leveled to a specific win ammount. For example, if the target is 10$, then on 1.50 the stake is 20 bucks, on 2.00 it is 10, on 3.00 it is 5 etc.
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Does anyone know a good read about efforts on creating ELO ratings for tennis or ice hockey?:unsure I spent some time on adapting ELO for hockey but the results are not encouraging so I am back at basics.
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Re: Elo Access Function The crucial point I don't get is how exactly you group them if we assume that by having 6235 unique RD we should have 6235 unique winning expectancies. In order to get 24 games with WE of 7% you should have 24 games with the same rating difference, am I correct? Everything else I understand perfectly, the chart etc.
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Re: Elo Access Function I understand, but looking at the win expectancy formula I see that it is actually derrived by using the rating difference. Having 6235 unique difference means the same number of wining expectancies, no? (Sorry for all these questions, but this has been bugging me for weeks already)
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Re: Elo Access Function So, that's what you used as a criteria for the regression and not the simple rating difference? If so, that makes perfect sense, I will quickly sort my table by winning expectancy. And 5/95 cut off is probably the borders of the observation - ignoring everything below 5% and 95 percent% winning expectancy due to the small number of such games?
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Re: Elo Access Function So I was right about it, they are all unique. I am trying to imagine what the regression would look like. On the X axis you would have 6235 unique values and only 0 and 1 corresponding to them. Am I right? Wouldn't that affect the fitting quoefficient?
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Re: Elo Access Function a1ehouse, how many unique rating differences do you have for 6250 Premiership games? Do you keep the figures up to 2 decimal places or round it up?
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Re: Elo Access Function Sorry for being off, guys. Yep, that's the link I was taliking about. Tonight am going to run the calculations for the Premiership, but I have bad feeling about the regression, I hop I won't be right about it.
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Re: Elo Access Function I am still going to backtest the calculations, but there is very good reason that makes me think 85 is more accurate. 85 is a result of calculation that provides a ratio between the points per game won by home team and away team. I saw it in a paper by an american guy who tries to adapt ELO system for MLS. It really makes sense. I can post the link to that paper if you like.
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Re: Elo Access Function a1ehouse, Have you tried to modify the system by changing the ammount of points that the home team gets for the home field advantage? (100 points if I am not wrong). I am working on the same ELO calculations for the Premiership and I believe that the formula can be tweaked a bit by changing the ammount of points given for HFA. I would suggest replacing 100 with 85.
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Re: Too Good To Be True??? Well, I managed to make 20 euros by laying the HT draw after 10 scoreless minutes. I was busy on the phone for 15 minutes, when I was back at the TV it was 1:0 and what I did was to hedge only the liability on the lay bet:). But on the Italy-Germany game two days ago I wasn't that lucky when laying the HT draw after 20 minutes at 2.2. Italy were dominating with the woodwork saving zee germans on two occasions but after 45 minutes it was 0:0... I rarely bet on U21 games, for some reason I just don't like the way these youngsters are playing, kinda slow and ugly most of the time... Tonight I layed the Ht draw simply because it was the only game worth betting. I am gonna wait for some baseball action 2 hours from now. There is another question arising when talking about lay-back trading. Do you guys go green on all the outcomes or rather hedge only the initial liability? I prefer doing it this way because games end at level termes less frequently than home or away win (especialy when talking about laying the draw)
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Re: Too Good To Be True??? Froment, have you considered laying the HT draw? I have been studying this system for a long time and in my opinion backing the 0-0 correct score is not something worth doing. By backing the 0-0 you are saving those 11% of games which actually finish 0-0. It's better to try and maximize the profit on those 89 % of games that see at least one goal. I never lay the draw in a game that involves a favorite shorter than 2.0. I either lay the HT draw (in this case you lay at odds 2.0-2.5 and once a goal is scored you back at odds 4.5 or higher), or I lay the draw in the beginning of the second half. I have noticed that a high scoring league like the norwegian one could be well exploited when laying the HT draw. Since the beginning of the new season in Norway I was unlucky only once in 12 games. :hope Lay the Draw could be a profitable system (but one should never expect huge ROI) only if you keep your head cool. A draw game could have downhearting impact on a punter but profitable betting is a marathon rather than 100 m race.
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Re: NHL value hunter (NEW) FEB 07 San Jose @ Columbus: Over 5.5 2.03 (Pinnacle) :sad Florida @ Washington: Washington -1.5 2.62 (Pinnacle) :clap LA Kings @ Devils : Over 5.5 2.04 (Pinnacle) :sad New Bank: 95.78 Strike Rate: 3 for 9 (33%) Profit: -4.22 Yeild: -0.24 FEB 09 Rangers @ Devils: Over 5.5 2.29 (Pinnacle)
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Re: NHL value hunter (NEW) FEB 05 LA Kings @ Capitals: Capitals -1.5 2.23 (Pinnacle) :sad Chicago @ Calgary: Calgary -1.5 3.36 (Pinnacle) :sad Anaheim @ Nashville: Over 5.5 : 2.27 (Pinnacle) :clap New Bank: 96.54 Strike Rate: 2 for 6 (33%) Profit: -3.46 Yeild: -0.28 FEB 07 San Jose @ Columbus: Over 5.5 2.03 (Pinnacle) Florida @ Washington: Washington -1.5 2.62 (Pinnacle) LA Kings @ Devils : Over 5.5 2.04 (Pinnacle)
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Re: NHL value hunter (NEW) The Penguins are more than a terrible team :@ FEB 04 Lightning @ Penguins: Penguins -1.5 2.35 (Pinnacle) :wall New Bank: 98.34 Strike Rate: 1 for (33%) Profit: -1.66 Yeild: -0.27 FEB 05 LA Kings @ Capitals: Capitals -1.5 2.23 (Pinnacle) Chicago @ Calgary: Calgary -1.5 3.36 (Pinnacle) Anaheim @ Nashville: Over 5.5 : 2.27 (Pinnacle) :hope
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Re: NHL value hunter (NEW) Not an outstanding start, but a small profit is still a profit. FEB 03 Thrashers @ Rangers: Rangers-1.5 2.46 (Pinnacle) :( Hurricanes @ Canucks: Over 5.5 2.17 (Pinnacle) :D New Bank: 100.34 Strike Rate: 1 for 2 (50%) Profit: 0.34 Yeild: 0.085 FEB 04 Lightning @ Penguins: Penguins -1.5 2.35 (Pinnacle) :hope
Calculating team's total goals in footbal
in Betting Systems & Strategy
Posted
Re: Calculating team's total goals in footbal That's true Kumquat, but it is still interesting to find out how to estimate team totals in football. Using only poisson distribution for soccer doesn't work well because 'pure' poisson underestimate the chance of no goals. That's why Skellam distribution is used instead. It only works when goals scored and allowed are independent, in football they are linear independent so modeling using Skellam distribution is OK. I know for sure that live betting models in Bet365 are based on Skellam distribution.