If your algorithm throws a wacky one out, can you let me know.
comment by NotSoMagicJuande (U1913)
posted 3 hours, 3 minutes ago
Team Bet Against: Chelsea Total Staked: 26 Profit: 25.45
Does this mean that if you were to bet £1 on the opposition on each of their 26 games, you'd have made £25.45 profit?
----------------------------------------------------------------------
Here are the matches in case you are interested
Chelsea Burnley 1718 2017-08-12 A 15.0 ---WIN 14.0
Tottenham Chelsea 1718 2017-08-20 A 2.05 ---LOSS 13.0
Chelsea Everton 1718 2017-08-27 H 8.0 ---LOSS 12.0
Leicester Chelsea 1718 2017-09-09 A 4.6 ---LOSS 11.0
Chelsea Arsenal 1718 2017-09-17 D 4.5 ---LOSS 10.0
Stoke Chelsea 1718 2017-09-23 A 5.75 ---LOSS 9.0
Chelsea Man City 1718 2017-09-30 A 2.45 ---WIN 10.45
Crystal Palace Chelsea 1718 2017-10-14 H 8.5 ---WIN 17.95
Chelsea Watford 1718 2017-10-21 H 9.5 ---LOSS 16.95
Bournemouth Chelsea 1718 2017-10-28 A 5.4 ---LOSS 15.950001
Chelsea Man United 1718 2017-11-05 H 3.13 ---LOSS 14.950001
West Brom Chelsea 1718 2017-11-18 A 6.25 ---LOSS 13.950001
Liverpool Chelsea 1718 2017-11-25 D 2.15 ---LOSS 12.950001
Chelsea Swansea 1718 2017-11-29 H 21.0 ---LOSS 11.950001
Chelsea Newcastle 1718 2017-12-02 H 15.0 ---LOSS 10.950001
West Ham Chelsea 1718 2017-12-09 H 7.5 ---WIN 17.45
Huddersfield Chelsea 1718 2017-12-12 A 8.5 ---LOSS 16.45
Chelsea Southampton 1718 2017-12-16 H 10.0 ---LOSS 15.450001
Everton Chelsea 1718 2017-12-23 D 6.25 ---LOSS 14.450001
Chelsea Brighton 1718 2017-12-26 H 20.0 ---LOSS 13.450001
Chelsea Stoke 1718 2017-12-30 H 17.0 ---LOSS 12.450001
Arsenal Chelsea 1718 2018-01-03 D 2.75 ---LOSS 11.450001
Chelsea Leicester 1718 2018-01-13 D 12.0 ---LOSS 10.450001
Brighton Chelsea 1718 2018-01-20 A 6.5 ---LOSS 9.450001
Chelsea Bournemouth 1718 2018-01-31 A 12.0 ---WIN 20.45
Watford Chelsea 1718 2018-02-05 H 6.0 ---WIN 25.45
Team Bet Against: Chelsea Total Staked: £26 Profit: £25.45
Have you tried to develop an algorithm for any other financial instrument Admin?
Are you using some kind of machine learning regressors like gradient boosting?
comment by Flashy flibble (U10324)
posted 21 seconds ago
Have you tried to develop an algorithm for any other financial instrument Admin?
----------------------------------------------------------------------
Yeah that's kinda part of my previous life. Wrote my first portfolio trading system back in 1999 which allowed portfolio managers to simulate strategy. During the financial crisis amongst other things i was fixing portfolio optimisations algorithms for a big investment bank. I don't put much faith in that nonsense these days. Its as close to a random walk as you can get.
Won a fantasy trader thing a year or two ago though as they hadn't modelled the game properly.
comment by Mr. Eboue Emmanuel (U12374)
posted 1 minute ago
Are you using some kind of machine learning regressors like gradient boosting?
----------------------------------------------------------------------
Mostly optimisers. I use amongst other things multiple PSO, GAs, Glow worm swarm algorithms which then compete
Don't know much about those will definitely look at them. Is there any python library that support those? I've been playing for some time throwing opta data at machine learning algos with variable degrees of success. For example trying to build expected goals models using stuff like distance/angle to goal, how the shot was assisted (counter attack, free kick, dribble), current game state, etc. I was thinking that if I derive expected goals for / against and then plug them in a poisson equation would be able to get something closer to true match odds. My best results sees to be using gradient boosting / xgboost getting to 3-4% of the bookmakers odds which is not bad but of course not good enough. It's a fun hobby but sadly don't have much time these days.
comment by Mr. Eboue Emmanuel (U12374)
posted 24 minutes ago
Don't know much about those will definitely look at them. Is there any python library that support those? I've been playing for some time throwing opta data at machine learning algos with variable degrees of success. For example trying to build expected goals models using stuff like distance/angle to goal, how the shot was assisted (counter attack, free kick, dribble), current game state, etc. I was thinking that if I derive expected goals for / against and then plug them in a poisson equation would be able to get something closer to true match odds. My best results sees to be using gradient boosting / xgboost getting to 3-4% of the bookmakers odds which is not bad but of course not good enough. It's a fun hobby but sadly don't have much time these days.
----------------------------------------------------------------------
Not sure about python, my initial version was written in C/C++ and the algorithms the same(http://lancet.mit.edu/galib-2.4/Overview.html etc), but each week it was taking me an hour or two of prep work to get data loaded and stuff. So i bit the bullet and started redoing it in java, and been at it since early 2016ish
Comment deleted by Site Moderator
comment by Admin1 (U1)
posted 13 hours, 7 minutes ago
comment by fridgeboy (U1053)
posted 20 minutes ago
A mate of mine is a professional at this game. Thought it was all bull at first but then I saw his betting 'room' at his place. 24 TVs all on one wall covering nearly every global sport imaginable. He's got mega rich clients that hire him to put bets on for them. If he wins, he gets a cut, if he fails he's not accountable (they're just less likely to continue using him). At 24 years of age he bought a 5 bed place in Muswell Hill (rich area of London for those not aware) completely in cash. We're talking millions - no mortgage. Incredible. Stands to reason that whatever you're doing with the stats in the main article isn't far off what he did in mastering the sports betting field. It's only a mug's game if you don't know what you're doing. Most don't, including myself. Some, however, can play the game extremely well.
----------------------------------------------------------------------
If truth be told, calling it a mugs game is probably the wise and fair assumption for most folk to make. Your mate benefits from the OPM(Other peoples money) effect as you always get a cut of a winning bet. Convincing folk to give him the cash is something he must very accomplished at. So there must be a reasonable talent behind his predictions.
Off the top of my head, I've been banned from Paddy, William Hill, Ladbrokes, Betfred for various sized wins and such. Its the dirty secret that they wont actually let you win consistently and just about tolerate the punters who win the occasional Hail Mary type bet,
Ultimately these days my focus is on the WDW markets as if I can crack that nut I can use the exchanges and not worry about getting banned.
----------------------------------------------------------------------
Having placed my first bet in 1964 and still awaiting the big one, I can tell you it is a mugs game, but I still enjoy it, so hey ho. I am not a betting shop man, if I have a bet on the horses, it is because I am going racing. Good article though Admin, and about in line with the way I do football bets. I myself have had a rest since the New Year, I have a few seasonal bets riding, so shall await the outcome of them in May. Includes Villa, Blackburn and Coventry finishing in the top three, Huddersfield and Burton for relegation, all struck prior to a ball being kicked, could give me a profit. Harry Kane top scorer, here's hoping.
Comment deleted by Site Moderator
comment by Admin1 (U1)
posted 13 hours, 8 minutes ago
comment by Mr. Eboue Emmanuel (U12374)
posted 24 minutes ago
Don't know much about those will definitely look at them. Is there any python library that support those? I've been playing for some time throwing opta data at machine learning algos with variable degrees of success. For example trying to build expected goals models using stuff like distance/angle to goal, how the shot was assisted (counter attack, free kick, dribble), current game state, etc. I was thinking that if I derive expected goals for / against and then plug them in a poisson equation would be able to get something closer to true match odds. My best results sees to be using gradient boosting / xgboost getting to 3-4% of the bookmakers odds which is not bad but of course not good enough. It's a fun hobby but sadly don't have much time these days.
----------------------------------------------------------------------
Not sure about python, my initial version was written in C/C++ and the algorithms the same(http://lancet.mit.edu/galib-2.4/Overview.html etc), but each week it was taking me an hour or two of prep work to get data loaded and stuff. So i bit the bullet and started redoing it in java, and been at it since early 2016ish
----------------------------------------------------------------------
Thanks. Never used genetic algorithms before. I'll definitely give them a try. It would be interesting if they are better than ML at this task.
bit dangeorus to go back so far on history
LFC are impossible to bet on or agaisnt currently. 2/3 years back they were prob easy to bet against once suarez was gone for example
With these things the more data you have the better. Only if your model is good of course.
comment by Mr. Eboue Emmanuel (U12374)
posted 7 minutes ago
With these things the more data you have the better. Only if your model is good of course.
----------------------------------------------------------------------
Within reason, https://betegy.com use a load of different factors, I'm sure it goes into the dozens. Football is so inherently influenced by the random it makes prediction difficult and the search for minute variables is probably of limited value Vs say using the bookmaker who offers the best odds. It's counter intuitive but it's not about picking winners, it's about picking winners that win more frequently than the bookmakers odds would suggest, but might in principle lose more often than win.
Of course - what I meant is that if you have a stable good model and you feed it with more data of the same kind it will get better and better. Lots of small random variables would rather confuse your model but more of the same meaningful stats is always better. At least in ML. Feed it with bs data and you get bs results.
comment by Admin1 (U1)
posted 16 hours, 18 minutes ago
----------------------------------------------------------------------
I was wondering this but then looked at the figures and decided it wasn't really worth it.
Take Inter for example - the best team to bet against since the creation of JA:
You make £62 profit over 251 games.
That's 24 pence profit per game...
Over a season it would be worth it (e.g. Chelsea this year) but you don't know the info at the start of the season.
----------------------------------------------------------------------
That's an absolutely incredible return. Its 25% which is astounding, If i could hit a 25% return id retire within a couple of years.
----------------------------------------------------------------------
When you put it in percentage terms, that is a very attractive return I agree.
Suppose you need to bet big to make it worthwhile, which rules me out as I'm the most casual / smalltime betting man ever, but if you're doing it seriously then yeah a consistent 25% over a few years worth of markets would be gold
comment by NotSoMagicJuande (U1913)
posted 1 minute ago
comment by Admin1 (U1)
posted 16 hours, 18 minutes ago
----------------------------------------------------------------------
I was wondering this but then looked at the figures and decided it wasn't really worth it.
Take Inter for example - the best team to bet against since the creation of JA:
You make £62 profit over 251 games.
That's 24 pence profit per game...
Over a season it would be worth it (e.g. Chelsea this year) but you don't know the info at the start of the season.
----------------------------------------------------------------------
That's an absolutely incredible return. Its 25% which is astounding, If i could hit a 25% return id retire within a couple of years.
----------------------------------------------------------------------
When you put it in percentage terms, that is a very attractive return I agree.
Suppose you need to bet big to make it worthwhile, which rules me out as I'm the most casual / smalltime betting man ever, but if you're doing it seriously then yeah a consistent 25% over a few years worth of markets would be gold
----------------------------------------------------------------------
Have in mind that those are after the fact numbers. They can change in the future. Survivorship bias at full strength here
I actually tried a betting strategy like that (in simulator of course) and it didn't make any profit. It just placed bets on the most profitable teams using data for a given period back. No value for me there.
This is a Leyton Orient WUM article
comment by Mr. Eboue Emmanuel (U12374)
posted 25 minutes ago
comment by NotSoMagicJuande (U1913)
posted 1 minute ago
comment by Admin1 (U1)
posted 16 hours, 18 minutes ago
----------------------------------------------------------------------
I was wondering this but then looked at the figures and decided it wasn't really worth it.
Take Inter for example - the best team to bet against since the creation of JA:
You make £62 profit over 251 games.
That's 24 pence profit per game...
Over a season it would be worth it (e.g. Chelsea this year) but you don't know the info at the start of the season.
----------------------------------------------------------------------
That's an absolutely incredible return. Its 25% which is astounding, If i could hit a 25% return id retire within a couple of years.
----------------------------------------------------------------------
When you put it in percentage terms, that is a very attractive return I agree.
Suppose you need to bet big to make it worthwhile, which rules me out as I'm the most casual / smalltime betting man ever, but if you're doing it seriously then yeah a consistent 25% over a few years worth of markets would be gold
----------------------------------------------------------------------
Have in mind that those are after the fact numbers. They can change in the future. Survivorship bias at full strength here
I actually tried a betting strategy like that (in simulator of course) and it didn't make any profit. It just placed bets on the most profitable teams using data for a given period back. No value for me there.
----------------------------------------------------------------------
Totally agree. Though the entire investment banking industry is built upon the same fallacy. The superstar funds and fund managers always face regression to the mean given long enough
comment by Nostraduncus (U11713)
posted 21 hours, 49 minutes ago
just watch who you bet with.
the inlaws do theirs at Willy hills and i do mine on sky bet.
ive checked their bets on sky and the difference is huge.
they were getting 800 quid at willi hills but 1200 for exactly the same on sky bet
----------------------------------------------------------------------
Do they do their bets at Hills in shop? I've always thought Hills offer very competitive odds online, but in shop (as per all bookies) they generally print terrible odds on their coupons.
comment by Mr. Eboue Emmanuel (U12374)
posted 11 hours, 22 minutes ago
comment by Admin1 (U1)
posted 13 hours, 8 minutes ago
comment by Mr. Eboue Emmanuel (U12374)
posted 24 minutes ago
Don't know much about those will definitely look at them. Is there any python library that support those? I've been playing for some time throwing opta data at machine learning algos with variable degrees of success. For example trying to build expected goals models using stuff like distance/angle to goal, how the shot was assisted (counter attack, free kick, dribble), current game state, etc. I was thinking that if I derive expected goals for / against and then plug them in a poisson equation would be able to get something closer to true match odds. My best results sees to be using gradient boosting / xgboost getting to 3-4% of the bookmakers odds which is not bad but of course not good enough. It's a fun hobby but sadly don't have much time these days.
----------------------------------------------------------------------
Not sure about python, my initial version was written in C/C++ and the algorithms the same(http://lancet.mit.edu/galib-2.4/Overview.html etc), but each week it was taking me an hour or two of prep work to get data loaded and stuff. So i bit the bullet and started redoing it in java, and been at it since early 2016ish
----------------------------------------------------------------------
Thanks. Never used genetic algorithms before. I'll definitely give them a try. It would be interesting if they are better than ML at this task.
----------------------------------------------------------------------
For Python these are worth a look https://developers.google.com/optimization/
Would definitely check it out.
Sign in if you want to comment
It's a Mug's Game Part Deux
Page 3 of 3
posted on 7/2/18
If your algorithm throws a wacky one out, can you let me know.
posted on 7/2/18
comment by NotSoMagicJuande (U1913)
posted 3 hours, 3 minutes ago
Team Bet Against: Chelsea Total Staked: 26 Profit: 25.45
Does this mean that if you were to bet £1 on the opposition on each of their 26 games, you'd have made £25.45 profit?
----------------------------------------------------------------------
Here are the matches in case you are interested
Chelsea Burnley 1718 2017-08-12 A 15.0 ---WIN 14.0
Tottenham Chelsea 1718 2017-08-20 A 2.05 ---LOSS 13.0
Chelsea Everton 1718 2017-08-27 H 8.0 ---LOSS 12.0
Leicester Chelsea 1718 2017-09-09 A 4.6 ---LOSS 11.0
Chelsea Arsenal 1718 2017-09-17 D 4.5 ---LOSS 10.0
Stoke Chelsea 1718 2017-09-23 A 5.75 ---LOSS 9.0
Chelsea Man City 1718 2017-09-30 A 2.45 ---WIN 10.45
Crystal Palace Chelsea 1718 2017-10-14 H 8.5 ---WIN 17.95
Chelsea Watford 1718 2017-10-21 H 9.5 ---LOSS 16.95
Bournemouth Chelsea 1718 2017-10-28 A 5.4 ---LOSS 15.950001
Chelsea Man United 1718 2017-11-05 H 3.13 ---LOSS 14.950001
West Brom Chelsea 1718 2017-11-18 A 6.25 ---LOSS 13.950001
Liverpool Chelsea 1718 2017-11-25 D 2.15 ---LOSS 12.950001
Chelsea Swansea 1718 2017-11-29 H 21.0 ---LOSS 11.950001
Chelsea Newcastle 1718 2017-12-02 H 15.0 ---LOSS 10.950001
West Ham Chelsea 1718 2017-12-09 H 7.5 ---WIN 17.45
Huddersfield Chelsea 1718 2017-12-12 A 8.5 ---LOSS 16.45
Chelsea Southampton 1718 2017-12-16 H 10.0 ---LOSS 15.450001
Everton Chelsea 1718 2017-12-23 D 6.25 ---LOSS 14.450001
Chelsea Brighton 1718 2017-12-26 H 20.0 ---LOSS 13.450001
Chelsea Stoke 1718 2017-12-30 H 17.0 ---LOSS 12.450001
Arsenal Chelsea 1718 2018-01-03 D 2.75 ---LOSS 11.450001
Chelsea Leicester 1718 2018-01-13 D 12.0 ---LOSS 10.450001
Brighton Chelsea 1718 2018-01-20 A 6.5 ---LOSS 9.450001
Chelsea Bournemouth 1718 2018-01-31 A 12.0 ---WIN 20.45
Watford Chelsea 1718 2018-02-05 H 6.0 ---WIN 25.45
Team Bet Against: Chelsea Total Staked: £26 Profit: £25.45
posted on 7/2/18
Have you tried to develop an algorithm for any other financial instrument Admin?
posted on 7/2/18
Are you using some kind of machine learning regressors like gradient boosting?
posted on 7/2/18
comment by Flashy flibble (U10324)
posted 21 seconds ago
Have you tried to develop an algorithm for any other financial instrument Admin?
----------------------------------------------------------------------
Yeah that's kinda part of my previous life. Wrote my first portfolio trading system back in 1999 which allowed portfolio managers to simulate strategy. During the financial crisis amongst other things i was fixing portfolio optimisations algorithms for a big investment bank. I don't put much faith in that nonsense these days. Its as close to a random walk as you can get.
Won a fantasy trader thing a year or two ago though as they hadn't modelled the game properly.
posted on 7/2/18
comment by Mr. Eboue Emmanuel (U12374)
posted 1 minute ago
Are you using some kind of machine learning regressors like gradient boosting?
----------------------------------------------------------------------
Mostly optimisers. I use amongst other things multiple PSO, GAs, Glow worm swarm algorithms which then compete
posted on 7/2/18
Don't know much about those will definitely look at them. Is there any python library that support those? I've been playing for some time throwing opta data at machine learning algos with variable degrees of success. For example trying to build expected goals models using stuff like distance/angle to goal, how the shot was assisted (counter attack, free kick, dribble), current game state, etc. I was thinking that if I derive expected goals for / against and then plug them in a poisson equation would be able to get something closer to true match odds. My best results sees to be using gradient boosting / xgboost getting to 3-4% of the bookmakers odds which is not bad but of course not good enough. It's a fun hobby but sadly don't have much time these days.
posted on 7/2/18
comment by Mr. Eboue Emmanuel (U12374)
posted 24 minutes ago
Don't know much about those will definitely look at them. Is there any python library that support those? I've been playing for some time throwing opta data at machine learning algos with variable degrees of success. For example trying to build expected goals models using stuff like distance/angle to goal, how the shot was assisted (counter attack, free kick, dribble), current game state, etc. I was thinking that if I derive expected goals for / against and then plug them in a poisson equation would be able to get something closer to true match odds. My best results sees to be using gradient boosting / xgboost getting to 3-4% of the bookmakers odds which is not bad but of course not good enough. It's a fun hobby but sadly don't have much time these days.
----------------------------------------------------------------------
Not sure about python, my initial version was written in C/C++ and the algorithms the same(http://lancet.mit.edu/galib-2.4/Overview.html etc), but each week it was taking me an hour or two of prep work to get data loaded and stuff. So i bit the bullet and started redoing it in java, and been at it since early 2016ish
posted on 7/2/18
Comment deleted by Site Moderator
posted on 8/2/18
comment by Admin1 (U1)
posted 13 hours, 7 minutes ago
comment by fridgeboy (U1053)
posted 20 minutes ago
A mate of mine is a professional at this game. Thought it was all bull at first but then I saw his betting 'room' at his place. 24 TVs all on one wall covering nearly every global sport imaginable. He's got mega rich clients that hire him to put bets on for them. If he wins, he gets a cut, if he fails he's not accountable (they're just less likely to continue using him). At 24 years of age he bought a 5 bed place in Muswell Hill (rich area of London for those not aware) completely in cash. We're talking millions - no mortgage. Incredible. Stands to reason that whatever you're doing with the stats in the main article isn't far off what he did in mastering the sports betting field. It's only a mug's game if you don't know what you're doing. Most don't, including myself. Some, however, can play the game extremely well.
----------------------------------------------------------------------
If truth be told, calling it a mugs game is probably the wise and fair assumption for most folk to make. Your mate benefits from the OPM(Other peoples money) effect as you always get a cut of a winning bet. Convincing folk to give him the cash is something he must very accomplished at. So there must be a reasonable talent behind his predictions.
Off the top of my head, I've been banned from Paddy, William Hill, Ladbrokes, Betfred for various sized wins and such. Its the dirty secret that they wont actually let you win consistently and just about tolerate the punters who win the occasional Hail Mary type bet,
Ultimately these days my focus is on the WDW markets as if I can crack that nut I can use the exchanges and not worry about getting banned.
----------------------------------------------------------------------
Having placed my first bet in 1964 and still awaiting the big one, I can tell you it is a mugs game, but I still enjoy it, so hey ho. I am not a betting shop man, if I have a bet on the horses, it is because I am going racing. Good article though Admin, and about in line with the way I do football bets. I myself have had a rest since the New Year, I have a few seasonal bets riding, so shall await the outcome of them in May. Includes Villa, Blackburn and Coventry finishing in the top three, Huddersfield and Burton for relegation, all struck prior to a ball being kicked, could give me a profit. Harry Kane top scorer, here's hoping.
posted on 8/2/18
Comment deleted by Site Moderator
posted on 8/2/18
comment by Admin1 (U1)
posted 13 hours, 8 minutes ago
comment by Mr. Eboue Emmanuel (U12374)
posted 24 minutes ago
Don't know much about those will definitely look at them. Is there any python library that support those? I've been playing for some time throwing opta data at machine learning algos with variable degrees of success. For example trying to build expected goals models using stuff like distance/angle to goal, how the shot was assisted (counter attack, free kick, dribble), current game state, etc. I was thinking that if I derive expected goals for / against and then plug them in a poisson equation would be able to get something closer to true match odds. My best results sees to be using gradient boosting / xgboost getting to 3-4% of the bookmakers odds which is not bad but of course not good enough. It's a fun hobby but sadly don't have much time these days.
----------------------------------------------------------------------
Not sure about python, my initial version was written in C/C++ and the algorithms the same(http://lancet.mit.edu/galib-2.4/Overview.html etc), but each week it was taking me an hour or two of prep work to get data loaded and stuff. So i bit the bullet and started redoing it in java, and been at it since early 2016ish
----------------------------------------------------------------------
Thanks. Never used genetic algorithms before. I'll definitely give them a try. It would be interesting if they are better than ML at this task.
posted on 8/2/18
bit dangeorus to go back so far on history
LFC are impossible to bet on or agaisnt currently. 2/3 years back they were prob easy to bet against once suarez was gone for example
posted on 8/2/18
With these things the more data you have the better. Only if your model is good of course.
posted on 8/2/18
comment by Mr. Eboue Emmanuel (U12374)
posted 7 minutes ago
With these things the more data you have the better. Only if your model is good of course.
----------------------------------------------------------------------
Within reason, https://betegy.com use a load of different factors, I'm sure it goes into the dozens. Football is so inherently influenced by the random it makes prediction difficult and the search for minute variables is probably of limited value Vs say using the bookmaker who offers the best odds. It's counter intuitive but it's not about picking winners, it's about picking winners that win more frequently than the bookmakers odds would suggest, but might in principle lose more often than win.
posted on 8/2/18
Of course - what I meant is that if you have a stable good model and you feed it with more data of the same kind it will get better and better. Lots of small random variables would rather confuse your model but more of the same meaningful stats is always better. At least in ML. Feed it with bs data and you get bs results.
posted on 8/2/18
comment by Admin1 (U1)
posted 16 hours, 18 minutes ago
----------------------------------------------------------------------
I was wondering this but then looked at the figures and decided it wasn't really worth it.
Take Inter for example - the best team to bet against since the creation of JA:
You make £62 profit over 251 games.
That's 24 pence profit per game...
Over a season it would be worth it (e.g. Chelsea this year) but you don't know the info at the start of the season.
----------------------------------------------------------------------
That's an absolutely incredible return. Its 25% which is astounding, If i could hit a 25% return id retire within a couple of years.
----------------------------------------------------------------------
When you put it in percentage terms, that is a very attractive return I agree.
Suppose you need to bet big to make it worthwhile, which rules me out as I'm the most casual / smalltime betting man ever, but if you're doing it seriously then yeah a consistent 25% over a few years worth of markets would be gold
posted on 8/2/18
comment by NotSoMagicJuande (U1913)
posted 1 minute ago
comment by Admin1 (U1)
posted 16 hours, 18 minutes ago
----------------------------------------------------------------------
I was wondering this but then looked at the figures and decided it wasn't really worth it.
Take Inter for example - the best team to bet against since the creation of JA:
You make £62 profit over 251 games.
That's 24 pence profit per game...
Over a season it would be worth it (e.g. Chelsea this year) but you don't know the info at the start of the season.
----------------------------------------------------------------------
That's an absolutely incredible return. Its 25% which is astounding, If i could hit a 25% return id retire within a couple of years.
----------------------------------------------------------------------
When you put it in percentage terms, that is a very attractive return I agree.
Suppose you need to bet big to make it worthwhile, which rules me out as I'm the most casual / smalltime betting man ever, but if you're doing it seriously then yeah a consistent 25% over a few years worth of markets would be gold
----------------------------------------------------------------------
Have in mind that those are after the fact numbers. They can change in the future. Survivorship bias at full strength here
I actually tried a betting strategy like that (in simulator of course) and it didn't make any profit. It just placed bets on the most profitable teams using data for a given period back. No value for me there.
posted on 8/2/18
This is a Leyton Orient WUM article
posted on 8/2/18
comment by Mr. Eboue Emmanuel (U12374)
posted 25 minutes ago
comment by NotSoMagicJuande (U1913)
posted 1 minute ago
comment by Admin1 (U1)
posted 16 hours, 18 minutes ago
----------------------------------------------------------------------
I was wondering this but then looked at the figures and decided it wasn't really worth it.
Take Inter for example - the best team to bet against since the creation of JA:
You make £62 profit over 251 games.
That's 24 pence profit per game...
Over a season it would be worth it (e.g. Chelsea this year) but you don't know the info at the start of the season.
----------------------------------------------------------------------
That's an absolutely incredible return. Its 25% which is astounding, If i could hit a 25% return id retire within a couple of years.
----------------------------------------------------------------------
When you put it in percentage terms, that is a very attractive return I agree.
Suppose you need to bet big to make it worthwhile, which rules me out as I'm the most casual / smalltime betting man ever, but if you're doing it seriously then yeah a consistent 25% over a few years worth of markets would be gold
----------------------------------------------------------------------
Have in mind that those are after the fact numbers. They can change in the future. Survivorship bias at full strength here
I actually tried a betting strategy like that (in simulator of course) and it didn't make any profit. It just placed bets on the most profitable teams using data for a given period back. No value for me there.
----------------------------------------------------------------------
Totally agree. Though the entire investment banking industry is built upon the same fallacy. The superstar funds and fund managers always face regression to the mean given long enough
posted on 8/2/18
comment by Nostraduncus (U11713)
posted 21 hours, 49 minutes ago
just watch who you bet with.
the inlaws do theirs at Willy hills and i do mine on sky bet.
ive checked their bets on sky and the difference is huge.
they were getting 800 quid at willi hills but 1200 for exactly the same on sky bet
----------------------------------------------------------------------
Do they do their bets at Hills in shop? I've always thought Hills offer very competitive odds online, but in shop (as per all bookies) they generally print terrible odds on their coupons.
posted on 8/2/18
comment by Mr. Eboue Emmanuel (U12374)
posted 11 hours, 22 minutes ago
comment by Admin1 (U1)
posted 13 hours, 8 minutes ago
comment by Mr. Eboue Emmanuel (U12374)
posted 24 minutes ago
Don't know much about those will definitely look at them. Is there any python library that support those? I've been playing for some time throwing opta data at machine learning algos with variable degrees of success. For example trying to build expected goals models using stuff like distance/angle to goal, how the shot was assisted (counter attack, free kick, dribble), current game state, etc. I was thinking that if I derive expected goals for / against and then plug them in a poisson equation would be able to get something closer to true match odds. My best results sees to be using gradient boosting / xgboost getting to 3-4% of the bookmakers odds which is not bad but of course not good enough. It's a fun hobby but sadly don't have much time these days.
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Not sure about python, my initial version was written in C/C++ and the algorithms the same(http://lancet.mit.edu/galib-2.4/Overview.html etc), but each week it was taking me an hour or two of prep work to get data loaded and stuff. So i bit the bullet and started redoing it in java, and been at it since early 2016ish
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Thanks. Never used genetic algorithms before. I'll definitely give them a try. It would be interesting if they are better than ML at this task.
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For Python these are worth a look https://developers.google.com/optimization/
posted on 8/2/18
Would definitely check it out.
posted on 30/12/18
Any updates?
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