[nivi]

how can you built your own predicting model in Excel etc?

is anyone who can show us how?

[Sanity Check]

You can look for "big data" courses @ places like udacity, coursera, udemy, khan academy et al.

https://www.coursera.org/specializations/big-data
https://www.coursera.org/specializat...ta-engineering

Many are free and offer decent content.

Statistical analysis, big data and similar topics are part of the analytical models books used to generate odds.

[nivi]

You can look for "big data" courses @ places like udacity, coursera, udemy, khan academy et al.

https://www.coursera.org/specializations/big-data
https://www.coursera.org/specializat...ta-engineering

Many are free and offer decent content.

Statistical analysis, big data and similar topics are part of the analytical models books used to generate odds.

thank you so much

[gojetsgomoxies]

probability, econometrics, python..... maybe start with figuring out how to calculate power ratings. i may be wrong, this may not be simple.

anyway, i think power ratings are a good place to start with analytics as they are ubiqitous, easy to understand and are logically consistent with how people think simply about quant stuff i.e. rams are 7 points better than saints, but it's in NOLA so add back 4 points for saints strong HFA = 3 point rams spread.

another good place to learn alot of stuff for free is mit open course ware. thousands of free courses with lectures/course notes readily avail.

[semibluff]

probability, econometrics, python..... maybe start with figuring out how to calculate power ratings. i may be wrong, this may not be simple.

anyway, i think power ratings are a good place to start with analytics as they are ubiqitous, easy to understand and are logically consistent with how people think simply about quant stuff i.e. rams are 7 points better than saints, but it's in NOLA so add back 4 points for saints strong HFA = 3 point rams spread.

another good place to learn alot of stuff for free is mit open course ware. thousands of free courses with lectures/course notes readily avail.

Nice idea. Horrible example.

[nivi]

mit open courses
sounds amazing

[peacebyinches]

Another thing to add to your toolkit, bayesian statistics: https://www.coursera.org/learn/bayesian-statistics
Viewing statistics through the eyes of a bayesian framework can be a game changer for a lot of people. I wish I had adapted a bayesian approach in handicapping (and my real life job..) sooner.

[nivi]

Another thing to add to your toolkit, bayesian statistics: https://www.coursera.org/learn/bayesian-statistics
Viewing statistics through the eyes of a bayesian framework can be a game changer for a lot of people. I wish I had adapted a bayesian approach in handicapping (and my real life job..) sooner.

how?
can you give us an example how it applies on sport betting?

[turtledoves]

based on my limited understanding, big data courses are for analyzing huge amounts of data, 100s of GB to TBs across a cluster of machines. you don't need to use tools like hadoop and apache spark when analyzing smaller datasets for sports analytics on a single machine.

might want to look into python, scikit-learn, pandas, numpy, scipy
tensorflow for machine learning is the hot tool

[peacebyinches]

Nate Silver (of fivethirtyeight.com) wrote an entire (very accessible) book on how it applies to sports betting, poker, finance, politics, weather, and even earthquakes called 'The signal and the noise'. It's a great place to start learning about statistics that is an easy read, not math intense, and entertaining in my opinion. If you prefer a more academic place to start there are a ton of cheap text books that show you the math behind the madness, such as this.

[Sanity Check]

based on my limited understanding, big data courses are for analyzing huge amounts of data, 100s of GB to TBs across a cluster of machines. you don't need to use tools like hadoop and apache spark when analyzing smaller datasets for sports analytics on a single machine.

might want to look into python, scikit-learn, pandas, numpy, scipy
tensorflow for machine learning is the hot tool

It was confirmed people use big data analysis to win on fantasy sports platforms like fanduel and draftkings.

Its an old thing that has been around for years.

Part of the reason states began banning fanduel and draftkings in many US states.

[nivi]

boys
give a Fuking example
a vid,a screenshot,wuteva

of how it analyzes data and gives an outcome


do not just post links and comment that they re great

[Bsims]

It was confirmed people use big data analysis to win on fantasy sports platforms like fanduel and draftkings.

Its an old thing that has been around for years.

Part of the reason states began banning fanduel and draftkings in many US states.

I believe the big data that was being used was done by insiders using all the customer picks. Hence the bans.

[Sanity Check]

boys
give a Fuking example
a vid,a screenshot,wuteva

of how it analyzes data and gives an outcome


do not just post links and comment that they re great

I'll give you an example.

Imagine your goal was to increase the accuracy of points over/under plays. A person could write an algorithm to compile and analyze game stats over the last 5 to 10 years. Based on data, they might find saturday or sunday has a higher statistical probability of over games in comparison to mondays or tuesdays.

There might be certain days of the year when a high percentage of teams hit the over play.

The point is something like a person can't predict what type of trends or patterns might emerge until after they analyze the data. Maybe there will be no patterns or trends. But sometimes a person might find something they can use to be more profitable.

I believe the big data that was being used was done by insiders using all the customer picks. Hence the bans.

Bro. You don't know what big data is. Go derail some other thread with your jibber jabber.

[nivi]

I'll give you an example.

Imagine your goal was to increase the accuracy of points over/under plays. A person could write an algorithm to compile and analyze game stats over the last 5 to 10 years. Based on data, they might find saturday or sunday has a higher statistical probability of over games in comparison to mondays or tuesdays.

There might be certain days of the year when a high percentage of teams hit the over play.

i am looking for something easier
like team A v team B
calculate he odds for an over outcome

how can i accomplish that ?

[Sanity Check]

i am looking for something easier
like team A v team B
calculate he odds for an over outcome

how can i accomplish that ?

There are many variables in sports, there isn't necessarily an easy way to be consistently accurate without putting in some work.

The basics would be looking at average points scored per game and avg points allowed per game as a basis for offense versus defense. Then looking at the last few games played to see if they're on a hot or cold streak. Then looking at how far into the season we are to get an indication of how motivated teams might be. Etc. Just really basic things most have likely tried and not found much success with.

There are a few really basic trends casual gamblers probably know. Like how NBA games in the playoffs have a tendency to be more tactical and slow paced, with higher pressure, resulting in lower point games than in regular season.

The idea behind big data is to take that type of observation to the next level. Its something I thought about but never really got around to doing as I've been looking for ways to make money outside of gambling.

[nivi]

The basics would be looking at average points scored per game and avg points allowed per game as a basis for offense versus defense. Then looking at the last few games played to see if they're on a hot or cold streak. Then looking at how far into the season we are to get an indication of how motivated teams might be. Etc. Just really basic things most have likely tried and not found much success with.

yes i know how to analyze data of two teams manually
thank you

what i m looking for is a software to calculate many teams from many leagues
using poisson distri, elo ratings etc
in no time

can we have that?

[HeeeHAWWWW]

It was confirmed people use big data analysis to win on fantasy sports platforms like fanduel and draftkings.

Big data has become a marketing term, flung around by journalists without much idea what it means. Mostly when it's used they mean machine learning - although again, that's lost its meaning as a buzzword.

Something like "predictive modelling" is probably most accurate.

[turtledoves]

[Bsims]

Bro. You don't know what big data is. Go derail some other thread with your jibber jabber.

I was simply pointing out why these fantasy companies ran afoul of the legal system a few years ago.

I agree with HeeeHAWWWW. "Big data has become a marketing term, flung around by journalists without much idea what it means."

[Sanity Check]

yes i know how to analyze data of two teams manually
thank you

what i m looking for is a software to calculate many teams from many leagues
using poisson distri, elo ratings etc
in no time

can we have that?

Hopefully someone else will comment, that's something I know nothing about.

Big data has become a marketing term, flung around by journalists without much idea what it means. Mostly when it's used they mean machine learning - although again, that's lost its meaning as a buzzword.

Something like "predictive modelling" is probably most accurate.

Machine learning has been around for decades. Its an old field that dates back to Alan Turing's day in the 1950s - 1960s. Big data is a more recent development which might include things like deep packet inspection and widespread collection of consumer and user meta data which are not necessarily related to machine learning.

AFAIK anyways.

I was simply pointing out why these fantasy companies ran afoul of the legal system a few years ago.

I agree with HeeeHAWWWW. "Big data has become a marketing term, flung around by journalists without much idea what it means."

Fantasy sports and sports gambling are banned for the same reasons state based regulation disapproves of bitcoin exchanges and escorts advertising on craiglist.

Fantasy sports, gambling, crypto and adult entertainment are all sources of revenue for small business owners in the USA which translates to economic growth and a degree of prosperity. The goal for legislators is to restrict economic growth and crackdown on independent operators in those areas.

[Believe_EMT]

can we have that?

bro, no one is going to hand you the keys to the kingdom. guys break their dikks working years to build models to find the slightest of edges. besides, we are all given this information every single fukkin day

line opens with limited information
more information becomes known
line moves
nearly 100% of knowable information is known
line closes

independent event happens

a nearly infinite number of independent events happen that prove the closing line is far more efficient than the closer

if you want to continue to reinvent the wheel, have it at. just don't come around demanding people hand you the answers. do some fukking work.

[nivi]

do some fukking work.

i do fukking your whore mother daily
now fukk off and stop spamming my threads you c*nt

[oilcountry99]

i do fukking your whore mother daily
now fukk off and stop spamming my threads you c*nt

Nivi.... EMT is correct, lazy won’t get you anywhere in this arena. Take a downer

[nivi]

Nivi.... EMT is correct, lazy won’t get you anywhere in this arena. Take a downer

wanna chat with me?
send me a pm

but do not spam on the thread

[peacebyinches]

Fine, here is a solid example, step by step, of how to analyze data and pick winners.

First, assume we have Team A and Team B. Scrape the web for a lines and the past data relating to the 3 most predictive statistics or metrics (e.g. the 3 things that produce the highest variance in determining outcomes) determined by either an independent component analysis or factor analysis (I am more familiar with ICA but it is up to you). To be more specific, you need to somehow incorporate some measure of kurtosis (fancy word for the 'tailed-ness' or skew of a distribution)in which to recover the multiple source signal by finding the correct weight vectors with the use of projection pursuit (this will be important later).The kurtosis of the probability density function of a signal, for a finite sample, is computed as

where is the sample mean of , the extracted signals. The constant 3 ensures that Gaussian signals have zero kurtosis, Super-Gaussian signals have positive kurtosis, and Sub-Gaussian signals have negative kurtosis. The denominator is the variance of , and ensures that the measured kurtosis takes account of signal variance. The goal of projection pursuit is to maximize the kurtosis, and make the extracted signal as non-normal as possible.
Using kurtosis as a measure of non-normality, we can now examine how the kurtosis of a signal extracted from a set of M mixtures varies as the weight vector is rotated around the origin. Given our assumption that each source signal is super-gaussian we would expect:

1. the kurtosis of the extracted signal to be maximal precisely when .
2. the kurtosis of the extracted signal to be maximal when is orthogonal to the projected axes or , because we know the optimal weight vector should be orthogonal to a transformed axis or .

For multiple source mixture signals, we can use kurtosis and Gram-Schmidt Orthogonalization (GSO) to recover the signals. Given M signal mixtures in an M-dimensional space, GSO project these data points onto an (M-1)-dimensional space by using the weight vector. We can guarantee the independence of the extracted signals with the use of GSO.
In order to find the correct value , we can use gradient descent method. We first of all whiten the data, and transform into a new mixture , which has unit variance, and . This process can be achieved by applying singular value decomposition to ,
Rescaling each vector , and let . The signal extracted by a weighted vector is . If the weight vector w has unit length, that is , then the kurtosis can be written as:
The updating process for is:

where is a small constant to guarantee that converge to the optimal solution. After each update, we normalized , and set , and repeat the updating process till it converges.





Great, now that you've extracted this information using your preferred software (personally I am a MATLAB guy, but you can do this in python as well since I know that is waaayy more popular and intuitive for most people) you only have two more things left to do before you can determine which team to place your bet on. Next to last step: find a coin and flip it. If it is heads, bet on Team A, if it is tails, bet on Team B. Last step: take some xanax and chill out. No one here, or anywhere, is going to walk you through how to simply 'analyze data'. That's like asking us to teach you how to 'do physics'. Be more specific.

[nivi]

Be more specific.

why all this negativity
i thought this thread would be a positive one for everyone


what i want is to learn how to do this

https://www.youtube.com/watch?v=mUO2wPNthAw

[peacebyinches]

what i want is to learn how to do this

https://www.youtube.com/watch?v=mUO2wPNthAw

Copy data into an excel file?? Control+c will copy, control+v will paste.

[nivi]

Copy data into an excel file?? Control+c will copy, control+v will paste.

this is what it delivers


pretty much he applies Poisson distibution
and the fukker selling it for 50 euros

what i want to do is a way to insert all the data of a league in excel and to get the possibilities calculated by Poisson distribution and if possible Elo ratings as well,
for the coming matches


i can do it manually for a match with two teams but if i can do it for a whole league with excel that would save me soooooooo much time

[HeeeHAWWWW]

i can do it manually for a match with two teams but if i can do it for a whole league with excel that would save me soooooooo much time

Use R, import your match results, bit of format fiddling, then use the PlayerRratings package:
https://cran.r-project.org/web/packa...ngs/index.html


Gives you ELO (and various others like glicko and Stephenson) for all rows in a few seconds.

[peacebyinches]

I second using R (might take a little effort to learn if you haven't used it before, but should be well worth it), and that looks like a very handy package HH. I can't believe I've never checked the R package repositories for anything similar! Looks like there's some NBA and MLB and NFL.

holy crap... looks like I'm not getting any actual work done for a while now

[nivi]

can anyone post a video of predicting possibilities for soccer matches with R?

[ChuckyTheGoat]

can anyone post a video of predicting possibilities for soccer matches with R?

Nivi, guys like Heehaw + Peace are doing a very good job in this thread. I can't pin-point the link, but the Poisson Dist output is a good start. Here is the basic premise:

*We need to get to the point where we project TWO NUMBERS, E (HomeGoals) and E (AwayGoals). if we assume two INDEPENDENT Poisson distibutions...then everything else falls out. Think of it like two columns:

F(0), F(1), F(2), etc. From that we get f(0), f(1), f(2) etc. Do that for both Home + Away. We can then calculate our Home Wins, Away Wins etc. This is a very good starting point.

And I echo Peace's note above. Read Nate Silver's book. He's not going to give u a license to print money...but it's a very good starting point.

[ChuckyTheGoat]

It's a link u posted in another thread:

https://annabet.com/en/poissoned/

Navigate those tabs on the top. Poisson is a really good basic approach for soccer game analysis.

The real question is whether your INPUT will be close to correct. The output from that link is certainly good, if not a little confusing to look at.

[nivi]

It's a link u posted in another thread:

https://annabet.com/en/poissoned/

Navigate those tabs on the top. Poisson is a really good basic approach for soccer game analysis.

The real question is whether your INPUT will be close to correct. The output from that link is certainly good, if not a little confusing to look at.

yeah this calculator looks dope
but i really have no idea how to use it

here is a more simple one
https://sinceawin.com/data/tools/poisson