Poker bankroll management spreadsheet


poker bankroll management spreadsheet

This Tiny Bathroom Was in Desperate Need of Some TLC - Until Now! Access Google Sheets with a free Google account (for personal use) or Google Workspace account (for business use). There are still video poker games that with proper strategy pay over %. I’ve also seen a blackjack game at the Fiesta Rancho and Slots-a-Fun in Las Vegas that had a basic strategy advantage. As I argue in my sports betting section betting NFL underdogs at home against the point spread also has resulted in a historical advantage. So x odds in craps is still one of .

As a new streamer, we suggest that poker bankroll management spreadsheet stream read article kbps, which is the bare minimum. Like expected strike outs in major league baseball. Some players will stay at the table until the game is shuffled, or they may "Wong out" or leave when the count reaches a level at which they no longer have an poker bankroll management spreadsheet. Today's episode is all about predictive modelling and how it can be applied to sports betting. Range to Add Up - This is what actually gets added. Are there any websites or blogs or any material out there that you've thought that was really useful in your journey? It is a nice change of perspective compared to my full length mirror. BetOnline also offers bank wires.

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That will show up like this:. If the player had to achieve a point twice, before rolling a seven, to win the pass line bet in craps, how much would that increase the house edge?

poker bankroll management spreadsheet

You wake up on the weekends and your knees hurt and your elbows hurt and your poker bankroll management spreadsheet are swollen. I would say there is one, and forgive me for starting off poker bankroll management spreadsheet at the more complicated end, but there is an eBook currently managenent by a guy named Jason Brownley from Australia and it's called Machine Learning Mastery. If you're seeking to growth you're making bet…. Views Read Edit View history. And I think that there's a lot of truth bankrolk that. Do you think from a personal perspective or experience, do you think this approach is catching up with bookmakers and they're struggling to handle the way people are betting nowadays? As my blackjack section shows, the 2 to 1 on poker bankroll management spreadsheet is worth 2.

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About Android Generator Apk Bitcoin. So, you obviously keep yourself very busy with everything that's going on at the moment. However you have to compare that to the poker bankroll management spreadsheet of rolling a losing combination. So, it's going to have a blank inputs. Poker bankroll management spreadsheet on the column header and where it says B1 write casino no bonus code the name of that list; I chose Limits for the Limits List. Poker bankroll management spreadsheet you can definitely get there provided that your models have the required level of sophistication.

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Video Guide

Bankroll Management In Poker (BRM) - Poker Quick Plays Andrew Mack: Hi, man. And so I have two examples, two different read article that I think will be helpful.

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Are you, obviously it's modelled, but are you betting on specific markets or specific sports at the moment? As of right now, I'm betting predominantly on the NHL as it just opened up recently. So, NHL Money Line totals, occasionally the puck line, some NHL props including shots, saves goals, points. And I think a little bit of CFL and I think that's most of it right now as of this period in the year. With regards to other seasons in the year, other things that I've done or looked at. MLB was a tough season for me, mostly because I've had some trouble forecasting the bullpen and so, while I continue to try and work out the kinks on the full game models, most of my betting for the MLB that's been successful l has been prop bet. So, strikes hits, runs errors as a prop home runs, runs in the first inning and a little bit of a first five innings because usually the article source pitchers that are still playing at that point, and so I've had a little bit more success with that.

But really over the course of the year, anything that I think I might have an edge on, I will take a look at, I do some NFL props as well, pass attempts, passing yards, receiving yards, rushing yards, touchdowns, a little bit of small league Euro basketball as has been mentioned in the book. And I think our previous Pinnacle Podcast, some AFL, if I have time and I'm also interested in the English Premier League exact score markets. I occasionally find a little bit of value there as well and I think that's most of what I'm up to these days. So the leagues themselves what many people know to be very efficient leagues are obviously major betting leagues for a lot of bookmakers.

And it seems that you then digging around into the markets within those that perhaps might be a little less efficient, but have you scaled up with your modelling and maybe I don't know, gone from KHL or Euro league basketball and moved up through those levels to where you're now [at] a point, you need those high limits poker bankroll management spreadsheet get your action down or is it just you're dedicating time to those markets and that's why you're betting on them? A little bit of both. I would think that, well, I suppose I should say that as your models get more sophisticated and more nuanced, you can progressively work your way up in more and click here efficient markets. It's certainly not the place that you should start, which is a point that I continue to repeat over and over again on Twitter and in the book.

But you can definitely get there provided that your models have the required level of sophistication. And you made a really good point with regards to these sharp markets, not every sub-market or derivative market inside. What we would consider largely to be a shift market is at the same level of efficiency. And so, as a result of that, there are frequently opportunities that present themselves. Props are a really great example of that. And with regards to the other things, like, definitely started out with smaller basketball leagues like the Icelandic women's basketball league and some other, European basketball leagues. And then worked my way up with the hockey model. I never actually focused much on the KHL. I really just started with the NHL and eventually progressed it to the point where it's showing good value in producing good results even though the market is quite sharp.

So, slightly different approaches for each market. Although I would say that basketball and baseball are very sharp and require quite a serious commitment to your model's sophistication. Well, I've heard a lot of talk about modelling. Let's get into it and discuss your book as well and a little poker bankroll management spreadsheet more detailed. So, you published Statistical Sports Models in Excel earlier this year and for anyone that hasn't read the book, could you just maybe give us a brief intro into it and tell us what it's about and why people should read it? Statistical Sports Models in Excel is essentially a book that I wish existed when I first got into modelling. It's basically designed to be a crash course in foundational statistical modelling techniques for the explicit purpose of sports betting with the heavy technical language and statistical formulas removed to make it easier for beginners to understand.

And I think it will give the readers some new model ideas, techniques to make their own forecasts for games and ways to help determine if a model that they've made is working poker bankroll management spreadsheet or not. Yeah, I can certainly testify the book sets out to do exactly what it says on the tin.

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I'm far from an expert on Excel and it certainly taught me a lot in a fairly short space of time. And with Excel being in the title - is that when we talk about your models and what you're ooker with modelling in general. Is that what you're using lucky pictures are you now looking at different programming languages? Well as I mentioned in the book, one of the reasons that I felt safe, I guess epreadsheet will, to write the book is because I have moved on to R poker bankroll management spreadsheet to a lesser extent Python and my SQL databases and things like that. So, I'm using a more sophisticated process now. And obviously spreadaheet your model becomes more sophisticated or requires more sophistication tools like that are only going to help you. So, some of the things that I was doing in Excel previously I'm not really using anymore. And so, felt free to be able to share those with other people and have them help other people learn and get up to speed more quickly, but at the same time not really have to reveal too, too much though what my current betting models are looking like or doing and so that was the impetus for the book.

I think if you, you mentioned Excel or Python and stuff like that, you quickly get these battle lines that are drawn in the sand poker bankroll management spreadsheet people are quick to defend whatever they use the most. And I guess there's someone that's used those three that we learn more here talked about. Could you maybe touch upon the strengths and weaknesses for each, for anyone that maybe doesn't know or only has knowledge of one thing? Yeah, I would say in some ways certainly with R and Python, it's very much a Coke versus Pepsi argument.

poker bankroll management spreadsheet

Everyone poker bankroll management spreadsheet maybe a personal favourite, but whether or not that's totally justified, other than purely familiarity as not totally certain. I would say that what's great about Excel is that it's hyper visual. Its point and click interface makes it very easy for someone poker bankroll management spreadsheet is just getting started to understand what's going on behind the scenes. And the most important thing that you could do is pop the hood and understand what's going on with the engine you want to be able to click on a cell and be able to see the formulas that that cell is using because it helps you understand the processes and the functions, and all of that is going to poer your understanding of what's happening. And I think that that is one of the understated strengths of Excel is that it's so visual that it's easy to spot. It's easy to troubleshoot mistakes that you've made.

It's easy to see what's going on and all of that can provide you with a greater understanding. I would say, that its weakness is probably data wrangling because as many people know, when you get any poker bankroll management spreadsheet, any type of sports betting data, you are going to have to do a tremendous amount of data wrangling to turn that into usable information. So, it's going to have a blank inputs. So, certain players didn't play that game or they didn't record a certain statistic that game, they didn't get any rebounds or they didn't get any assists or whatever the data is there's going to be empty cells, empty values, there's going to be outliers. So maybe inputs that aren't totally helpful to what it is that you're trying to do. So, generally with data pomer, you want to deal with your empty values or no values. You want to poker bankroll management spreadsheet with your outliers. You ultimately would like it to be formatted in a way where statistical analysis is easy to do.

And poker bankroll management spreadsheet how you structure the columns and the rows is very important. All of that in Excel, it can be quite challenging and so when you get into the really heavy work with thousands and thousands of data points, that part can be a little bit cumbersome in Excel certainly. Those two things become fairly tedious in Excel and managemfnt usually when most people start to think about maybe other options for doing it. So that's Excel, I would say, I've heard mixed things about R in terms of some people really think that it's quite user friendly, some people think that it is almost uninterpretable. And a managfment of that seems to have to do with how much of a computer science background do bankrol, have.

The computer science background people that I've talked to seem to love Python and have a certain amount of disdain for R just because of the way that the inputs are set up. I personally found R to be very user friendly. Although I don't have computer science background, so that might be an element to it. I found that source coding was fairly approachable and made a certain amount of sense. I would say that its strength is that it was built primarily for academics. And academics usually pioneer the leading-edge packages.

poker bankroll management spreadsheet

So, whatever … if there's a poker bankroll management spreadsheet machine learning algorithm that's just come out, it's very likely to show up on R first, so, you have a lot of really totally free cutting-edge tools that you can use with R. Poker bankroll management spreadsheet I think that that makes it very, very useful for sports betting. Scraping, web scraping if you want to scrape odds and things like that. I don't know if it's quite as good as Python. I think that Python is a little bit easier to use for scraping web data and that to me is the real split. I think that R is really good for the machine learning and the statistical analysis. It's a little bit more cumbersome for the scraping. Python is also very good for the machine learning and statistical analysis as well and a little bit better for web scraping.

So really, either or whatever works for people. I think anyone, no matter what their preference, they can't have any complaints with that. I guess one of the questions I often have with these languages is that people tend to say that they're similar to a spoken language in the sense that once you learn one, it then becomes a lot easier to learn another. Is that something that you'd agree with? I don't know if I would totally agree with that. But I found R was a lot easier to learn than Python and that's just me. Other people would obviously have different experiences. I found that Python was a little more, it seemed a little more technical to me, I guess would be the word I would use to describe it. Certainly not that you can't learn it and certainly not that there isn't some level of crossover because there is, games free2play koop R and Python do have different ways of doing things, assigning variable names and other things like that and you get used to one and poker bankroll management spreadsheet you try to switch to another, sometimes, you make a few mistakes here and there and you go back and you fix it and carry on.

So, I don't know if … I guess in one sentence, in terms of getting your mind used to thinking in code, it is helpful. You learn one and then it becomes easier to learn another one. But obviously the details will be different for each of those respective programming languages. So, if someone … let's imagine someone's hovering over the button on their book, obviously they need to be aware that as good as your book is, it's not a case of buying it, reading it and you're set to go, you're going to start making money from sports betting and through the modelling side of things. What are the Skills and traits. I would say first I would say positivity, which may surprise some people, but I think that, if you don't approach it with the right attitude, you're going to give up before you ever even get a poker bankroll management spreadsheet of poker bankroll management spreadsheet. So, I think that's actually a very undervalued attribute.

A curiosity I would say, because really when you're trying to develop things for yourself, you have to ask instead of having a negative attitude, you predetermining why certain things won't work or are unlikely to work. It's much better and more helpful to be curious and to ask yourself, well, what if this worked or what if we could do things like poker bankroll management spreadsheet and you try it. So, a curiosity and a willingness to explore and experiment even at the risk of a foolish or silly experiment, I think is a read article, really positive trait.

Also, the ability to think critically and analytically and to consider contrary or contemporaneous evidence to the contrary of why something might or might not be causally related or wildblaster bonus code. Those are all good things to have as well and really just a desire to keep learning and keep improving because the moment that you think that you've finished learning is a dangerous moment for a modeller, because it's very much an arms race when you're building a model that is trying to outpace the market. They haven't quite clicked them into place in the past.

poker bankroll management spreadsheet

The thing is people want poker bankroll management spreadsheet to almost find that motivation. But if someone poker bankroll management spreadsheet at that point yet, how do you, what would you say to someone that says, look, I'm really struggling. I know what I need to do, but I just can't get that final little push to do it. Is there anything you'd say to them that would help them get there? There's a quote from the founder of IBM that my dad used to say when we were little kids. That was, if you want to double spielbank chemnitz rate poker bankroll management spreadsheet success, you need to double your rate of failure. Which was, I always it was an interesting quote.

There's something about that where you really have to get your hands dirty and you have to start making some mistakes because when you make mistakes and you learn from them, you will improve. Whatever it is that you're doing. You continue to keep reading, you continue to keep trying to find new ideas, but above all, keep trying things and keep making mistakes because every mistake that you make, you're going to learn from that. You're going to realize, okay, that didn't work and you're going to build for yourself almost like a database in your mind of experimental ideas that worked or didn't work or looked promising.

And when you start amassing those, you start having better ideas. And so, a lot of people seem to think that, maybe they can just think about one thing coated, put it all together and boom, it's going to work and instant glory and riches and that's just really not the way that it works. You really have to, you have to learn from your mistakes and you have to make a lot of mistakes in order to get to where you want to be. I think there's another expression that an expert is someone that's made every mistake that can be made in a very narrow field. And I think that there's a lot of truth to that. Props to your dad, Andrew. I think he grew up in the right household.

So, outside of inspirational IBM quotes. And if we're looking at tools or resources that people might use to not shift that mindset but to help them develop the actual skills to build models and help them to find success in betting. Are there any websites or blogs or any material out there that you've thought that was really useful in your journey? I would say there is one, and forgive and schalke esport spieler tot other for starting off maybe at the more complicated end, but there is an eBook currently out by a guy named Jason Brownley from Australia and it's called Machine Learning Mastery. And it's an eBook series on both R and Python. And the premise of his eBook is essentially that developers don't poker bankroll management spreadsheet understand the statistical nuances of machine learning.

So he put together these eBooks where he gives you a crash course in machine learning. And then walks you through templates of code to run all of the various machine-learning models. So they're there, it's almost like a basic template for every machine learning model that you might want to start with, whether it's regression or classification. And he goes through a number of different things and basically the example code that he gives you … he uses some very simple example data sets, but the example code is worth a hundred times the price of the eBook because you have an example to visually see how to work this in. And you can take out the example data, plug in sports data and just try it and you will immediately begin slowly understanding how you might be able to apply machine learning to a sports data set. And I think that's probably one of the best machine learning resources that's available. Very helpful and definitely helped me to get up to speed in both R and Python for the actual machine learning element of it.

So, I would recommend that if people are interested in that they should definitely check it out. With regards to some of the more basic stuff it … Google is your friend. I think that that's been said before.

poker bankroll management spreadsheet

I think Rob Pizzola said that in his chat with you. But it's so poker bankroll management spreadsheet. Google is your friend, if you have a little notepad and you write down statistical terms and things that seem interesting. And then just start Googling them and trying to look for research papers or videos or anything that you can find that might help explain that. That's a very useful, you might want to know. What is a Bradley Terry model? What is a Glicko boku casino sites uk system? How is it different from an ELO rating system? What is the TrueSkill rating? What is multi culinary? What does a Poker bankroll management spreadsheet value mean? How is it different link a T stat value?

There are so many questions that you can ask and really how helpful Google is to you is very dependent on how good the questions that you ask are. So that was definitely a huge point for me and I think that's something that a lot of people should focus on as well if they're trying to improve. What else did I do? I pretty much bought every statistical modelling and sports betting book that I can get my hands on. Absolutely outrageous number of books here at the moment. Let's see, basically I've got everything from algebra and calculus textbooks to probability textbooks, Bayesian textbooks, data science books for R and Python, machine learning model books. And almost every sports betting book that has ever been written.

So, try to read as poker bankroll management spreadsheet as I can about how other people have approached these problems. Not because I want to copy what they're doing, but because you never know when one little sentence or one little paragraph or one little example is going to give you a light bulb going off in your head that pays for the price of the book a hundred times over. And that's happens in almost every book. There's something in there that you think, Oh, that's interesting. Maybe I should try and work with that or give it a try. Where else can you look bankrokl good tools and resources? I really liked reading statistical research papers to see what academics have done with regards to sport. There are literally thousands of masters theses and PhD managememt where people have tried to solve the same problems and well, they've manaement away most of what they're doing in terms of methodology.

There are some really good ideas there and you ;oker get some really excellent concepts about maybe some superior ways to think about the problem. And if you have some tools to help you think about the problem, you're going to come up with better solutions.

poker bankroll management spreadsheet

So, reading research papers, even if you don't understand the entire paper, I think is a very, very useful thing to do. What else have I done? I've contacted and had meetings with the professors in the statistics department at university just to ask them some questions about various techniques, about Basien statistics and things like that. That was tricky, because academics are very risk adverse generally and they're not usually very keen on betting. So, you have managementt ask these questions without telling them that poker bankroll management spreadsheet what you're interested in which can be a little bit of a tricky situation. But I did bxnkroll some things from a few of the professors at the university here from just talking to spreadsheeh.

That was handy too. And what else back to a previous point, but just experimentation, you never know what you're going to find just by trying different things. And one example I can give of that is there are a number of random Excel plugins for example, that some of them turn out to be pretty handy. So, I found a plugin for Excel called the Chess Ranking Assistant. And the Chess Ranking Assistant allows you to input the names of chess players in your high school chess team, group, whatever. And input the match results and poker bankroll management spreadsheet a couple of buttons and it will automatically calculate the ELO ratings for all the players. It will automatically calculate the Glicko ratings for all the players and you can use that to predict it.

It will give you a basic forecast for who would be likely to win a game between player four and player two. Not like you're going to be able to create, a full read article out betting model with that. But that could be very handy for learning how, a rating system like ELO or Glicko work.

poker bankroll management spreadsheet

So there's a lot of little plugins that you can play with to find new ideas and things like that. So just to try to put myself in the shoes of this beginner, this aspiring model builder that you very kindly lent them your library of books. Poker bankroll management spreadsheet doing all their can, reading poker bankroll management spreadsheet these materials. But for some people it's nice to have an example, and Poker bankroll management spreadsheet don't want to kind of give too much away from your book or anything like that, but obviously the process of creating, testing, refining and measuring that goes into a model. Can you just kind of speak a little bit to what's actually involved and perhaps maybe use one of your previous examples?

I actually prepared a new example for today because I know that a lot of listeners are interested in the finer technical details and sometimes they can get frustrated when we talk from a 30, foot view about these things. And so I have two examples, two different approaches that I think will be helpful. One of them is for props and one of them … actually, they're both for props. One of them is a little more traditional handicapping and the other one is more statistically oriented. So I'll just start with the quick one first, which is I don't know if you want to consider this another resource or if this read article more of a process. But for something like props, the best possible advice that I could give someone that's just starting, that has no idea what to do. Would be to pick one team from a league or one player from a team and watch that player or that team for an entire season and take notes.

But not take notes about the things that fans are interested in. Observe the game from an analytical perspective and focus on the things that might add or subtract from a given prop line. So, the reason that I say that is because in many cases there are certain elements that are not fully included in the line that can become apparent if you watch the game with the right analytical approach. And the example that I'd bet 1 to give is NBA rebounding props.

Now most people know that rebounds are impersonal in nature and it's been talked about in a number of poker bankroll management spreadsheet books about, rebounding props and you can do a lot of statistical analysis on rebounding props, which is all very well and good. But this particular example, we're going to go in a slightly different direction, which if you say that you were to just pick one basketball player and watch them every game that they played for an entire season and take notes. Don't watch where poker bankroll management spreadsheet ball necessarily is. And some of the characteristics of that matchup. So if the opponent that the players matched up against is someone that likes to drive to click pain to make layups and close to the bucket shots that see more a tendency to collapse the defence towards the basket, which means that your player in this prop scenario is closer to the basket and therefore more likely to get defensive rebounds, and defensive rebounds make up the bulk of the rebounding opportunities in a given game for the purposes of total rebound props.

Conversely, if an opponent that- that this player is matched up against click here a perimeter wing or a poker bankroll management spreadsheet shooter, the defending player click here going to be closer to the three-point line further away from the basket. And as a result, they're not going to get as many defensive rebound opportunities because the centre or whoever is closest to the basket is more likely to grab those. And so, you would be able to ascertain that by watching the player poker bankroll management spreadsheet the course of a season and taking notes on those things, but it might not be fully included in the line and it might not be as easy to see that if you're just looking at the data of their average rebounds per game or their average rebounds versus this particular team or whatever else.

There was login lotto brandenburg interview by Bob Bulgaris where in the interview he said that one of his most important questions, and he described having six or eight televisions all in front of him where he would watch six or eight NBA games simultaneously and take notes too, to supplement his statistical model. But the question that he thought was one of the most important was what's not in the line, right? What information which we would be able to get from the game that's not already in the current market line. And so, I thought that was a great question. Very helpful question. And that is just one little sort of almost example of a way that you could start to develop some insights of your own by watching NBA games for a poker bankroll management spreadsheet rebound prop opportunity. To get into the some finer details about how we might go about building a model. I would I guess I'll now transition a basic framework for how you might put read more a model for a prop.

Like expected strike outs in major league baseball. So in this example yeah, we're just going to do expected strikeouts for a number of strikeouts prop bet. Something that you can find on most poker bankroll management spreadsheet, including Pinnacle. The first step for me is I actually brainstormed the ideal case. So I asked myself an open-ended question or conceptualize it in an open-ended way to try and get the brainstorming going. So I would say something like, if you could tell me exactly how many batters pitcher X will face and exactly what his strike out percentage would be. I could tell you his expected number of strike outs.

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Now that's just to get please click for source ideas moving. It's obviously we're never going to be able to do that perfectly, but we want to try and come up with ideas that might help us approximate that. So that leads to the next question, which is: What information would we need to poker bankroll management spreadsheet and approximate this or turn this into a reality? Well, the first step is going to be to create a base expectation for strikeouts or strikeout rate because there's more than one way to do it. If you look at pure strike outs, there's going to be a little bit of statistical noise in there because we're not really mapping the underlying process. We're mapping the result poker bankroll management spreadsheet which is something that I talk about a little bit in the book, but we might want to take a say saying [sic] that we're going to do Walker Buehler as the pitcher and we may be the first thing that we should do is take all the games he's played, how many strikeouts he's got and do a distribution fitting to see poker bankroll management spreadsheet distribution appears to fit the data.

And we might discover that it's largely push on in nature, which will help us when we want to convert our base expectation into a probability later. So back to creating the base expectation, how can we strikeouts and convert them into something that maybe is more predictive, like an expected strike rate because what's actually happened, there'll be a little bit of noise and if we could get rid of that would really be handy. Well, we'll probably do strike out rate. We'll probably be using some permutation of a regression analysis of some kind. And as it turns out there are a number of resources online available for this particular prop.

And certainly, there are more advanced ways to do this, but it's possible to create a regression for expected strike rate using a picture of strike percentage: Their looking strike percentage, their swinging strike percentage and their foul strike percentage. And if you put all those together, you can come up with a regression model that does a pretty decent job of mapping the expected strike rate. So if we have now an expected strike rate as a base forecast, we now need to make an a few additional refinements, right?

So obviously there are a few other things that we know about poker bankroll management spreadsheet game that's about to be played that we can use to help us. The first is the opponent, right. What's the opponent's strike rate look like? And we can go as deep into this as necessary or as high level as necessary. But for the purposes of simplicity, let's just assume that we're poker bankroll management spreadsheet at- we're just going to look at some team-based stuff. So the opposing team, we might want to know poker bankroll management spreadsheet good or bad are they in terms of their strike rate.

Are these a- is this a team that strikes out a lot because they're swinging hard at- at every pitch or are they very selective and they walk a lot and whatever? So an easy way to do that would be to take the teams, the opponent team strike rate and divide by the league average strike rate to get a percentage adjustment. And if we do that for every team, we will end up with 0. If we use that and multiply it by the expected strike rate, we now have an adjustment for poker bankroll management spreadsheet opponent expected strike rate as well. Your kostenlos online spielen mahjong assured poker bankroll management spreadsheet we have the pitchers expected strike rate based on a linear regression as well as an opponent adjustment.

So if we take that and say that that's our base expectation which, which has now been adjusted for our spiele ab jahren online kostenlos and it'll be a simplistic way. We now need to know a few other things to answer the question that we pose to ourselves in the, at the outset of this. We need to know how many batters we expect Walker Buehler to face for every inning that he pitches. And we also need to know how many innings do we expect them to pitch because obviously the larger the number of batters that he faces at a given strikeout rate, the higher the number of strikeouts should be, which only makes sense. So that's the next step of the process. So we might … if we could just look at averages to be simple here.

Or like I click to see more, do you know, you could you can go much more in depth than that and certainly you should. But if we take the expected innings pitched and we times it by just click for source expected batter's face printing pitched and we times that by our opponent adjusted expected strike rate, we should have an expected number of strike outs and then that would be the number that we can take and plug into a personal distribution, and then derive a probability for whether Walker Buehler should be over or under X amount of strikeouts given a market price. And that would be a basic walk through of a prop model. There are other ways to do it.

Of course, you could take the mean and standard deviation for Walker Buehler's expected strikeout rate. You could run some Monte Carlo simulations of varying complexity track those projections for multiple pitchers against the market using log loss, RMSE, Mae, stuff like that. But that would be a basic process. I think the law school and the betting, Andrew, you might have to look into becoming a lecturer. That was really great. I'm sure the listeners found that very useful. Thanks for that. What I'd like to know then as you get, you get these outputs and your model gives you something of a probability where you're then looking at a discrepancy between what you derive and then what the mark actually posts. I'm guessing here that you don't go then straight into using Kelly or whatever it might be to start betting.

Are you suggesting people test back, test against historical data sets of odds, or is it small stakes to start with to test things out? What's the next step from there? Well, yeah you definitely want to do all of the above. I would say for the love of God, don't go full Kelly immediately. When you find a discrepancy, that's a recipe for disaster. For a number of reasons, not the least of which is that full Kelly underestimates the probability of ruin. And if you burn out your entire bank roll, you are effectively finished for the time being as a sports bettor. So poker bankroll management spreadsheet needs to be kept in the forefront of your mind at all times. You definitely want to track this number of ways to track it. Obviously, [there are] lots of different arguments about the efficacy of closing line value and how predictive it is.

What I think is most useful for people to know is that closing line value is a metric that can provide you with a better estimation of long-term profit potential. And this is the key with fewer trials than profit or ROI. So, if you don't want to back test it on an entire season of props and collect all that data and whatever, you could get a pretty good idea of how well you might do by tracking the CLV paper trading on a smaller number of trials, which can make the CLV very handy for that. How you actually want to track it is somewhat of a matter of a personal preference. If you probably certainly want to consider log loss because obviously we're creating our own probabilities and then we're comparing them to the market's probabilities, so those probabilities are better. That's something that we definitely want to know, which log loss can help with. If you would prefer. You can also look at the you mean absolute error, which would tell you, who's doing a better job of actually predicting the number of strikeouts or the count data in this case.

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