Yes it definitely will, however it’s more of setting the value of a tie as a loss for the team you calc for. So if I’m trying to find the real prob of a win for team A and team B, and don’t count ties, I’d have to calculate each individually. I can also calculate the tie scenarios as well, but if it’s ties lose, and I want to calculate the prob to win, I’d calc team A and just 1-P(A) because it’s faster.

Glad you’ve liked the content. I did receive lots of requests for starting with zero Excel and stat basics, so we are gonna do this series from nothing and just keep building up to models that can be modified for actual use

Not sure, but here is the section of the loop: For currentRow = formulaRow + skipRows + 1 To lastRow Step skipRows + 1 ws.Range("B" & formulaRow & ":H" & formulaRow).Copy ws.Range("B" & currentRow).PasteSpecial Paste:=xlPasteFormulas Next currentRow

Think you meant the "=" but if not the full thing is in comment above

Perfect! Thank you!

Could be a rounding error, or a possible scenario you didn't grab that looks like a 0.0% but is actually more of a .0001 kind of number. Only other thing I can think of is that perhaps once of the cells that is calculating is referencing another value accidently.

It would be a count for whatever you are aiming for. So I’d target the column of outcomes =countif(L:L, “A”)/10,000 this would give the prob Away winning given the outcomes of the Monte Carlo

This can be used for other stats like receiving yards, and other stats that are non-discrete (non-count). This is more of an intro model which is why I used it for a discrete type of prop like receptions. For discrete, you would want to use more of binom.dist or poisson depending upon what specifically you are looking for.

The environment I use is PyCharm. There are several options out there, but for me I like the ease of PyCharm. Some have also tried using googles cloud options to not need to store and run locally, but I prefer to have it run on my machine.

Thanks! Hopefully it is of use to everyone, and they integrate into their models

It will be nearly the same. You won’t need to go find as much stuff to install or manage. As far as code, not sure how big the projects can go in their notebooks, but the code itself should all be fine

I haven’t worked very much in the collab environment, so that is based on my limited knowledge

It can be. It really depends upon what stats you think will have an impact on the outcome. if the way Player A plays impacts Player B. Then you would want to use player level stats. If you think team level stats are reliable to still calculate probability of winning, then you can stick with team level and other stats. Some sports, team level can be used, in others player level and play by play would be needed.

So, hopefully this is going to answer the question, if I understand it properly. All stats are descriptive. Then depending upon your question you are asking, the stat could be more predictive than another. The first step is to know what specific question you are asking to solve, then find related stats that independently or have co-linearity, to answer your question. If we were asking questions about the NFL, we could say weather stats, defensive stats, and offensive stats all can be combined and worked together to form predictions. So the past descriptive stats could then answer questions like How many receiving yards will player XYZ get since in the past we have seen these stats form certain patterns/trends, or using things like linear regression.

I have not fully done a walk through on mlb. I did do some for Unabated that you could check out.

So, unfortunately a futures model for Superbowl/Season Wins is far more complex than what I honestly would cover, as it requires probabilities of teams winning different games, injuries, draft spots of teams (tanking), etc. I prefer to use Unabated season tool for finding edges in the market. I have a LOOSE model that gives me some ideas, then use the tool to guide further to find any decent bets. You could do a monte carlo sim where you were to do a power rating model, then sim each week of the season adjusting power ratings, which then adjusts the winner each week.

The issue is with the format of the text/values in the file you have. They must have some kind of special charter. Often this can happen with player names. You can either clean up the values in the file, or use additional code to tell it to ignore the issues. I can get the line of code you’d need in a day, I need to grab from one of my other models.

Okay, so for the file you are importing, I would add ", encoding="ISO-8859-1" " That should help with the encoding issue.

Yes, this could be used in shots, goals, and corners.

The MLS file will contain urls that I want to loop through for the MLS data on fbref. You would need ne to create this file so that allow the scrapper to pull in the information. The encoding portion allows for unique characters to be properly handled by the Python script so it doesn't fail out if it see's a non-standard character in a name.

So, usually once you paste it in for the first time, you will need to modify the data to match a table, however that setup should continue to exist. Did it at least paste in as some readable values, or is it all in column A with html?

@@wageredontilt1649It was just html in column a. So weird. I also switched the settings to split by column and it didn’t do anything. Thank you for responding!

@@Actapguru That is odd. The only other thing I would suggest is maybe point your excel to a website, and import html. Then give it a try by copying and pasting in the html from python. Not sure why it is only wanting to display it as html. The only other thing I can think is that the html is incomplete so it doesn't know how to render.

@@wageredontilt1649 Ok thank you! What python software do you use? i use pycharm so i’m wondering if it delivers the html differently

It’s an excel issue, I use the same Pycharm. Some have had issues with it before as well

Yeah, MC works really well when you have small data sets. You can also bootstrap data; and then MC for really good results.

@@wageredontilt1649 wow thanks for that. I will try that today

You’d likely want to randomize it all for the formula. So, I’d set it up to randomize targets, and probabilities, then take that value and put through regression formula and save the result. Then have the MC do it again, and so on for 10k loops. Then you’d plot or measure the results of those 10k scenarios.

They are both really solid books. I think everyone should read them that want to start to model. It helped me for my intro understanding. If you like the books, I’d also give him a follow on X. Has really good insights.

I am just using the inspect feature, which is in most browsers. So, if you are using Chrome, or Firefox, if you right click on the screen. The floating options will appear, and you click on inspect. That should open up the html on the screen.

Sorry it didn’t go into enough detail on the model building for you. What aspect of the model building piece were you hoping to find that wasn’t covered?

@@wageredontilt1649 Sorry I miss read the Title. Changed my comment.

@@jefffriend1306 ​ @jefffriend1306 Okay, thank you for the reply back! If there is anything specific that you were hoping to see on modeling, or sports betting that you don't see in any of my content, please let me know. I can try and work something up.

@@wageredontilt1649 right now I am trying to learn all I can about differnet models for different NFL stats. I really know nothing about any of it. Thanks for the reply!

For the FIP v AVG is displaying in the cell as a gut check when looking at your numbers, and the actual FIP is used within Esta RA/IP, which then cascades down into the other cells.

Prop bets are your best option for +EV plays consistently

I’ve done differing props. When you say 1st down rushing prop, can you explain the prop a bit more? How many first downs? Who will get the first down? Etc

@@wageredontilt1649 yes my bad, I could’ve explained myself better 😂 and thank you a lot for replying too! I currently wanna make a model on which team in the nfl will get more rushing 1st downs than the other one. For example, let’s say it’s week 7 of the nfl season, and you have Baltimore at home and Steelers playing away. Which team will have a better rushing game as a team? As well, is there a way to implement a defense rank then use that rank against your prediction of your rushing 1st downs? Sort of like a Bayesian model

@StertyOG for something like this you will want to account for predicated score, and occurrence of runs in sets of downs. You’d also want to bake in the probability the defense gives up a pass v giving up the run, and bake in the distribution of yardage a team earns per run per down and what defense gives up.

@@wageredontilt1649 thank you! I’ll try!

Books by Andrew Mack are amazing and so are Ed Millers “Intercept”

It would depend upon what you set your pass fail probability too, as well what you mean better stats = lower probability. Do you have an example of data you see that happening with?

Is the IF for the p()? If so, it sounds like there is a reference key mistaken. Can you copy and paste the formula you have into a comment? I can take a look from there.

For a temporary fix, I created a full list of players on a new sheet, then set each line up field to be a drop down. I will look up the player line up from differing sites (depending which one will post first), and begin typing in the name, for the drop down to find the player. Unfortunately there are no sites I have found with an easy pull in structure. To get stats or lineups history, you will need to set up scripts via pyhton.

@@wageredontilt1649 Ok unfortunately I don't know python to configure and extract in excel .otherwise i use this site for lineup baseballmonster

No, I no longer offer a git for this, I had too many ppl asking for customized code, or passing code off as their own.

You may be talking about the videos I did for Unabated. Those videos can be found below. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-SX2xANBCqsY.html

@@wageredontilt1649 yes that's the video I was thinking of. Thank you!

So, many of my videos that cover the betting side are done in excel videos so you can see the formulas, and the how and why the math/stats work. When I say that the models I show can't be used to win, I mean the model at the state it is in. If you were to add/use differing stats with differing correlations and dependencies, you can beat the books. Any full developed and active betting models are not exposed as to not give away the edge that has been discovered. An example would be the NHL line up builder series I have. That model conceptually can win, however if you do exactly what I do in the video, it will not beat the book as you need more stats and relational data to get an edge on a sports book line.

I will be updating/doing a new video reflecting this.

When you say replace them; do you mean dynamic? Or just changing out the data sets as is?

@@wageredontilt1649 change them automatically and manually if possible a video would be interesting on this subject, best regard

Also can you explain how you would import API as well?

So, you would be able to use player line up data to create a team prediction; or you can use some basic team stats to build predictions (though not totally accurate) There are a few videos on the channel covering these.

One would be here Linear Regression and Player Stats in Excel ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-IDlyb7r3bJ4.html

I will be updating/doing a new video reflecting this.

The vise description contains the link for the sheet. As far as automation, you would need to update the with code either in excel or google sheet scripts

Using a standard possession formula, or data set, you can calculate how many possessions will exist for a player in a minute, then estimate the minutes the player will be on the court. Using that info, you can map out the how many the players on a team will likely have in a given game.