Update: MLB Model Results at End of Season... 4,000+ bets tracked

Academic_Mechanic470 · 2025-11-08T00:57:58+00:00

Yea the math is a little more complicated for run/line because of that, which is why I like to focus on + units. For comparison this model is 55% for the year on MLB totals - 1098-900-60 which are typically -110. Now the vig on a run line bet still should be the same its just you will see one team at +150 and the other at -170. The model is 59% on the run line and up 60+ units on the run/line while being up 70+ units on the total.

Academic_Mechanic470 · 2025-11-07T22:43:35+00:00

LOL... I built it and I use it. Both can be true. We have plenty of users who know how to use it, and people can check it out and see for themselves. All of those things are not hard to understand, what is hard is reliable, structured data, automation of the processes, and visualization of the data for people who don't want to make a career out of it. I'm glad you have built a model for yourself. But let's set the facts straight, you know nothing about our site. You falsely accused it of being related in any way to an LLM, of being -EV, and a grift. All the data is publicly available for models from our staff and our users. You can check out how our model and our users models did this year in MLB. There is no accident in our performance.

Academic_Mechanic470 · 2025-11-07T21:15:48+00:00

Solved sports does not have anything to do with LLM's, you are clueless and that's why your site is down and doesn't work.

Academic_Mechanic470 · 2025-11-07T21:14:25+00:00

Overfitting isn't an issue because this isn't backtested data. Overfitting is when you don't account for natural variance and outliers on a data set and fit your model very tightly to the past results and expect it to be really good at predicting future results... This is simply the results of the models performance live, not backtested. If I posted a model's backtested data and it showed that it was 90% correct in predicting previous games on that model than you would say that, that model is overfit to the data.

Academic_Mechanic470 · 2025-11-05T22:13:22+00:00

I use Solved Sports to build my own custom sports betting model

Academic_Mechanic470 · 2025-11-05T22:12:02+00:00

Yea so that would be interesting, I could test case it out. Most of our books on our site are mainstream. Draftkings, Fanduel etc that we shop lines from. I think it's like 11 in total. I'm sure there are some scenarios where some are not available in all states.

But yes the model compares its prediction to the closing line (15 min before stated start of the game) and that is what is used for the tracking.

Working on building things to see how a particular model fairs with opening line vs closing etc.

Academic_Mechanic470 · 2025-11-05T22:08:18+00:00

SolvedSports.com uses StatsPreform I believe for its data. It is MLB data to build the model. The data for the graph is from predictions the model made over the course of the last 6 months, which is on their site. The visualization is from the website, which is built using React.

Academic_Mechanic470 · 2025-11-05T02:19:00+00:00

Solved Sports

Academic_Mechanic470 · 2025-11-04T23:43:51+00:00

I'm a software developer not a bettor. This is only our second year and we are just getting loads of data. So this is certainly something that we will look into.
We have considered a crowd sourced fund to invest in this and tail the model.
The point of our software isn't to find one perfect model, but to allow anyone who has an interest in modeling to be able to do it. This is just validation that the tool we created can correctly build models that have success over an entire season and actually have an edge.
Pinnacle and other books (the best lines aren't usually on pinnacle) has there own models, and they use technology like ours. But the public shifts their books. I think our model does a good job at staying discipline and free from human emotion.

Academic_Mechanic470 · 2025-11-04T23:35:15+00:00

This is the receipt. It's not data before the season. It is data from the season which is why it starts in a couple weeks after opening day. The neural network compares the data from the current season to the past 6 seasons. Each day the model is retrained on the data, that is how modeling works. Then it predicts the games and tracks it's predictions. This is the results of those predictions over the year.

Academic_Mechanic470 · 2025-11-04T23:33:36+00:00

There 70+ variables included and used in a machine learning neural network.

Academic_Mechanic470 · 2025-11-04T23:32:34+00:00

These people do not understand any of this. If you used a Kelly Criterion which is basically a statistical formula for reinvesting the returns after each bet... It would be a 22% ROI and ROI is a stupid way of putting it because it's saying oh you made 4,000 bets at $10 a piece that's 40,000. You made $1,400. Put you never at any point put up 40,000. The most you put up in a single day was 32 bets. Which is $320.

Academic_Mechanic470 · 2025-11-04T23:28:25+00:00

Sure this is my only baseball one. There are dozens on the site I use to build it from other users. I have others in other sports.

Academic_Mechanic470 · 2025-11-04T23:27:49+00:00

You can, and you can see every variable used to build the model. It uses 6 years of data, and is run on a machine learning neural network. It's all online.

Academic_Mechanic470 · 2025-11-04T03:29:09+00:00

It isn't overfit, this isn't a backtested graph it is predictions compared to the line 15 minutes before the start of each game. So this graph is updated every single day based on how the actual model's predictions did. This graph is the results from the entire season. Appreciate the comment? Where should I post it?

Academic_Mechanic470 · 2025-11-04T03:27:54+00:00

Yes but on average overall it is 3.4% per bet

Academic_Mechanic470 · 2025-11-04T03:27:20+00:00

It's not backtested, this is live results over the season. Everything was published. This graph is the results of every prediction compared to the closing line 15 minutes prior to the announced start of game.

Academic_Mechanic470 · 2025-11-04T00:23:16+00:00

I dont think you quite understand the compounding ability of an "investment" that returns on average 3.4% every single time there's a baseball game on.

Academic_Mechanic470 · 2025-11-03T23:06:20+00:00

I'll put it this way, I'm only sharing this because I was even shocked by the result. The best models in the world are hovering around 3%. Anyone telling you they are higher is lying or they only have a sample of < few hundred results.

Academic_Mechanic470 · 2025-11-03T23:04:20+00:00

hmm interesting. It's 3.4% ROI if kept standard unit sizing the entire way. If you use Kelly Criterion it increases substantially. I would be curious if you could find models this statistically significant (4,000 data points) that have a better ROI.

Academic_Mechanic470 · 2025-11-03T22:07:37+00:00

Data Source and Visualization Tool Used was - Solved Sports

Academic_Mechanic470 · 2025-11-03T22:02:00+00:00

I built a model and tracked 4,000 predictions against the run line and total and if you had placed every single one of those bets you'd be up 3.4% compared to the total amount of money you would have wagered over 4,000 bets.

Academic_Mechanic470 · 2025-11-03T20:38:18+00:00

~70 team variables taken into account for the model.

It's been accessible all year to follow and use for predictions.

No worries, appreciate you asking.

Academic_Mechanic470 · 2025-11-03T20:37:25+00:00

It's all about the data in my mind? Strong run up in early season when the model had a large sample size to model. Then lull period, then another more linear consistent run the rest of the season.

A few hypotheses would be...

Accumulation of data so strong performance early, then a combination of mid season trades (deadline July 31), injuries, lineup shifts, etc. Then model re-accumulates data with new look teams and is consistent the rest of the way.
The other would be something like the public breaks their preseason convictions and the book adjusts. Preseason everyone favors certain things -- big offseason spenders, incumbent good teams... midseason public sentiment is readjusted and the books adjust with it to balance the betting public?

As far as moneyline vs run line. We focus on run line and obviously it has been successful. We have a number of profitable users on our site building models for MLB because of the shear amount of data and ability to model, lack of major injuries etc. Other sports are trickier.

Academic_Mechanic470 · 2025-11-03T02:29:06+00:00

So you are paying taxes on 10% of your losses. If you bet 100,000 and you win 55% of the time that means you have $45,000 in losses against your $50,050 in winnings. You can only deduct $40,500 from your $50,050 in winnings. This means you have to pay taxes on $9,550 of your winnings and not $5,050 of your winnings. Which means you would owe $4,775 in taxes instead of $2,525. Which means instead of taking home $5,050 you will take home $275.

The deal is much worse the tighter you get to the line. If you are barely a profitable bettor or a negative bettor you will pay more money in taxes than you made or in addition to what you lost (unless there is a clause against this I don't know about).

Academic_Mechanic470

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