"Chew! Chew!, that's what they call me" 👀
A full-stack developer from Thailand 👀
📜 Click here! Discover more about me! 👀
Back in 2018, I released a couple of Android mods that helped lots of users have a better experience when they're using their phones. The mods take benefits from that era where most Android phones faced many issues such as "slow" or "having a terrible speakerphone".
Well, actually it's not that bad 55+ but due to the phone having various range prices and OS versions, they have to disable some functions of the phone to make notice between higher phone price and lower phone price. So I decided to make mods and run a community to solve those issues, at first it's just for testing kinda like the beta phase in the group. after being there for a while I had to release it because I felt my time had come!
Without ChatGPT and no incredibly fast growth after the pandemic,
it worked very well, with a total of over 30,000+ downloads. It was a remarkable achievement in my journey.
Go further, if you're a football fan. Have you ever been curious about how bookies provide their odds? Some say they use relevant information and compute it in real time. This topic is completely mysterious and hard to tell exactly how or which data they use.
Hands up if you ever try to get all historical data factors since football has been invented, and get nothing. Don't be disappointed because now I'm gonna give you a hint about this secret.
Come with me, let's explore the hint together.
Firstly, I will start with one question that leads you in the same direction. How many factors are there in a football game? Let's say...
Players stats, Team stats, Leagues stats, Field size, H2H stats, Recent stats, Competition types, Weather, Player's mood, Buying judge or player (Why not cause we all know this is a business game, not charity), Home field advantage, xG stats, Lineup, Injuries, Red card, Team strategies, Tiredness, Individual player tactics, Motivation, VAR (KK), leagues level, Team level, and if that's a competition between countries, you have to acquire each country's history too, not all of the factors has been listed here but that's enough.
Now we can take all of those factors into probability and convert it to the odds... finally, we got this, right? the answer is NO! Based on the factors that I have mentioned, some of them are truly implicit. So, just remember that there's neither probability nor models that give you 100% accuracy.
According to what I said, now we can take only explicit factors and integrate them with statistics, and the rest will be your path, but I will give a little more direction. well, when it comes to math nothing is easy (at least for me). However, a widely accepted method in the football world is to use distributions, depending on what you need, and the Poisson Distribution is a good choice.
Until now, I have been building a Football Prediction Generator. It's a web application that can predict Correct Score, Asian Handicap, and Over/Under with true odds and probability that are close to what bookies provide. Of course, I can't get into deep connection factors like bookies do, but sometimes they can't against and shift the margin/odds that much when the result is about to flip to maintain their secret/profit.
Last but not least, even though it can predict the odds/margin close to what bookies gave and tell the value odds/margin, it doesn't mean or assure that you will get the result in the future at all, not even a bit.
If you are interested in this project, have an edge model, and want to contribute, feel free to contact me. Thanks.
- HTML
- JavaScript
- CSS
- PHP
- SQL
- Vue
- Laravel
- Inertia
- Tailwind
- Alpine
- Pest
- Jest
- React
- LangChain
- Figma
- Visio
- Postman
- Docker
- Git
- JetBrains products
| Language | Proficiency |
|---|---|
| English | Intermediate |
| Thai | Native |


