I use Python pandas to clean 10k+ rows of betting historical data, and it's free. I drop duplicate rows, fill missing values with the previous day's odds, and calculate implied probability from the mo
I use Python pandas to clean 10k+ rows of betting historical data, and it's free. I drop duplicate rows, fill missing values with the previous day's odds, and calculate implied probability from the moneyline.
The code fits in 20 lines, and it runs in 2 seconds on my AWS t2.micro instance. I export the cleaned data to CSV, and my betting bot uses it to find value bets.
If you're working with sports data, skip the paid tools. Pandas is free, powerful, and works on any system.
Read the original article and join the discussion on Dev.to
Read on Dev.to
🔍 Introduction If you've ever used a bottleneck calculator, you've probably seen a simple...
Introduction When building real-time games on blockchain, one of the biggest challenges...
Reaction time scores are easy to overread. One fast click can feel impressive, but it may not say...
How to Build a Retro Gaming Console with RetroPie 4.8 and Raspberry Pi 5 Note: RetroPie...
Ceci est un post dev.to. Il ne générera pas son front-matter mais uniquement son contenu en...
Introduction One of the core promises of blockchain gaming is fairness. Unlike traditional...