my name is ajeeb and I scraped every single topps cricket attax(from the ipl) card, except 2017 and found some interesting results. code available on GitHub.

The statistics used were from the current twenty20 statistics(for players who haven’t played twenty20 cricket, we used the odi,t20i database) of the respective players, and labelled them with the values of the cricket attax cards themselves at that time powered by ollama :P

I used Selenium to make a bot that scrapes ESPNcricinfo's Statsguru to fetch statistics for every single player. used ollama to read 950 cards and structure the information i needed from each card.jpeg, took me 2 weeks, but here we are

Now I’m just gonnna let y’all look at the interesting stats and have fun with it, let me know if you have any suggestions on twt (@ajeebtech).

Comparisons

Krunal Pandya vs Hardik Pandya

• Krunal Pandya: Batting 75, Runs: 27, Bowling 55
• Hardik Pandya: Batting 72, Runs: 33, Bowling 42

Krunal had a batting of 75 surprisingly and for some reason Hardik has 72 lmfao

Virat Kohli vs Rohit Sharma

• Virat Kohli: Batting 101, Runs: 71, Bowling 63
• Rohit Sharma: Batting 97, Runs: 51, Bowling 15

I guess Rohit just doesn’t roll his arm anymore 🫠

Chris Gayle vs Travis Head

• Chris Gayle: Batting 101, Runs: 58, Bowling 27
• Travis Head: Batting 74, Runs: 24, Bowling 43

Legend vs legend-in-the-making. Stats-wise, they look hilariously similar. My model is basically doing a similarity contest here. More analysis soon.

Pakistani Players (since they don’t play IPL anymore)

• Fakhar Zaman: Batting 101, Runs: 42, Bowling 5
• Babar Azam: Batting 96, Runs: 53, Bowling 0

Honestly, Babar's stats are wild.

One last one — Bowlers!

• Jasprit Bumrah: Batting 33, Runs: 16, Bowling 99
• Mitchell Starc: Batting 27, Runs: 8, Bowling 98

I don’t mind this. that’s the end of this document(what is this is this a paper or something)

that was my first medium document thank u for reading