PlantCrawl

Building CrawlPlant: Apify Actors and data APIs for developers, analysts and AI agents. Turning web data into useful datasets, automated workflows and practical insights.

Joined on Oct 23, 2026 piotr@crawlplant.com https://crawlplant.com

PlantCrawl

Oct 31

Your first tennis prediction model should have a baseline it can lose to

#machinelearning #python #datascience #tutorial

7 min read

Want to connect with PlantCrawl?

Create an account to connect with PlantCrawl. You can also sign in below to proceed if you already have an account.

Create Account

Already have an account? Sign in

PlantCrawl

Oct 30

Turn a tennis final into an illustrated AI recap, with receipts for the pressure games

#python #datavisualization #tutorial #ai

12 min read

PlantCrawl

Oct 29

Ask your tennis dataset a question: AI chooses the filters, Python does the counting

#ai #python #datascience #tutorial

7 min read

PlantCrawl

Oct 28

From 233 tennis matches to one pressure game: connect four Actors into a research workflow

#python #tutorial #datascience #api

7 min read

PlantCrawl

Oct 27

When tennis Elo and the market disagree: build a research shortlist, not a magic pick

#python #datascience #api #tutorial

5 min read

PlantCrawl

Oct 26

A 6–2 set can hide five break points: draw a tennis pressure map in Python

#python #datavisualization #tutorial #api

5 min read

PlantCrawl

Oct 25

One tennis rivalry, three different stories: build a surface-aware H2H card

#python #datascience #tutorial #api

5 min read

PlantCrawl

Oct 24

Your tennis CSV should not stop at last season: build an updating ATP/WTA dataset

#python #datascience #api #tutorial

5 min read

PlantCrawl

Oct 23

Build an AI tennis scout that shows where every fact came from

#ai #python #api #tutorial

9 min read

DEV Community

PlantCrawl

Badges

1 Week Community Wellness Streak

Writing Debut

Your first tennis prediction model should have a baseline it can lose to

Want to connect with PlantCrawl?

Turn a tennis final into an illustrated AI recap, with receipts for the pressure games

Ask your tennis dataset a question: AI chooses the filters, Python does the counting

From 233 tennis matches to one pressure game: connect four Actors into a research workflow

When tennis Elo and the market disagree: build a research shortlist, not a magic pick

A 6–2 set can hide five break points: draw a tennis pressure map in Python

One tennis rivalry, three different stories: build a surface-aware H2H card

Your tennis CSV should not stop at last season: build an updating ATP/WTA dataset

Build an AI tennis scout that shows where every fact came from