Esports Scrapers & Automation
Python data collectors and n8n pipelines for extracting esports match data, team statistics, and updating community sheets automatically.
// esports_pipeline.py — Autonomous Match Collector & Sheet Exporter
import requests, json, time
from bs4 import BeautifulSoup
from googleapiclient.discovery import build
def fetch_tournament_standings(url):
res = requests.get(url, headers={"User-Agent": "EsportsBot/2.0"})
soup = BeautifulSoup(res.text, "html.parser")
matches = parse_match_rows(soup)
return export_to_sheets(matches)
What I Built & Process
01
Problem Statement & Need
Community tournament tracking required hours of manual data entry from match streams and website tables into shared tracking spreadsheets.
02
Architecture & System Design
Wrote Python scrapers (BeautifulSoup/requests) paired with scheduled n8n cron workflows that scrape match scores, format team records, and push structured rows directly to Google Sheets APIs.
03
Shipped Outcome
Fully automated match ingestion pipeline. Replaced 5+ hours of manual weekly entry with 100% automated background execution.