Building a Sports Data Scraper: Stats, Odds, and Live Scores

Sports data is big business. From fantasy sports to betting analytics, there's massive demand for real-time statistics, historical data, and odds comparison. Scraping Sports Statistics import requests from bs4 import BeautifulSoup class SportsStats : def __init__ ( self ): self . session = requests . Session () self . session . headers . update ({ ' User-Agent ' : ' Mozilla/5.0 ' }) def scrape_standings ( self ): url = ' https://www.basketball-reference.com/leagues/NBA_2026_standings.html ' resp = self . session . get ( url ) soup = BeautifulSoup ( resp . text , ' html.parser ' ) standings = [] table = soup . select_one ( ' #confs_standings_E ' ) if table : for row in table . select ( ' tbody tr.full_table ' ): cols = row . select ( ' td ' ) team = row . select_one ( ' th a ' ) if team and len ( cols ) >= 3 : standings . append ({ ' team ' : team . get_text ( strip = True ), ' wins ' : cols [ 0 ]. get_text ( strip = True ), ' losses ' : cols [ 1 ]. get_text ( strip = True ) }) return s