AI · Web Scraping · Python Pipeline · Sports Tech

LIV Golf
AI Scoring
Bot

Built a fully automated AI-powered Python bot that scrapes every LIV Golf event in real time, processes scoring data for all players, and generates live leaderboards — zero manual input required.

Client
Gimme Games Productions
Role
Backend / AI Engineer
Trigger
Every LIV Golf Event
Stack
Python · Scraping · AI · APIs
LIV Golf AI Bot · Live Leaderboard
LIV Golf — Jeddah · Round 3
Hole 14 of 18 · 47 players · Auto-updated
POSPLAYERR3TOTTHRU
1
B. DeChambeau
Crushers GC 🇺🇸
-7-19F
2
D. Johnson
4 Aces GC 🇺🇸
-5-16F
3
P. Reed
Crushers GC 🇺🇸
-6-15F
4
C. Niemann
Torque GC 🇨🇱
-4-1314
5
T. Pieters
Range Goats 🇧🇪
-3-1214
6
L. Oosthuizen
Stinger GC 🇿🇦
E-1012
LIVEUpdated 43s ago · AI Bot
0
LIV Golf events covered
0
Players tracked per event
0s
Avg score update interval
0%
Manual intervention required
Pipeline Architecture

How the Bot Works

📅
Event Trigger
LIV schedule detected
🕷️
Scraper
Live scores + player data
🤖
AI Parser
Normalize + enrich data
⚙️
Pipeline
Process & store scores
📊
Output
Live leaderboard API
Overview

🔴 The Problem

  • LIV Golf scoring data had no official public API — only web-based score displays
  • Manual score tracking for 48 players across 54 holes was time-consuming and error-prone
  • Game platform needed real-time data to power fantasy scoring features
  • Score sources inconsistent across events — different formats per tournament

🟢 The Solution

  • Automated Python scraper triggered on every LIV Golf event schedule detection
  • AI-powered parser normalizes inconsistent score formats across events
  • Pipeline stores structured player scores in real time — feeds live leaderboard API
  • Zero manual intervention — fully autonomous from event start to final results
Outcomes & Impact
100% Event CoverageEvery LIV Golf event automatically detected and scored — no missed tournaments since deployment.
Real-Time LeaderboardsScore updates every 60 seconds during live events — powers fantasy platform with live player rankings.
Zero Manual WorkFully automated pipeline — team no longer spends hours manually entering or verifying score data.
AI-Normalized DataLLM parsing handles format inconsistencies across events, ensuring clean structured output every time.
Technology Stack
PythonBeautifulSoupSelenium LLM ParsingFastAPIPostgreSQL CeleryRedisDockerGitHub Actions