Open Data & Web Scraping

LCK Spring 2024 Players Statistics

Unlike the other cases — contracted work presented in anonymized form due to confidentiality —, this project is open: a public, auditable, verifiable dataset on Kaggle.

Public, fully verifiable dataset (10.0 Kaggle usability score, the maximum possible) covering the complete LCK (League of Legends Champions Korea) Spring 2024 split: players, champions, and matches organized into three relational tables. Collected via web scraping with BeautifulSoup and Selenium from Gol.gg, with rigorous metric normalization, ready for EDA, visualization, and predictive modeling. Published on Kaggle with a maximum usability score.

python pandas selenium

Case Study

Problem

LCK Spring 2024 statistics scattered across hundreds of individual match pages on Gol.gg, with no relational structure for analysis or modeling.

Solution

Hybrid collection pipeline (BeautifulSoup + Selenium), normalization of inconsistent formats (percentages, MM:SS durations converted to seconds), deduplication, and three tables connected by sequential Player IDs.

Impact

Maximum usability score (10.0) on Kaggle, CC BY 4.0 license, 300+ downloads, and third-party reuse in EDA notebooks, public, auditable proof of data engineering craft.

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