# Visualization of Unstructured Sports Data -- An Example of Cricket Short Text Commentary

arXiv: https://arxiv.org/abs/2404.00030 · HTML: https://mlsanity.com/paper/2404.00030/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 37 references that are in the map.
- First posted on arXiv 22 Mar 2024.

## Builds on (most cited first, 2 of 2)

- [Topic Segmentation and Labeling in Asynchronous Conversations](https://mlsanity.com/paper/1402.0586/) (2014)
- [Online Visual Analytics of Text Streams](https://mlsanity.com/paper/1512.04042/) (2015)

## Abstract (arXiv)

Sports visualization focuses on the use of structured data, such as box-score data and tracking data. Unstructured data sources pertaining to sports are available in various places such as blogs, social media posts, and online news articles. Sports visualization methods either not fully exploited the information present in these sources or the proposed visualizations through the use of these sources did not augment to the body of sports visualization methods. We propose the use of unstructured data, namely cricket short text commentary for visualization. The short text commentary data is used for constructing individual player's strength rules and weakness rules. A computationally feasible definition for player's strength rule and weakness rule is proposed. A visualization method for the constructed rules is presented. In addition, players having similar strength rules or weakness rules is computed and visualized. We demonstrate the usefulness of short text commentary in visualization by analyzing the strengths and weaknesses of cricket players using more than one million text commentaries. We validate the constructed rules through two validation methods. The collected data, source code, and obtained results on more than 500 players are made publicly available.