Web Scraping for Sports StatsTuesday, July 02, 2019
Big data has changed the sports industry. From team composition and playing strategy to marketing operations; from sport team owners to betting agencies, sports are commercialized and goes beyond just a social event of group gathering in driving positive social impact. Forbes estimated the sports industry will reach a value of $73.5 billion by 2019. If you ever encountered with sports betting, you probably knew the power of web scraping. When it comes to scraping sports data from websites, many people will think of using R, Python or API of the websites. But all of them are difficult for people with no prior programming background, like me.
So here I would like to introduce the means for non-tech professionals to scrape sports data from websites, by using Octoparse, a beginners-friendly web scraping tool. The advantages you could get are:
Easier - Point & Click visible operations, no programming required.
Faster - You don’t need to study the websites or test your code.
Various Data Formats - Excel, CSV, JSON, HTML, or export to your database, including SQL Server, MySQL, and Oracle.
Where could you scrape the sports data?
To address this question, we need to understand what sports stats are for? The purpose of sports statistics could break down into two parts: Performance Analytics & Market Value Analytics. Somehow the latter will be affected by the former.
Sports performance analytics will require the information including tables, results, fixtures, and standings. Mainly this information could be found on the relevant official sites, like NBA.com, FIFA.com, NFL.com; or some third party websites providing the congregated information, like sportstats.com. Regarding the market value analytics, apart from the above-mentioned information, it requires information from social media or portal sites, to evaluate their social influence.
How can you scrape the sports data?
Instead of a step-by-step tutorial on a specific website, I prefer to show you a roadmap for web-scraping sports data from different kinds of platforms, helping you to find out the right path for web-scraping sports data.
Scraping Table Information
Most sports data are shown in a table, so with the same scraping workflow, you can extract the information from the sports official sites or any third party websites. To create the scraping crawler for retrieving table information, you can follow these two articles:
Scraping data from Social Media
To scrape reviews or tweets from the Social Media for market value analysis, you can open the searching result page in the Octoparse’s built-in browser, or build up key-words input scraping tasks. Please follow the instructions of these articles:
Build Your up-to-date Sports Data Feed
If you need to build a sports data feed, keeping the extracted data updating automatically and continuously, you may want to use Octoparse premium functions: Cloud Extraction. The benefits include:
- The scraping task can be scheduled to run in the cloud at any time and frequency
- Data extracted can feed in the database programatically
- Data collected speed increase up to 6-20 times
- Connected with Octoparse API, with which you can feed the data into your own systems
Actually, you don’t need to figure out all the scraping tutorials above, but just one of them could help you understand the working logic of scraping tasks, then you can apply to other similar websites.
Any questions you encounter in scraping data, Octoparse Support Team is ready to help!
Author: Surie M.(Octoparse Team)
Edit: Ashley Weldon
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