How A Sports Data Analyst Can Benefit From Web Scraping
Everyone loves an underdog story. Our shelves are filled with tales of underestimated heroes fulfilling their destinies against all odds. When Jackie Robinso helped break the race barrier in baseball, he became a national hero and was also subjected to threats. However, these stories are necessarily full of people unable to see the potential in the hero, often because they lack the resources or background to impress those at the top.
What if I told you there was a way to spot the underdog before anyone else? Thankfully, we live in a world full of sports statistics. Gone are the days of ineffable “star quality.” With all the sports data publicly available online, it is easier than ever to find the diamond in the rough. Whether a professional sports coach, someone who places bets on your favorite team, or just a fan looking to gain more insight, sports data analysts can gather information on their favorite players and teams cheaper and faster than ever before!
If you are already familiar with the basics of data and web scraping, use the table of contents below to jump forward to find out how to use sports data in your advantage.
Table of Contents
Understanding Big Data In Sports And Web Scraping
What is big data in sports?
Before you can start using sports data to your advantage, you must first understand what it is and why it is collected. The great thing about American sports data is that it can be used by a myriad of people (players, coaches, recruiters, fans, advertisers, fantasy players). Big data, as defined by Wikipedia, is a field that treats ways to analyze, systemically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with using traditional data processing application software. The more obvious sports data sets pertain to the sports themselves (home runs, goals, wins, losses, etc). Big Data sports, such as professional baseball, basketball, and Hockey become too much for individuals to handle manually when collected over seasons of time and among multiple players and teams. In order to properly analyze all the data available in Big Data sports today, one must use web scraping.
Why is web scraping the easiest way to collect sports data?
Web scraping uses bots to extract, collect, and organize large data sets from websites. For anyone trying to analyze big sports data, web scraping is a great way to collect the most information without getting lost within it. By using a scraping tool, you can organize data by team, league, player, or season for better analysis. Today, many professional sports teams have staff members or entire departments dedicated to statistical analysis. These professionals need access to the most data possible to do their job correctly. The more data they have, the sharper their analysis will be. Web scraping allows these professionals and other fanatics to collect the vast amounts of data they need to succeed without all the manual labor usually required. With all the time and energy web scraping saves, your team will have more time to use the data to win!
Using Data Science In Sports To Build The Strongest Team
When it comes to sports data analysis, there are performance analytics and market value analytics. Performance analytics are statistics about individual and team performance, while market value analytics are based on analyzing the popularity and social value of a player or team.
Performance Analytics for coaching and recruitment
Performance Analytics are collected from official league websites or third party sites that aggregate information for multiple teams and leagues. For American sports data, you should visit the official sites of the NBA, NHL, MLB, and more. If you are a coach and often struggle with determining which player is best for the job, relying on sports data science can take the stress out of your decisions. Instead of picking favorites or trying to gauge what player is best for the moment, data can give you a clear picture free from personal bias. You might be surprised by what players the data favors.
Scraping Robot’s HTML scraper allows users to input any URL and receive the page’s full output. This scraper can be used on any official league website (NBA, MLB, NHL, etc) or third party aggregate sites. Most useful for collecting data on teams and players, this information can be used by fans, players, and coaches to improve decision making.
Market value analytics for building a fanbase
While it is easy to see how sports performance data can be used by players and coaches, market value analytics help marketing teams understand what players are loved by fans and how to build a stronger fanbase. Our social media scraper allows you to analyze an individual user’s followers, accounts they follow, and their biography. This is especially important for sports data analysts looking at collegiate sports data. At many colleges, tailgating season is a rite of passage as students fill the stands cheering on their team. These events are profitable for schools and help them attract potential applicants. When you better understand your fanbase, schools can adjust the game experience accordingly, leading to better attendance and ticket sales. Collegiate sports data is most useful for those involved in advertising school sports, especially universities that want to raise student body engagement and game attendance.
Journalists discovered that many high school seniors use social media sites to scope out colleges and the student body beyond the traditional glossy pamphlets. Looking at photos based on location gives prospective students a glimpse into what students post themselves, turning it into a more meaningful reflection of student life. By having a student body with a strong and positive online presence, younger students will be more attracted to the school. This is why building your audience engagement, especially amongst young people, is crucial to growth.
Sports Betting Data In Fantasy Football And Beyond
Today, we live in a world where fantasy leagues exist for any sport you can imagine. In this realm, sports data is extremely useful to fans whether they are informally betting their friends as part of an extensive fantasy league. If you live where sports betting is legal, then using a web scraping tool can give you an advantage. Similarly, data can help you pick the strongest fantasy team amongst all your friends!
By using data to help you pick your fantasy team, it is easier to find quality players that not everyone wants. (Think: Moneyball.) Instead of competing with your friends for stars, you can use data to find the underdogs. Even if you play fantasy sports as a hobby, it requires a lot of time and information. By using HTML web scraping tools to gather sports betting data and fantasy data, you can collect and organize all the stats without dedicating extra time you don’t have. Web scraping tools are also fairly cheap ways to collect data, making it more accessible for fans and fantasy players alike.
Why Scraping Robot Is The Best Tool For Big Data Sports Analytics
Instead of simply favoring star power, analyzing big data in sports gives you an edge over the competition by allowing you to collect and organize large sets of data. Scraping Robot has multiple modules that sports fans can use.
Ebay Scraper
Any real sports fan also owns real memorabilia. However, in a world of fakes and high prices it can be hard to gauge what jerseys and memorabilia are worth it. By using Scraping Robot’s Ebay scraper, you can easily identify the titles and prices of different items. This helps you save money and wear your favorite colors with pride!
Google Places Scraper
Want to find the best place to watch the big game? With the Google Places scraper, you can input any location and keyword and get the top 20 location results for that keyword. For example, you can look up sports bars in Denver and receive a list of options, ensuring you make the best choice to enjoy your favorite sport in style!
Conclusion
Sports are with us our whole lives. We start as toddlers on the soccer field and eventually become fans in the stands, unless you are lucky enough to make it in the big leagues. No matter your role, sports data is increasingly useful for fans, coaches, and players alike. With a web scraping tool, sports data analysts can discover the underdogs favored by the stats. You can also use social media to better understand what fans love and loathe about their favorite team. For those obsessive fans, scraping can be a tool for acquiring memorabilia at the best price, placing smart bets, and building the perfect fantasy team. While data and sports may feel worlds apart, their union is building stronger and better teams.
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