The Use of Data Analytics in Recruitment
March 11th, 2019
It’s football season, and that means one thing in the KDR office – Fantasy Football. We have a league set up (called the KDR Cup) to see who has the best team in the office, and with most of us this is down to luck of our picks, but I want to have a look at how big data and analytics can help me gain an advantage on my colleagues.
Similar to how people may use big data and analytics to make sporting bets, they can use it to build the ultimate fantasy football team.
In every game that is played big data is being collected, we can find out each game’s stats, team stats and individual player stats but once this data is fully collected and analysed it can help us to make pretty accurate predictions.
To see how big data helped to predict the outcome of football games we only have to look back to the 2014 world cup. Google and Microsoft both used their own big data and analytics to make predictions, in the end with big data analytics Google was able to predict 14 out of 16 matches correctly, while Microsoft managed to predict 15 out of 16 matches correctly!
With this mass collection of data fantasy football players can see the performance of their team more easily, making it easier to know when to make changes and which players to keep. Many of the apps these games are played on have their own algorithms to score the players and allows the users to make informed decisions.
By using the data and stats that are already provided effectively the ultimate team can be picked. We no longer have to make our predictions based on a lucky hunch or the previous game, we can look at life time statistics to create our team.
The big data that is provided to me is definitely helping me make my decisions, I am currently top of the league! I’m excited to see how big data can continue to improve fantasy football, help me create my team and keep me at the top of the league.
Do you use big data analytics to play fantasy sports? How do you think big data can continue to improve the game?
This blog was originally published on LinkedIn. To read the original article click here