IMPLEMENTING BIG DATA ANALYSIS TO GET INFORMATION ABOUT MYSELF IN DOTA 2 (Assignment 2)

IMPLEMENTING BIG DATA ANALYSIS

TO GET INFORMATION ABOUT MYSELF

IN DOTA 2

·         Abstract:

Dota 2 is the most played game in the world. Dota 2 has 113 heroes with unique skills and dozens of items. DotA 2 is the most attractive game that should be played by everyone.

And with various heroes and items in Dota 2, I tried to make a research using big data. I already played 700 games so far in Dota 2, and I want to know unique information that comes up after played 700 games.

In this case, I am using dota buff to help me provide all the data that I need to find out my unique information. And here is some information that I got.

·         Win rate by activity by day of week:

Here is the result of my win rate by activity by day by week. The higher the bar means the more often I played in that day. As you  can see, my highest win rates is on Saturday with 53% win rates, followed by Monday with 50% of win rates. The rest of it, I often got loose than win.

·         Win rate by activity by hour of day :

      Here is the result of my win rate by activity by hour of day. The higher the bar means the more often I played in that day. As you can see, my highest win rates are at 1a.m followed by 9a.m, 9p.m, and 7p.m. The rest of it, I often got loose rather than win.

·         Most played heroes with win rates:

         This picture shows us my top 10 most played heroes all the time. The top 3 of the tables is my signature heroes. It means that the most heroes I used all the time. As you can see, my highest win rate heroes is witch doctor with 67.5% win rates, followed by  Warlock with 65.22% win rates, Shadow Fiend 52.38% win rates, and viper with 51.43% win rates.

·         Conclusions:

         After I got all the in formations, now I know if I want to win the game. When I should play dota 2, and what hero should I play.