by Jack Pendleton, pendleton.87@osu.edu, Economics
My spring semester project intends to analyze player and character placements across major tournaments in 2019 and early 2020. This falls under the Original Inquiry of the Honors and Scholars G.O.A.L.S. as I researched and analyzed data in order to procure information about the smash scene in the last year.
I originally came up with this idea because of my passion for the game, as well as noticing an overall lack of statistics provided for the game. Due to the statistics for the game coming entirely from fans there is an overall lack of information when compared to other Esports such as Overwatch which has its own league that keeps track of important statistics and player data. I worked on my own to complete this project so that I could share it with the community. I worked on the project throughout the semester gathering the data of tournaments that had been played in 2019 in the first weeks of the semester. As tournaments in 20202 were played I added them to my spreadsheet. Unfortunately, the majority of major tournaments that would have been played were cancelled due to COVID-19 resulting in the decreased quantity of data to analyze. After I got all my data I really just wen ahead and found the parameters that I was interested all in one day.
The results of my project were quite enlightening about the state of the top ten players as well as the differences in placement across multiple characters in the game. As can be seen in this list of average placements as well as the standard deviation of placement the number one player Hungrybox shows clear dominance as the number one while being extremely consistent throughout the year. In addition one is able to see separation between the upper half and lower half of players for the most part. With the upper top players for the most part averaging close to 4 while those on the fringe of the top 10 averaging more around 6.
In addition when analyzing the stats for the most played characters we also see a bit of interesting data. The most alluring to me is the very low average placement by Jigglypuff, but with a much higher standard deviation. The thing that makes this which is not reflected in the data is that the placements for that character, unlike others, is not following the standard distribution but rather follows a bimodal distribution with Hungrybox, being the only top Jigglypuff player with his results being evened out with the other Jigglypuff players who do not place in the middle spots but only in the 9 and 10 area.
Further we see things that fans of the community would mostly expect with higher tier characters placing higher as well as seeing more play and placements in the top spots of tournaments. One suprising thing would be the higher placements of Captain Falcon players in the 2019 season as compared to his place on the tier list. This may be explained by a break out year for Captain Falcon main Wizzrobe but the lower standard deviation would imply that Falcon players as whole seemed to have a favorable year.
Overall this really helped enhance my understanding of the placements of players and characters for the 2019 season as well as giving me a taste of how to do my own research. By pushing me to do something I might not normally do this project has enhanced my urge to seek out answers on my own rather than wait for others to gather the information. This project has also given me a look into gathering data for Esports which is a field that I wish to work in after graduation.