Argumentative Visualization

Valmeekam Karthik - kvalmeek@asu.edu - 1216539207

“Play the opening like a book,
the middlegame like a magician,
and the endgame like a machine.” – Rudolph Spielmann

Chess Openings - How to Open?

https://www.kaggle.com/datasnaek/chess


In the game of chess, there are three conventional phases of the game; opening, middle game, end game.
Opening is crucial to win a game of chess and there are many openings that have been discovered. Each of these openings have different implications. Hence we want to know if a player should open with the opening moves that is the most popular among winners or the moves that lead to the most win percentage? On the whole we want to know...
"How to Open?"
We have data of around 20000 chess games with the opening move of each game and the piece color of the winners. Using this we try to determine the top 20 openings that give the best win percentage for a color piece and the 20 most used opening moves by the winning players.
Out of all the games that have been won, white won 52.3% games whereas black won 47.7% of the games

Wins as Percentage For Each Opening
  • Information Access Rhetoric [1]
    • Omission: It uses omission as the chart only focuses on the openings where white as a winner has higher win percentage and omits the openings with black as a winner and having higher win percentages.
    • Metonomy: This chart uses metonomy as the original dataset contains only the opening move for each game. To get a condensed and simpler data, the win percentages for each opening with different color pieces as winners has been calculated. We also use the fixed compariso
  • Mapping Rhetoric [1]
    • Contrast: We showcase win percentage for white and black as winners in a single bar and the win percentages contrast each other.
Wins as Numbers For Each Opening
  • Information Access Rhetoric [1]
    • Omission: It uses omission as the chart only focuses on maximum wins with white as a winner for an opening and does not show it according to the entire number of wins for an opening.
    • Metonomy: This chart also uses metonomy as I calculated the total number of wins for each type of winner for a given opening. I created a subset of the larger dataset
  • Mapping Rhetoric [1]
    • Juxtaposition: We showcase number of wins for white and black as a winner and juxtapose the two bars side by side for each opening

This visualization also follows Typographic emphasizes [1] to highlight win percentage of white and black and Color mappings with white representing white winners and grey representing black winners.

References
[1] Hullman, Jessica, and Nick Diakopoulos. "Visualization rhetoric: Framing effects in narrative visualization." IEEE transactions on visualization and computer graphics 17.12 (2011): 2231-2240.