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Welcome to Conundrum 23!
This week let’s take a look at some super light data prep and visualisation in the wonderful world of chess.
Attached is data about a collection of chess games - included is the ID of the players, the victor of each game, and a few other statistics.
Can you display the top 10 players by raw win:loss ratio and display their prowess visually?
Good luck!
@MichaelG and others who are reading.
Thanks for this week's conundrum.
This conundrum is using an ambiguous term, or a term that I do not understand how to calculate.
raw win:loss ratio
If a player played 1 game and lost 0 as many of the participants in this data did. That produces an undefined value for the ratio win/loss, often displayed as a positive Infinity. There are 4381 players who have no losses in the data. (if you drop draws.) All would be calculated as an infinite win/loss ratio.
However, then how do we pick a top 10 from this list? All have the same infinite score. We might want to celebrate a top 10 pick based on the number of wins. So showing the player who had 24 wins with no loss might get the #1 position. A then the player with 18 wins and no loss...
However what about a player that has 45 wins and 1 loss? They made 46 attempts and have a ratio of 45/1 which is lower than the infinity scored by a player who had 1 win and 0 losses. I would think that the player having 45 wins and 1 loss is likely a much better player than the "one-win wonders" in our dataset.
Can anyone point me to a place that produces a calculation to deal with this kind of issue?
@MichaelG can you clarify what you intended by the
top 10 extract the top players by raw win:loss ratio
P.S. What do folks think about dealing with the 950 games that are "draws"? At this point in time, I've dropped those games because they are neither a win nor a loss. We could also give each player .5 wins and .5 losses for the draw.
Looking forward to hearing what others think about the challenge. Please jump in with your ideas.
Hey @tgb417
Thanks for the question/input!
I agree those players with a infinite win/loss ratio present a problem for how I formulated the conundrum - perhaps raw wins would be a better metric. But then that would bias in favour of those plays who played a lot of games - since 10 wins 5 losses would rank lower than 20 wins and 50 losses.
Perhaps a combined score that requires a given number of games played and then awards a value based on the number of wins less the number of losses? Any other ideas?
On what exactly I intended by that I'm afraid that was just a mistype on my part - I meant what it now says:
top 10 players by raw win:loss ratio
Thanks for pointing that out!