When deciding upon data to use for a visualization, I was drawn to ‘The Price is Right’ pricing games because I have been watching the show since I was young and always imagined which game I would play if I would on the show. As such, I decided to look at the data to determine which game is actually the best to play. I define “best” to be both in terms of the chances of winning said game and the cash value of the prizes offered to contestants of said game. I was able to find a couple of (somewhat obscure) websites that provided me with the data I needed to classify the various games. The Price is Right Stats contains data about every game on the price is right including how many times said game has been played, the most and least expensive prizes offered for said game, and the stats on how many contestants have won said game. Certain games are more complicated than others, and more data was provided for games with more intricate rules. All of the data is ranged in various charts, so I simply copy-pasted this data into Excel. Using Excel functions I was able to calculate the ratio of winners to the number of plays of each game and the average cash winnings of each game.

Although this website gave me hard stats on winning each game, I also wanted to be able to compare the theoretical probabilities of winning each game, as the game stats contain different numbers of samples. I found some websites where such probabilities were already listed, such as The Price is Right Blog: Odds of Winning Pricing Games and Probability and Statistics Through Game Throws. For the rest, I calculated the probabilities by hand using the rules as described by Wikipedia: List of Price is Right Pricing Games and The COMPLETE Pricing Game Directory!

In Excel, I used a linear combination of the found stats and theoretical probabilities to determine the odds of winning each pricing game. By multiplying this value by the average winnings for each game, I was able to determine the “payoff” of each game, and as such the “rating” of playing each game. I plotted this data in my data visualization which you can try out here.

The Price is in the Payoff from Erica Lazrus on Vimeo.

I made a few changes to my original design based on some of the comments at the class crit. Firstly, I decided to order the games based on graphed y-value instead of alphabetically. I also decided to limit the mouse functionality to just scrolling through the games, and to use the keyboard to navigate the right-hand menu. The ‘up’ and ‘down’ arrow keys are used to move up and down the menu. The ‘left’ and ‘right’ arrow keys open and close menu items, respectively. I took away the extrema menu items, as now that the graph is ordered by y-values, the extrema can be found much more easily without these buttons. I added to menu items: Sort By allows the user to change the y-axis from the default payoffs, so maximum possible dollar winnings, the odds of winning this maximum, and the frequency with which each game is played. Search allows user to search for a particular game by name by typing it into the text box and hitting the ‘enter’ key. The added some auto-completion suggested games to help the user search and these can be scrolled through and selected using ‘enter’.