Kristi Davis & Elizabeth Leeber
LIS 658: Information Visualization
Our goal was to use a set of compiled statistics about popular TV game show “The Price is Right” to create visualizations that would assist a potential contestant. We found this dataset on the r/opendata subreddit. Unless otherwise noted, all visualizations pertain to seasons 29-40; we chose this time period as it contained more complete data in comparison to prior seasons. The current season on television is Season 41, therefore Season 40 is the most recent complete season.
Our analysis is divided into sections representing the distinct segments of the game; for the purpose of this paper they are called “One Bid,” “Pricing Games,” “Showcase Showdown,” and “Final Showcase.” The rules of each segment vary significantly, therefore a contestant’s strategy would need to change to incorporate the trends in the data for that segment.
One Bid Segment
There are four people who have been selected from the audience to Come on Down and take a spot at one of the podiums on Contestant’s Row. They are presented with a prize and asked to bid on it according to what they believe the price to be without going over the product’s price. The person who has the closest bid to that item’s price without going over wins the prize and is called up on stage to participate in more prize games.
Bidding begins from left to right (red, blue, yellow, green) in the first game. Each subsequent game moves from left to right, with the newest person at the podium bidding first. Eventually, the order has the newest contestant bidding first, followed by the second newest and so on until the fourth bidder, who has been at the podium for the longest time.
One Bid: Winner by Order
This visualization shows how many contestants won their way on stage by which order they bid. The dataset includes information on the number of contestants who won, which order they bid in for each season for the past 10 years. Looking at the visualization, you can draw the conclusion that the fourth bidder very clearly has the advantage over the other three. Contestants who bid fourth have nearly twice as many wins as the other three contestants. The first, second and third bidders have approximately the same numbers of wins, with the third bidder appearing to have a slight advantage.
There are several reasons the fourth bidder has the clear advantage. First, they know all of the other three bids, so they can strategize accordingly. They have the option to bid one dollar higher than the other contestants, thereby ensuring if the price is over the top bid, they will win. They can also examine the other bids and determine the other contestants have all overbid, and elect to use the dollar bid strategy outlined in the next visualization.
One Bid: Bidding Strategy
A popular strategy for contestants playing One Bid is to bid one dollar when they think other contestants have gone over the price of the prize. This strategy ensures they will make it up on stage if the other contestants have, in fact, overbid. This visualization examines bidding strategy over the past 10 years in order to examine whether contestants are better off bidding one dollar or attempting to guess the price of the prize. The dataset includes the total number of bidders, those who bid one dollar, those who won with a dollar bid and those who won with a perfect bid.
The stacked line graph allows the viewer to compare the size of the area for each group. From the comparison, it appears as though the one dollar bid strategy tends to work more often than attempting to win with a perfect bid. The ratio of the number of attempted bids (in blue) to that of the number of perfect bids (in red) is much larger than the ratio between the number of $1 bidders (in green) winning with each one dollar bid attempt (in red). You can also see that most contestants don’t ever make it up on stage.
Once the customer has won the One Bid segment, the host brings them up on stage to play one of several pricing games. The structure and prizes vary greatly, but the basic premise of each game involves the contestant guessing the retail prices of items. One of the challenges in working with this data was the large number of pricing games; the initial dataset contains 106 different games. Although the contestant does not get to choose the pricing game that they play, a knowledge of which pricing game they are likely to play would allow them to strategize more effectively.
Frequency of Pricing Game per Season
To create this heat map, I used the compiled list of pricing games as well as the season and frequency of plays for that pricing game. Each data point represents the number of times per season a game was played. One can see that the frequency at which the pricing games are played varies by season; some games are played frequently in one season and then disappear entirely from the lineup (“Barker’s Markers” is absent from Season 37-40, mostly likely because Bob Barker was no longer the host at that point). Others, such as “1 Right Price,” “Pick a Pair,” and “Stack the Deck” are played with consistent frequency over time. There is another category of game, including “Joker,” that gradually diminishes in frequency of plays over time. A contestant on the show’s current season would be advised to become familiar with the games that were most popular in recent seasons, a category which includes “1 Right Price,” “1 Wrong Price,” “3 Strikes,” “Any Number,” “Cover Up,” and “Double Prices.”
Pricing Game Frequency of Plays & Wins (Season 40)
This bubble cluster visualization demonstrates the frequency at which various pricing games were played and won during the most recent completed season. The size of the bubbles corresponds to the number of plays per season, and the color corresponds to the frequency of wins per season. The frequency was determined by dividing the number of wins by the total number of plays; this was added to the data set to make the results easily understandable to the viewer. A contestant would want to familiarize him or herself with the most frequently played games, such as “Squeeze Play” and “Flip Flop,” and would want to be assigned a game with a high frequency of wins, like “Cliff Hangers” or “Pick-a-Pair.”
The showcase showdown is played after the three winners from Contestant’s Row play their pricing game. There are 20 spots on the wheel, each with a dollar amount between 5 cents and one dollar in 5 cent increments. Each contestant gets two spins and tries to get as close to a dollar as possible without going over. The contestant with the highest spin, or combination of two spins, gets to move on to the Showcase. If a contestant spins $1, or two spins that add up to a dollar, he/she wins $1,000 and has a chance to spin for an additional $10,000 or $25,000. In the bonus spin, if the spin lands on .05 or .15 spots (in green), the contestant wins an additional $10,000. If they land on $1 again, they win $25,000.
Showcase Showdown: Odds of Winning
This visualization shows the odds each contestant has of winning the showcase showdown based on the decision the first contestant makes after the first spin. The dataset includes information on the contestant’s spinning order, the dollar amounts on the wheel, and the stay or spin results based on the first spin amount.
Though the spin itself is going to have random results, the bar graphs can help contestants strategize their move after the first spin. By comparing the “1st Contestant Spin” to the “1st Contestant Stay” charts, one can derive that the first contestant should spin again with anything $.65 or less. Doing the same comparison with the 2nd contestant’s data, you can see that their odds get better if they spin again on anything $.55 or less. They also should spin again if they are tied with the first contestant with an amount of $.65 or less. The contestant who spins third has a simpler trajectory, in that they should only spin twice if their first spin does not beat the previous two contestant’s spins. The higher they spin the first time, the better their chance of winning.
Showcase Showdown: Payoff
This visualization shows the number of contestants who have received some form of payoff from the showcase showdown. The dataset includes the number of contestants who won $1,000 by spinning a dollar on the big wheel, and then the number of those who followed up with an additional $10,000 or $25,000 win with the bonus spin. Based on the distribution of the dots, contestants are much more likely to win the smaller amount than they are to win big. Contestants are almost nine times more likely to take home $1,000 than they are to take home the bigger prizes.
There is only a slight difference in contestant’s odds at taking home $11,000 (the original $1,000 plus an additional $10,000 from the additional spin) and $26,000 (the original $1,000 plus an additional $25,000 from the additional spin). The dots are very close to each other, sometimes even overlapping. There are two spots on the wheel that contestants can land on to win ten thousand, while there is only one spot that will win twenty five thousand. However, their close proximity to each other on the visualization points to the fact that there are only three spots out of twenty that will guarantee contestants take home more money, so the chances of winning are much lower.
The final showcase is played the winner of each showcase showdown. The first contestant is that day’s top winner; they are shown a set of items called a “showcase.” This usually consists several smaller prizes in addition to one big-ticket prize, like a car or a boat. The top winner has the option to bid on the first showcase or pass. If they pass, the runner-up bids on that showcase and the top winner bids on the second set of items.
Frequency of Showcase Actions
This graph displays trends over time for the final showcase segment. The years correspond to the starting year for each season (seasons run from fall to spring of the following year). Each colored line represents an action or an outcome; one can isolate the individual lines to aid in analysis. The graph demonstrates that the top winner frequently passes on the first showcase and chooses to bid on the second, and that the runner-up (second contestant) is more likely to win. One would suppose based on this that the strategy employed by the top winner was ineffective, however in the one time period where the top winner won more frequently, they also passed more frequently on the first showcase. The runner-up therefore has a decided advantage over the top winner; potential contestants should aspire to be in this position.
Final Showcase Winners & Losers
This stacked bar graph shows the number of “double winners” and “double losers” per season. A double win occurs when a final showcase contestant successfully guesses the price of their showcase within $1,000 of the actual price; the contestant then receives all of the prizes features in both showcases. A double loss occurs when both contestants overbid on their showcases and no prizes are awarded. It is more likely that a double win will occur than a double loss, which suggests that double overbids are not a frequent occurrence. The graph also demonstrates that there is significant possibility of a double win, with Season 29 having a 9.76% rate of double wins.
Please note that this data contains a calculated field that was derived from the original data set; the number of double wins and the number of double losses for each season was divided by the total number of episodes in that season in order to determine the percentages of wins and losses for each.
In an ideal scenario, a contestant would want to be selected to play at Podium 4 and would bid $1. After being called up on stage, the contestant would be asked to play “Bullseye” or “Pick-a-Pair.” They would then spin the wheel during the showdown and hit a high dollar amount on their first spin; but they wouldn’t be the top winner for that day. They would enter the final showcase as the runner-up and bid within $1,000 of the retail price of their showcase, this winning both sets of prizes.