So how to bid in Contestant’s Row? Let’s discuss what to do, and what not to do, based on whether you bid 1st, 2nd, 3rd, or last (Bidder 1, Bidder 2, Bidder 3, Bidder 4).
Please pick up the book in ~1 year’s time to learn more. 🧵👇
1. Let’s start off and define the goal: To maximize one’s odds of being closest to the actual retail price without going over? This does not mean having the best point estimate, but rather capturing the largest probability of winning across reasonable price ranges.
2. Bidding $1,000 as Bidder 1 for an item you think is worth about $1,100 does not do you much good if one of the subsequent bidders bids $1,001 (“clips” you). As an early bidder, the better your bid is, the more likely it is to be clipped.
3. Being overly concerned about going over as Bidder 1 is foolish because Bidder 1 only won 18% of bidding rounds in Seasons 47-48, with Bidder 4 winning 41% of the time. As the first bidder, you should be willing to go over a lot if it ups your chance of winning above 18%.
4. Recall that underbidding was egregious. The highest bid won 53% of bidding rounds, and the last bidder, who has the benefit of being able to bid $1 over the highest bid or bid $1, won 64% of the time with the highest bid.
5. Last Bidder: Most fans realize Bidder 4 should bid $1 over the best prior bid or bid $1 if the chance of Bidders 1-3 having gone over is high. But Bidder 4 also gets to bid 4th in a re-bid, so a $1 bid is only practical if odds of winning are better than winning on a re-bid
6. Underbidding and strategic play by Bidder 4 meant that the most frequent pattern was for Bidders 1-3 to come in low and somewhat clustered, with Bidder 4 topping the highest prior bid by $1, as seen in the examples below.
7. Now for Bidders 1-3: Things get a bit advanced. Consider a simplified game where 4 bidders are choosing a random number between 1 and 100, as if in Contestant’s Row. Bidder 1 should bid 77.78, Bidder 2 should bid 55.56, Bidder 3 should bid 33.34, and Bidder 4 should bid 0.01
8. In this game, with these strategies, Bidder 1, 2, and 3 will each win 2/9 of the time, and Bidder 4 will win 1/3 of the time. But Contestant’s Row bidding is a lot more complex than choosing a random number between 1 and 100. Or is it?
9. Turns out that Bidder 1 should mostly bid towards the high end of the range of values he/she feels are realistic. That move “self-limits” the range of values over which he/she can win but prevents others from clipping his/her bid or coming in slightly above.
10. Of course, this Bidder 1 strategy does not work as cleanly as it does in the Simplified Game. It works better for known prizes like electronics where contestants are likely to agree on the likely range of values for that prize.
11. Without going into to detail, Bidder 2 has a couple different best actions depending on how Bidder 1 bids, and Bidder 3 has a few best actions depending on how Bidder 1 and Bidder 2 bids.
12. If Bidder 1 goes high, Bidders 2 and 3 should come in progressively lower, as in the Simplified Game. But if Bidder 1 instead delivers his best estimate (i.e. in the middle of the likely range), Bidder 2 should go high, as Bidder 1 should have done.
13. Broadening one’s bid has relevance in real life. In applying for college, good grades make for a good point estimate bid. But how can you broaden your bid to include athletics, extracurriculars, and volunteer activities, so that you have a greater chance of gaining admission?
14. In case you are skeptical that Bidder 1 should always bid high, the evidence on underbidding may convince you otherwise. My next thread.
Who would think the highest bid in Contestant’s Row would prevail over 50% of the time? Certainly not me when I started my research.
Please pick up the book in about one year’s time to learn more. 🧵👇
1, The last bidder (Bidder 4) won Contestant’s Row bidding 41% of the time. He would have won 53% of the time had he always bid $1 above the highest prior bid.
2. Bidder 4 won with a $1 bid only 26% of the time. Had he instead bid $1 over the highest prior bid every time he bid $1, he would have won 44% of the time. That’s how egregious underbidding was.
You are probably thinking – Let’s Dig in to the Conclusions Already! Here are some interesting takeaways as it relates to contestant shortfalls and biases. The next threads will address the right strategies 🧵👇
1. Contestant’s Row: underbidding was very pronounced. The highest bid won 53% of bidding rounds, and the last bidder, who has the benefit of being able to bid $1 over the highest bid or bid $1, won 64% of the time with the highest bid.
2. Contestant Rows: bidders seemed to anchor their bids based on the 1st bid made, whether the 1st bid made sense or not. This amplified the underbidding, in as much as the 1st bidder underbid for a variety of reasons, and then latter bidders followed his/her lead.
Introduction to “Decoding The Price Is Right,” Thread Two:
When watching the show, I wondered what strategies would maximize one’s chances of winning, across Contestant’s Row Bidding, The Showcase Showdown, and many of the Pricing Games.
Haven’t you? 🧵👇
1. TPIR strategies are governed by various fields of math. Contestant’s Row and the Showcase Showdown are unique game theory problems. Human biases create some unexpected outcomes in the Showcase. And many Pricing Games are governed by interesting applications of probability.
2. I have always loved probabilities. In college I studied math & economics. I loved game theory, which studies mathematical models of strategic interaction among rational decision-makers. Sequential games like bidding on TPIR include Tic Tac Toe, Connect Four, & Chess.
Introduction Thread: Like many of you, I grew up watching The Price Is Right. During snow days, holidays, always at 11am. TPIR provides millions exposure to games of probability and chance in a way few other shared experiences do.🧵👇
1. Why do fans love TPIR?
Why would they not?
Fans winning great prizes.
The excitement of being called down from the audience.
Guessing prices, with the audience shouting out suggestions. The Price Is Right is “ingrained in American culture,” to quote model Rachel Reynolds
@chadsgx’s “Pitch Your Startup Spaces,” held Mondays at 8pm, is a great resource.
I am enjoying being a regular panelist.
A thread 👇🧵
1. I invested in five start-ups at a seed stage from 2015-2019. Three are going very well, and I have added to my investment in two of those recently.
2. I have taken more concentrated bets because I like finding start-ups and entrepreneurs whom I have conviction in versus being part of a fund with questionable deal flow access and high fees.