r/TheAmazingRace • u/DaAPlaz • 2h ago
Older Season Age Statistics of The Amazing Race (U.S.)
Warning: lots of text (scary) so i’ll put the summary here:
TLDR: The best age to be to win TAR (U.S.) is about 29 years old, yay!
Other good ages that win are 21, 22, 23, 24, 25, 30, 33, 34, 35, 36 years old (don’t blame me, blame the stats)
I remember watching The Amazing Race for this first time when I was in 6th grade, and I’ve always wanted to apply for the show. However, I began to notice that young people (early 20s) went home early often because they just don’t have enough life experience and get lost easily. That’s when I wondered to myself, at what age should I apply and go on to win The Amazing Race? Soooo….
Statistical Question: What is the optimal age for winning The Amazing Race (U.S.)?
Initially, I thought that you can simply gather the ages of all winners of the race, then find the average/median/mode to get an answer.
However, this kinda is unfair and doesn’t take into account of population size or whatever.
- For example, there are five winners aged 26 years old and four winners aged 33 years old. Based on this information, you may conclude that racers who are 26 years old have a statistically higher chance of winning. However, TAR has cast sixty-two 26-year-olds but only thirty-two 33-year-olds, so it’s probable that there is a higher count of 26-year-old winners compared to 33-year-olds.
Thus, we should compare the win rate of all ages since it accounts for population size i think.
- However, another problem occurs because this method benefits the ages that don’t have many racers. For example, there have been only five 55-year-olds, and since one of them won the race, the win rate for 55-year-olds 20%. This is the largest win rate for any age, but we know obviously that 55-year-olds aren’t the best racers lol.
So now I made a decision to arbitrarily draw borders and make my own conditions. I want to only analyze data sets with ten or more data points since I want to take into account for population size; I developed 2 ways to determine the optimal age for winning The Amazing Race.
- I found the win rate of these age ranges: 19 to 22, 23 to 27, 28 to 32, 33 to 37, 38 to 42, 43 to 47, 48 to 52, 52 to 57, 58 to 62, 63 to 67. It satisfies my condition since there are ten or more racers for each age range. Here’s what I got:
Age Range | 19 to 22 | 23 to 27 | 28 to 32 | 33 to 37 | 38 to 42 | 43 to 47 | 48 to 52 | 53 to 57 | 58 to 62 | 63 to 67 |
---|---|---|---|---|---|---|---|---|---|---|
Win Rate | 12.70% | 10.91% | 8.74% | 10.91% | 4.44% | 10.71% | 4.44% | 10.71% | 0% | 0% |
Close race, but it seems like ages 19 to 22 years old have the highest win rate, so you would conclude that ages 19 to 22 are the optimal ages to win, right? Looking at my second method…
- I found the win rate of each age, but only if there have been ten or more racers with that age. For example, I wouldn’t include 55-year-olds in my data because there have been only five 55-year-old racers. Here’s what I got:
Age | 29 | 34 | 25 | 35 | 22 | 24 | 21 | 36 | 23 | 30 |
---|---|---|---|---|---|---|---|---|---|---|
Win Rate | 16.28% | 15.79% | 14.29% | 14.29% | 13.89% | 13.51% | 13.33% | 13.04% | 12.90% | 12.82% |
Now, it seems like 29-year-olds have the best chance of winning the race! How interesting, but this makes the results inconclusive, great. In this second table, the top four win rates do not include the age range of 19 to 22 years old, quite conflicting I’d say. Moving on ig to the actual graphs I uploaded
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NOTES
- I recorded the individual ages of all team members, rather than just using team averages, so each individual person has their own data point. Also, returning racers are counted for each time they ran the race
- The age data reflects how old each racer was at the time of the START filming, not their current age. For example, Flight Time TAR15 had his 33rd birthday on Leg 8, but his TAR15 stats are counted under as a 32-year-old.
- Additionally, all ages were rounded down to whole numbers, as you would typically state them in a normal conversation e.g., '42' instead of '42 and a half' (duh)
Slide 1:
- I found the average age for all the people who finished the race in 1st place, 2nd place, 3rd place, and so on.
- There is a clear trend here: younger racers do better, with the average age of all winners being 29.92 years old.
Slide 2:
- I graphed each individual person’s age on the x-axis, then their respective finishing placement on the y-axis. Larger dots correspond to a greater frequency (for example, there are a lot of 26-year-olds who placed 9th).
- There is not a clear trend here. An r-squared value of 0.0258 is pathetic lmao (basically, this graph is kinda useless)
Slide 3:
- This a vertical bar chart of the average finishing placement of each age.
- The best average finishing placements are by ages 14, 16, 30, 68, and 36 years old. This is misleading because there has been only like one 14-year old, two 16-year-olds, and two 68-year-olds.
- The best average finishing placements by ages that have ten or more data points are ages 30, 26, 29, 35, and 46 years. uhhh cool.
- The worst average finishing placement are by ages 8, 11, 60, 70, and 71 years old
- The worst average finishing placements by ages that have ten or more data points are ages 49, 39, 41, 44, and 40. idk what you want to do with that information
Slide 4:
- This is a histogram of all the ages of all the racers. Each category’s size is five years. It follows a pretty even smooth curve skewed right.
- Ages 23 to 32 make up 48.9% of all racers. I wonder if that is the same percent amongst the people that have applied for the race.
Slide 5:
- Column chart of all the ages of all the racers.
- There is a CLEAR peak at 26 years old, making up 7.1% of all racers. The next three ages with the highest frequency of racers are 27, 29, and 28 years old.
Slide 6:
- Box-and-whisker plot of all the ages of all the racers. Outliers are not marked, but are included in the graph.
- Min = 8 years old, Q1 = 26 years old, Median = 31 years old, Q3 = 39 years old, Max = 71 years old. There are quite a few outliers using the outlier formula.
Slide 7:
- This is an extensive table of statistics for each age.
- Oldest Racer Records
- The oldest racer ever period is Jody TAR16 at 71 years old at the time of filming! She is followed closely by Mel TAR18 at 70 years old (he’s such an icon). Props to them for signing up to do the show at that age
- Don & Mary Jean TAR6 and Meredith & Gretchen TAR7 (we have a BAD elephant!) are the oldest teams, with both teams having an age average of 67.5
- Dave TAR24 is the oldest person to win the race at 58
- Kim & Penn TAR33 are the oldest team to win the race, with an average age of 46
- Teri & Ian TAR2 and Ken & Tina TAR13 are the oldest teams to reach the finale, with an average age of 50
- Donald TAR12 is the oldest person to reach the finale at 68
- Youngest Racer Records
- Youngest racer period is Austin Black TAR8 at 8 years old, followed closely by Carissa Gaghan TAR8 at 9 years old. They both were incoming 4th graders at the time of filming. Outside of TAR8, the youngest racers are Zac TAR19, Cole TAR28, Cameron TAR28, and Maya TAR36 all at 19 years old.
- Darius & Cameron TAR28 and Maya & Rohan TAR36 are the youngest teams to have run the race, with both teams having an average age of 20.5
- Tommy Linz TAR8 is the youngest to win at 19. Outside of TAR8, the youngest person to win is Starr TAR13 at 21.
- Nick & Starr TAR13 and the Linz Family TAR8 are the youngest teams to reach the finale, as well as the youngest teams to win the race, with an average age of 21.5
- The ages that have won the race the most are 29 (count=7 racers), 25, 22, 24, 26, and 30 years old.
- The ages that have reached the top three the most are 29 (count=18 racers), 30, 26, 27, 25 years old.
- The ages with the best top three RATE are 14, 20, 19, 50, 16, and 68 years old.
- The ages with the best top three RATE and have more than ten data points are 30 (43.59%), 29, 36, 35, and 46.
Slide 8:
- Season # is on the x-axis, Average Age is on the y-axis.
- TAR8 “Family Edition” had kids competing on the show, so that’s why it has the youngest average age at 29.40 years. TAR25, TAR29, and TAR17 closely follow it, all 29.something years too
- TAR37, the newest season, visibly has the oldest average age at 40.46 years! I think the show did that due to the aging of the show's middle-aged audience (mostly Gen X & Millennials), or it’s because 14 teams is a lot of people so they decided to cast more older people. TAR21, TAR15, TAR36, and TAR11 follow it, in that order.
- Despite TAR37 having the oldest average age, it’s kinda funny how the two youngest average age teams on that season placed first and second place lmaoo
Slide 9:
- Season # is on the x-axis, MEDIAN Age is on the y-axis
- Quite odd how the results change compared to the graph on the previous slide. Both graphs suggest that TAR is casting more older people recently. This post is already too long and this graph isn’t that useful so I’ll move on.
Slide 10:
- I calculated each team’s age GAP and plotted it here.
- Most teams have an age gap of just 0 to 3 years.
- There are two clusters on this graph: one cluster at an age gap of 0 to 10 years, and another cluster at an age gap of 25 to 38 years. This is because teams are either really close in age (e.g. friends, lovers) or teams are part of a parent/child duo (parents, grandparents, children).
- Largest age gap is Jody & Shannon TAR16 with a 49 year gap, followed closely by Nicholas & Donald TAR12 with a 45 year gap (props to them for making it so far).
- Smallest age gap would be any set of twins.
- The largest age gap of any team that is NOT a parent-child team is held by Tim & Rex TAR34 with a 19 year gap (I rly wish they lasted longer)
- Meanwhile the largest age gap for any romantic team is Ray & Deanna TAR7 (17 year gap)... hmmm such a lovely relationship they had huh
Slide 11
- I graphed each team’s age GAP on the x-axis, then their respective finishing placement on the y-axis. Larger dots correspond to a greater frequency (for example, there are a lot of teams with an age gap of 4 years and also placed 5th).
- There is not a clear trend here. An r-squared value of 0.0079 is even more pathetic (this graph is also useless)
TLDR (again): The best age to be to win The Amazing Race (U.S.) is about 29 years old, yay!
if you have any questions, comments, or concerns, lmk! what kind of statistics should i do next to waste my time?