๐ŸŽ‚ Birthday Paradox ยท Sports
โ† All sports

Olympic Equestrian Eventing (Equestrian)

Delegation

52 team lists ยท 274 player entries ยท avg team size 5.3

Read this sport as a comparison between raw coincidence and what team size alone predicts. Here, the real rate is +2.7 points above the birthday-paradox baseline.

Real team lists
5.8%
teams with shared birthdays
Why it matters: This is the headline rate, but it should never be read without team size.
Expected from size
3.1%
from avg team size
Why it matters: This is the fair baseline: what same-size random teams would do.
Gap from expected
+2.7 points
real โˆ’ expected
Why it matters: Positive means the sport has more birthday matches than size alone predicts.
Team lists
52
teams analysed
Why it matters: Enough team lists for a useful sport-level read.
What to notice: The best question on a sport page is not "is the real rate high?" but "is it high after accounting for team size?" That is what the gap card is answering.

Country comparison

Countries with the most team lists for Olympic Equestrian Eventing (Equestrian), charted by the share of teams with at least one shared birthday.

What to compare: This view is best for spotting sample-shape differences inside a sport. Among the highest-sample countries, AUS has the highest observed rate, with an average team size of 5.4.

Gender split inside this sport

Real and expected rates for labelled team lists in this sport.

Why it matters: The gender gap is mostly a team-size story. Women have the larger average team size here (5.4 athletes), so their birthday-match rate naturally rises.

By country

Top 40 countries by team-list count.

CountryTeam listsAvg playersReal
AUS55.40.0%
GBR55.60.0%
GER55.40.0%
USA55.40.0%
FRA45.50.0%
IRL45.375.0%
NZL45.00.0%
BRA35.30.0%
BEL35.00.0%
CAN35.00.0%
SWE35.00.0%
ITA25.50.0%
JPN25.00.0%
ESP15.00.0%
AUT15.00.0%
HUN15.00.0%
POL15.00.0%
What to notice: Countries with larger average teams will naturally show more shared birthdays. The country list is most useful for finding which samples are driving this sport's overall rate.

By gender

Where the dataset records it.

GenderTeam listsRealExpectedGap
Women277.4%3.2%+4.2 points
Men254.0%2.9%+1.1 points

Sample team lists

Largest teams in the dataset.

TeamSeasonPlayersRepeatsExpected chance
IRL Equestrian Eventing (Equestrian) (2000 Summer) ยท IRL2000 Summer614.0%
IRL Equestrian Eventing (Equestrian) (2008 Summer) ยท IRL2008 Summer512.7%
IRL Equestrian Eventing (Equestrian) (2012 Summer) ยท IRL2012 Summer512.7%
GBR Equestrian Eventing (Equestrian) (1996 Summer) ยท GBR1996 Summer705.6%
AUS Equestrian Eventing (Equestrian) (1996 Summer) ยท AUS1996 Summer604.0%
USA Equestrian Eventing (Equestrian) (1996 Summer) ยท USA1996 Summer604.0%
GBR Equestrian Eventing (Equestrian) (2000 Summer) ยท GBR2000 Summer604.0%
FRA Equestrian Eventing (Equestrian) (1996 Summer) ยท FRA1996 Summer604.0%
ITA Equestrian Eventing (Equestrian) (1996 Summer) ยท ITA1996 Summer604.0%
USA Equestrian Eventing (Equestrian) (2000 Summer) ยท USA2000 Summer604.0%
What to notice: The sample team lists show the mechanics: once the player count gets large, the expected chance climbs quickly, and each repeat is another player landing on a date already present.