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

Olympic Snowboarding (Skiing)

Delegation

113 team lists ยท 1,240 player entries ยท avg team size 11.0

Read this sport as a comparison between raw coincidence and what team size alone predicts. Here, the real rate is +0.2 points above the birthday-paradox baseline.

Real team lists
15.9%
teams with shared birthdays
Why it matters: This is the headline rate, but it should never be read without team size.
Expected from size
15.7%
from avg team size
Why it matters: This is the fair baseline: what same-size random teams would do.
Gap from expected
+0.2 points
real โˆ’ expected
Why it matters: Positive means the sport has more birthday matches than size alone predicts.
Team lists
113
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 Snowboarding (Skiing), 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, SUI has the highest observed rate, with an average team size of 16.4.

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. Men have the larger average team size here (11.3 athletes), so their birthday-match rate naturally rises.

By country

Top 40 countries by team-list count.

CountryTeam listsAvg playersReal
CAN816.412.5%
AUT811.90.0%
GER810.312.5%
SUI816.437.5%
USA817.612.5%
JPN811.525.0%
ITA811.412.5%
FRA713.114.3%
FIN67.00.0%
AUS69.333.3%
NOR57.40.0%
CHN57.40.0%
SLO46.80.0%
RUS48.825.0%
POL45.80.0%
CZE35.70.0%
SWE311.333.3%
NZL25.00.0%
ROC214.5100.0%
GBR26.0100.0%
ESP15.00.0%
ARG15.00.0%
NED16.00.0%
KOR110.00.0%
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
Women4114.6%14.5%+0.2 points
Men7216.7%16.4%+0.3 points

Sample team lists

Largest teams in the dataset.

TeamSeasonPlayersRepeatsExpected chance
CAN Snowboarding (Skiing) (2014 Winter) ยท CAN2014 Winter24153.8%
SUI Snowboarding (Skiing) (2018 Winter) ยท SUI2018 Winter24153.8%
SUI Snowboarding (Skiing) (2014 Winter) ยท SUI2014 Winter23150.7%
JPN Snowboarding (Skiing) (2022 Winter) ยท JPN2022 Winter18134.7%
FRA Snowboarding (Skiing) (2010 Winter) ยท FRA2010 Winter17231.5%
ITA Snowboarding (Skiing) (2006 Winter) ยท ITA2006 Winter16128.4%
ROC Snowboarding (Skiing) (2018 Winter) ยท ROC2018 Winter16128.4%
SUI Snowboarding (Skiing) (2010 Winter) ยท SUI2010 Winter15125.3%
USA Snowboarding (Skiing) (2002 Winter) ยท USA2002 Winter14122.3%
GER Snowboarding (Skiing) (2018 Winter) ยท GER2018 Winter13119.4%
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.