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

Olympic Ski Jumping (Skiing)

Delegation

101 team lists ยท 574 player entries ยท avg team size 5.7

Read this sport as a comparison between raw coincidence and what team size alone predicts. Here, the real rate is -2.8 points below the birthday-paradox baseline.

Real team lists
1.0%
teams with shared birthdays
Why it matters: This is the headline rate, but it should never be read without team size.
Expected from size
3.8%
from avg team size
Why it matters: This is the fair baseline: what same-size random teams would do.
Gap from expected
-2.8 points
real โˆ’ expected
Why it matters: Negative means this sport is quieter than team size alone predicts.
Team lists
101
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 Ski Jumping (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, GER has the highest observed rate, with an average team size of 6.5.

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 (7.1 athletes), so their birthday-match rate naturally rises.

By country

Top 40 countries by team-list count.

CountryTeam listsAvg playersReal
NOR135.50.0%
USA125.60.0%
JPN96.00.0%
GER86.512.5%
FIN85.30.0%
AUT85.80.0%
POL75.10.0%
SLO76.60.0%
CZE55.40.0%
TCH45.00.0%
YUG35.00.0%
GDR35.30.0%
SWE35.00.0%
CAN25.50.0%
ITA26.50.0%
ROC28.00.0%
RUS25.50.0%
URS25.00.0%
FRG15.00.0%
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
Women70.0%6.1%-6.1 points
Men941.1%3.6%-2.5 points

Sample team lists

Largest teams in the dataset.

TeamSeasonPlayersRepeatsExpected chance
GER Ski Jumping (Skiing) (1994 Winter) ยท GER1994 Winter512.7%
JPN Ski Jumping (Skiing) (2018 Winter) ยท JPN2018 Winter909.5%
SLO Ski Jumping (Skiing) (2018 Winter) ยท SLO2018 Winter909.5%
GER Ski Jumping (Skiing) (2014 Winter) ยท GER2014 Winter909.5%
GER Ski Jumping (Skiing) (2018 Winter) ยท GER2018 Winter909.5%
GER Ski Jumping (Skiing) (2022 Winter) ยท GER2022 Winter909.5%
JPN Ski Jumping (Skiing) (2014 Winter) ยท JPN2014 Winter807.4%
SLO Ski Jumping (Skiing) (2014 Winter) ยท SLO2014 Winter807.4%
NOR Ski Jumping (Skiing) (2014 Winter) ยท NOR2014 Winter807.4%
ROC Ski Jumping (Skiing) (2018 Winter) ยท ROC2018 Winter807.4%
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.