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

Olympic Softball (Baseball/Softball)

Team

38 team lists ยท 568 player entries ยท avg team size 14.9

Read this sport as a comparison between raw coincidence and what team size alone predicts. Here, the real rate is +22.2 points above the birthday-paradox baseline.

Real team lists
47.4%
teams with shared birthdays
Why it matters: This is the headline rate, but it should never be read without team size.
Expected from size
25.1%
from avg team size
Why it matters: This is the fair baseline: what same-size random teams would do.
Gap from expected
+22.2 points
real โˆ’ expected
Why it matters: Positive means the sport has more birthday matches than size alone predicts.
Team lists
38
teams analysed
Why it matters: Small sample: treat the rate as a lead, not a verdict.
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 Softball (Baseball/Softball), 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 15.0.

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

By country

Top 40 countries by team-list count.

CountryTeam listsAvg playersReal
AUS515.060.0%
CAN514.860.0%
USA515.020.0%
JPN515.060.0%
CHN415.050.0%
ITA315.033.3%
TPE315.0100.0%
NED215.050.0%
GRE114.00.0%
CUB115.00.0%
NZL115.00.0%
MEX115.00.0%
PUR115.00.0%
VEN115.0100.0%
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
Women3847.4%25.1%+22.2 points

Sample team lists

Largest teams in the dataset.

TeamSeasonPlayersRepeatsExpected chance
NED Softball (Baseball/Softball) (1996 Summer) ยท NED1996 Summer15125.3%
USA Softball (Baseball/Softball) (1996 Summer) ยท USA1996 Summer15125.3%
AUS Softball (Baseball/Softball) (1996 Summer) ยท AUS1996 Summer15125.3%
AUS Softball (Baseball/Softball) (2000 Summer) ยท AUS2000 Summer15125.3%
TPE Softball (Baseball/Softball) (1996 Summer) ยท TPE1996 Summer15225.3%
CHN Softball (Baseball/Softball) (1996 Summer) ยท CHN1996 Summer15125.3%
JPN Softball (Baseball/Softball) (2004 Summer) ยท JPN2004 Summer15125.3%
TPE Softball (Baseball/Softball) (2004 Summer) ยท TPE2004 Summer15125.3%
ITA Softball (Baseball/Softball) (2000 Summer) ยท ITA2000 Summer15125.3%
CAN Softball (Baseball/Softball) (2004 Summer) ยท CAN2004 Summer15125.3%
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.