← All contributors

Caoimhin

Overview

15
Games logged
9 won, 6 lost.
60.0%
Personal win rate
−0.1 pts vs community (60.1%).
1,169
Days active
4.7 games / year on average.
Silas
Favorite investigator
Most-played character.
2
Longest win streak
Consecutive victories in a row.
2
Longest loss streak
Consecutive defeats in a row.

Career arc

Feb 9, 2014
first game
Apr 23, 2017
last game

Wins vs losses

A quick visual tally of this contributor's career so far.

N= 15

Best & worst Ancient One (n ≥ 5)

  • Best Cthulhu — 40.0% (n=5)
  • Personal nemesis Cthulhu — 40.0% (n=5)
  • Unique AOs faced 6

Net record

+3
9 victories minus 6 defeats. Ahead of the 50/50 line by 10.0 pts.

Ancient Ones

Above or below the curve

For each Ancient One this contributor has faced at least 5 times, the gap between their personal win rate and how the community does against the same foe. Green bars = they beat the community average; red bars = they trail it.

N= 5

Most-faced Ancient Ones

Where this contributor spends their time, split into wins and losses. Bar length is total games against each foe; the green share is how often they won. Sorted by games played.

N= 15

Win rate with confidence range

Same per-AO win rate, but with a 95% confidence band based on sample size. Wide bars = few games (treat with caution). Narrow bars = many games. Only AOs with 2+ games shown.

N= 13

Where they sit among peers

Rank against every other contributor with at least 5 games logged. Higher is better.

N= 716
50%ile

Above the median — outperforms 50% of the cohort.

Repertoire breadth

An effective count of how many Ancient Ones make up this contributor's career — accounts for how lopsided their distribution is. Close to the unique-AO count = broad variety. Close to 1 = one or two favourites dominate.

4.4eff. AOs

Career is spread across many Ancient Ones. Top foe: Cthulhu (33% of all games). 6 unique AOs ever faced.

Toughest AOs they've beaten

Ancient Ones where the community loses at least 55% of the time — and this contributor has carved out at least one win.

N= 5
Ancient One Community loss % Personal wins Personal win %
Cthulhu 56% 2 / 5 40.0%

All Ancient Ones faced

Click a column header to sort.

N= 15
Ancient One Games Wins Win %
Cthulhu 5 2 40.0%
Yog-Sothoth 4 3 75.0%
Azathoth 2 2 100.0%
Yig 2 1 50.0%
Shub-Niggurath 1 0 0.0%
Hypnos 1 1 100.0%

Investigators

Most-played investigators

Where this contributor spends their time on the roster. Sorted by total games with each character.

N= 63

Win rate by investigator

Per-character win rate with a 95% confidence band. Only investigators played 3+ times appear; wide bars mean a small sample.

N= 58

Roster breadth

An effective count of how many investigators make up this contributor's career — it accounts for how lopsided their picks are. Close to the unique count means wide variety; close to 1 means a couple of mains dominate.

13.1eff. chars

Most-played: Diana (11% of all games). 18 unique investigators ever fielded.

Expansions

Boxes in play

How often each expansion is on the table in this contributor's games. A single game usually mixes several boxes, so the totals overlap.

N= 10

Expansions mixed per game

How many expansion boxes this contributor typically combines in a single game.

N= 15

Time & Activity

Time at the table

Across 10 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 10
19h
Roughly 19h spent summoning horrors. Averaging 114 min per game (−57 min vs the community's 171 min).

Game-length distribution

How long this contributor's games run, in minutes. The visible range clips a few long outliers.

N= 10

Quick wins or long grinds?

9min
Their victories average 111 min and defeats 120 min — they tend to close out the faster games.

Win rate by team size

Does this contributor do better solo or in a full party? Win rate against the number of investigators at the table, with a 95% confidence band. Only team sizes with 3+ games shown.

N= 15

Games per year

This contributor's logged games by calendar year — the seasons when they were most active.

N= 15

Records

Trophy case

Career bests and lifetime tallies.

8
Best score
30m
Fastest victory
3h
Longest game
4
Biggest team
15
Monsters defeated
5
Investigators lost

How their games end

The split of victory types (green) and defeat causes (red) across this contributor's games.

N= 15

Outcome mix vs community

For each way a game can end, the gap between this contributor's share and the community's. Bars to the right = it happens to them more often than the average player.

N= 15