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Berni643

Overview

10
Games logged
3 won, 7 lost.
30.0%
Personal win rate
−30.1 pts vs community (60.1%).
2,367
Days active
1.5 games / year on average.
Michael
Favorite investigator
Most-played character.
2
Longest win streak
Consecutive victories in a row.
4
Longest loss streak
Consecutive defeats in a row.

Career arc

Jul 7, 2016
first game
Dec 31, 2022
last game

Wins vs losses

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

N= 10

Best & worst Ancient One (n ≥ 5)

  • Best
  • Personal nemesis
  • Unique AOs faced 7

Net record

−4
3 victories minus 7 defeats. Below the 50/50 line by 20.0 pts.

Ancient Ones

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= 10

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= 6

Where they sit among peers

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

N= 716
11%ile

Still learning — outperforms 11% 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.

6.2eff. AOs

Career is spread across many Ancient Ones. Top foe: Azathoth (20% of all games). 7 unique AOs ever faced.

All Ancient Ones faced

Click a column header to sort.

N= 10
Ancient One Games Wins Win %
Azathoth 2 1 50.0%
Syzygy 2 0 0.0%
Shub-Niggurath 2 0 0.0%
Hastur 1 1 100.0%
Cthulhu 1 0 0.0%
Shudde M'ell 1 0 0.0%
Yog-Sothoth 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= 22

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.

12.1eff. chars

Most-played: Michael (14% of all games). 14 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= 7

Expansions mixed per game

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

N= 10

Win rate by expansion

Win rate in games featuring each box (95% band). Boxes played 5+ times only — this reflects which boxes they tend to win with, not the box's own difficulty.

N= 14

Time & Activity

Time at the table

Across 8 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 8
43h
Roughly 42h 40m spent summoning horrors. Averaging 320 min per game (+149 min vs the community's 171 min).

Games per year

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

N= 10

Records

Trophy case

Career bests and lifetime tallies.

2h 30m
Fastest victory
6h 30m
Longest game
5
Biggest team
25
Monsters defeated
0
Investigators lost

How their games end

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

N= 10

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= 10