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krambis12

Overview

307
Games logged
161 won, 146 lost.
52.4%
Personal win rate
−7.7 pts vs community (60.1%).
3,867
Days active
29.0 games / year on average.
Zoey
Favorite investigator
Most-played character.
8
Longest win streak
Consecutive victories in a row.
8
Longest loss streak
Consecutive defeats in a row.

Career arc

Jan 20, 2016
first game
Aug 23, 2026
last game

Wins vs losses

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

N= 307

Best & worst Ancient One (n ≥ 5)

  • Best Hypnos — 80.0% (n=15)
  • Personal nemesis Cthulhu — 20.7% (n=29)
  • Unique AOs faced 16

Net record

+15
161 victories minus 146 defeats. Ahead of the 50/50 line by 2.4 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= 307

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= 307

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= 307

Personal vs community win rate

Each Ancient One the contributor has fought multiple times. Across the bottom: the community's win rate against that foe; up the side: this contributor's own. Color marks the gap — green where they beat the community against that foe, red where they trail it. Dot size shows how many games they've logged against it.

N= 307

Where they sit among peers

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

N= 718
42%ile

Below the median — outperforms 42% 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.

14.5eff. AOs

Career is spread across many Ancient Ones. Top foe: Yig (10% of all games). 16 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= 29
Ancient One Community loss % Personal wins Personal win %
Cthulhu 55% 6 / 29 20.7%

All Ancient Ones faced

Click a column header to sort.

N= 307
Ancient One Games Wins Win %
Yig 30 13 43.3%
Cthulhu 29 6 20.7%
Abhoth 27 20 74.1%
Hastur 27 14 51.8%
Shudde M'ell 21 8 38.1%
Yog-Sothoth 21 14 66.7%
Syzygy 19 7 36.8%
Shub-Niggurath 18 11 61.1%
Antediluvium 17 7 41.2%
Ithaqua 17 11 64.7%
Rise of the Elder Things 17 13 76.5%
Atlach-Nacha 15 5 33.3%
Hypnos 15 12 80.0%
Nephren-Ka 14 9 64.3%
Azathoth 11 6 54.5%
Nyarlathotep 9 5 55.6%

Investigators

Most-played investigators

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

N= 693

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= 722

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.

52.5eff. chars

Most-played: Zoey (3% of all games). 55 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= 301

Expansions mixed per game

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

N= 307

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= 2,274

Time & Activity

Time at the table

Across 301 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 301
845h
Roughly 845h 20m spent summoning horrors. Averaging 169 min per game (−3 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= 301

Quick wins or long grinds?

15min
Their victories average 161 min and defeats 176 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= 304

Games per year

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

N= 307

Win-rate trajectory

A rolling win rate across their career in game order — is their form trending up or down? The dashed line marks the community average.

N= 307

When they log games

Every logged game on a day × hour grid, by the time it was submitted (in the form's own timezone, not this contributor's). Darker cells are busier slots. The strip on top totals games by hour, the strip on the right by weekday. Hover any cell for win rate and average length.

N= 307

Records

Trophy case

Career bests and lifetime tallies.

-10
Best score (lowest win)
45m
Fastest victory
8h
Longest game
8
Biggest team
803
Monsters defeated
328
Investigators lost

How their games end

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

N= 307

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= 307