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IHRH

Overview

157
Games logged
112 won, 45 lost.
71.3%
Personal win rate
+11.2 pts vs community (60.1%).
1,053
Days active
54.4 games / year on average.
Akachi
Favorite investigator
Most-played character.
21
Longest win streak
Consecutive victories in a row.
5
Longest loss streak
Consecutive defeats in a row.

Career arc

Dec 28, 2017
first game
Nov 15, 2020
last game

Wins vs losses

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

N= 157

Best & worst Ancient One (n ≥ 5)

  • Best Yog-Sothoth — 90.9% (n=11)
  • Personal nemesis Cthulhu — 45.5% (n=11)
  • Unique AOs faced 16

Net record

+67
112 victories minus 45 defeats. Ahead of the 50/50 line by 21.3 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= 154

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= 157

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= 157

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= 157

Where they sit among peers

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

N= 718
70%ile

Above the median — outperforms 70% 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.

15.0eff. AOs

Career is spread across many Ancient Ones. Top foe: Shub-Niggurath (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= 11
Ancient One Community loss % Personal wins Personal win %
Cthulhu 55% 5 / 11 45.5%

All Ancient Ones faced

Click a column header to sort.

N= 157
Ancient One Games Wins Win %
Shub-Niggurath 15 12 80.0%
Azathoth 12 8 66.7%
Cthulhu 11 5 45.5%
Hastur 11 5 45.5%
Ithaqua 11 6 54.5%
Shudde M'ell 11 8 72.7%
Yog-Sothoth 11 10 90.9%
Atlach-Nacha 10 7 70.0%
Nephren-Ka 10 9 90.0%
Syzygy 10 8 80.0%
Abhoth 9 6 66.7%
Antediluvium 9 7 77.8%
Hypnos 9 8 88.9%
Yig 9 6 66.7%
Rise of the Elder Things 6 5 83.3%
Nyarlathotep 3 2 66.7%

Investigators

Most-played investigators

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

N= 375

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= 367

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.

45.4eff. chars

Most-played: Akachi (4% 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= 157

Expansions mixed per game

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

N= 157

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= 964

Time & Activity

Time at the table

Across 154 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 154
414h
Roughly 413h 55m spent summoning horrors. Averaging 161 min per game (−10 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= 154

Quick wins or long grinds?

7min
Their victories average 163 min and defeats 156 min — their wins tend to be the longer grinds.

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= 154

Games per year

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

N= 157

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= 157

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= 157

Records

Trophy case

Career bests and lifetime tallies.

-16
Best score (lowest win)
45m
Fastest victory
6h
Longest game
8
Biggest team
332
Monsters defeated
20
Investigators lost

How their games end

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

N= 157

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= 157