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Humac

Overview

212
Games logged
163 won, 49 lost.
76.9%
Personal win rate
+16.8 pts vs community (60.1%).
4,183
Days active
18.5 games / year on average.
Jacqueline
Favorite investigator
Most-played character.
22
Longest win streak
Consecutive victories in a row.
3
Longest loss streak
Consecutive defeats in a row.

Career arc

Jan 10, 2014
first game
Jun 23, 2025
last game

Wins vs losses

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

N= 212

Best & worst Ancient One (n ≥ 5)

Net record

+114
163 victories minus 49 defeats. Ahead of the 50/50 line by 26.9 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= 208

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= 212

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= 212

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= 212

Where they sit among peers

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

N= 718
77%ile

Top-quartile player — outperforms 77% of contributors with 5+ games.

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.

14.0eff. AOs

Career is spread across many Ancient Ones. Top foe: Shub-Niggurath (11% 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= 20
Ancient One Community loss % Personal wins Personal win %
Cthulhu 55% 15 / 20 75.0%

All Ancient Ones faced

Click a column header to sort.

N= 212
Ancient One Games Wins Win %
Shub-Niggurath 23 22 95.7%
Cthulhu 20 15 75.0%
Yig 20 16 80.0%
Azathoth 19 14 73.7%
Abhoth 16 12 75.0%
Ithaqua 14 12 85.7%
Yog-Sothoth 14 10 71.4%
Hastur 12 9 75.0%
Nephren-Ka 12 7 58.3%
Syzygy 12 7 58.3%
Hypnos 11 8 72.7%
Shudde M'ell 10 8 80.0%
Nyarlathotep 9 6 66.7%
Rise of the Elder Things 9 9 100.0%
Atlach-Nacha 7 5 71.4%
Antediluvium 4 3 75.0%

Investigators

Most-played investigators

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

N= 624

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= 513

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.

42.6eff. chars

Most-played: Jacqueline (5% 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= 192

Expansions mixed per game

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

N= 212

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= 1,125

Time & Activity

Time at the table

Across 205 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 205
658h
Roughly 657h 55m spent summoning horrors. Averaging 193 min per game (+21 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= 205

Quick wins or long grinds?

2min
Their victories average 192 min and defeats 194 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= 208

Games per year

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

N= 212

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= 212

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= 212

Records

Trophy case

Career bests and lifetime tallies.

-22
Best score (lowest win)
1h
Fastest victory
7h
Longest game
8
Biggest team
351
Monsters defeated
58
Investigators lost

How their games end

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

N= 212

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= 212