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nhigui

Overview

31
Games logged
12 won, 19 lost.
38.7%
Personal win rate
−21.4 pts vs community (60.1%).
1,047
Days active
10.8 games / year on average.
Leo
Favorite investigator
Most-played character.
3
Longest win streak
Consecutive victories in a row.
7
Longest loss streak
Consecutive defeats in a row.

Career arc

Mar 2, 2016
first game
Jan 13, 2019
last game

Wins vs losses

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

N= 31

Best & worst Ancient One (n ≥ 5)

  • Best Azathoth — 38.5% (n=26)
  • Personal nemesis Azathoth — 38.5% (n=26)
  • Unique AOs faced 5

Net record

−7
12 victories minus 19 defeats. Below the 50/50 line by 11.3 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= 26

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= 31

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= 28

Where they sit among peers

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

N= 716
22%ile

Still learning — outperforms 22% 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.

1.4eff. AOs

Career is concentrated on a few favourites. Top foe: Azathoth (84% of all games). 5 unique AOs ever faced.

All Ancient Ones faced

Click a column header to sort.

N= 31
Ancient One Games Wins Win %
Azathoth 26 10 38.5%
Cthulhu 2 0 0.0%
Nyarlathotep 1 1 100.0%
Shub-Niggurath 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= 69

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= 64

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.

9.9eff. chars

Most-played: Leo (16% of all games). 14 unique investigators ever fielded.

Expansions

Expansions mixed per game

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

N= 31

Time & Activity

Time at the table

Across 31 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 31
45h
Roughly 45h 25m spent summoning horrors. Averaging 88 min per game (−83 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= 31

Quick wins or long grinds?

28min
Their victories average 105 min and defeats 77 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= 30

Games per year

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

N= 31

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= 31

When they play

Every logged game on a day × hour grid (UTC). Darker cells are busier slots. The strip on top totals games by hour of day; the strip on the right totals them by weekday. Hover any cell for win rate and average length.

N= 31

Records

Trophy case

Career bests and lifetime tallies.

6
Best score
35m
Fastest victory
6h
Longest game
5
Biggest team
9
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= 31

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= 31