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Mesokhris

Overview

16
Games logged
11 won, 5 lost.
68.8%
Personal win rate
+8.6 pts vs community (60.1%).
383
Days active
15.2 games / year on average.
Charlie
Favorite investigator
Most-played character.
3
Longest win streak
Consecutive victories in a row.
2
Longest loss streak
Consecutive defeats in a row.

Career arc

Oct 24, 2021
first game
Nov 11, 2022
last game

Wins vs losses

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

N= 16

Best & worst Ancient One (n ≥ 5)

  • Best Yig — 40.0% (n=5)
  • Personal nemesis Yig — 40.0% (n=5)
  • Unique AOs faced 7

Net record

+6
11 victories minus 5 defeats. Ahead of the 50/50 line by 18.8 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= 5

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= 16

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= 14

Where they sit among peers

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

N= 716
68%ile

Above the median — outperforms 68% 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.

5.3eff. AOs

Career is spread across many Ancient Ones. Top foe: Yig (31% of all games). 7 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= 2
Ancient One Community loss % Personal wins Personal win %
Cthulhu 56% 1 / 2 50.0%

All Ancient Ones faced

Click a column header to sort.

N= 16
Ancient One Games Wins Win %
Yig 5 2 40.0%
Yog-Sothoth 3 2 66.7%
Azathoth 2 2 100.0%
Shub-Niggurath 2 2 100.0%
Cthulhu 2 1 50.0%
Ithaqua 1 1 100.0%
Nephren-Ka 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= 71

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= 68

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.

13.9eff. chars

Most-played: Charlie (12% of all games). 21 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= 9

Expansions mixed per game

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

N= 16

Time & Activity

Time at the table

Across 16 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 16
32h
Roughly 32h spent summoning horrors. Averaging 120 min per game (−51 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= 16

Quick wins or long grinds?

0min
Their victories average 120 min and defeats 120 min — they tend to close out the faster games.

Games per year

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

N= 16

Records

Trophy case

Career bests and lifetime tallies.

11
Best score
1h 30m
Fastest victory
2h 30m
Longest game
4
Biggest team
19
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= 16

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= 16