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Mash

Overview

11
Games logged
3 won, 8 lost.
27.3%
Personal win rate
−32.9 pts vs community (60.1%).
99
Days active
11.0 games / year on average.
Silas
Favorite investigator
Most-played character.
3
Longest win streak
Consecutive victories in a row.
8
Longest loss streak
Consecutive defeats in a row.

Career arc

May 17, 2014
first game
Aug 24, 2014
last game

Wins vs losses

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

N= 11

Best & worst Ancient One (n ≥ 5)

  • Best
  • Personal nemesis
  • Unique AOs faced 5

Net record

−5
3 victories minus 8 defeats. Below the 50/50 line by 22.7 pts.

Ancient Ones

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= 11

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= 9

Where they sit among peers

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

N= 716
9%ile

Still learning — outperforms 9% 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.

3.9eff. AOs

Career is spread across many Ancient Ones. Top foe: Yog-Sothoth (36% of all games). 5 unique AOs ever faced.

All Ancient Ones faced

Click a column header to sort.

N= 11
Ancient One Games Wins Win %
Yog-Sothoth 4 2 50.0%
Shub-Niggurath 3 1 33.3%
Azathoth 2 0 0.0%
Cthulhu 1 0 0.0%
Yig 1 0 0.0%

Investigators

Most-played investigators

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

N= 32

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= 18

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.

9.3eff. chars

Most-played: Akachi (16% of all games). 11 unique investigators ever fielded.

Expansions

Expansions mixed per game

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

N= 11

Time & Activity

Time at the table

Across 11 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 11
21h
Roughly 21h spent summoning horrors. Averaging 115 min per game (−57 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= 11

Quick wins or long grinds?

21min
Their victories average 130 min and defeats 109 min — their wins tend to be the longer grinds.

Records

Trophy case

Career bests and lifetime tallies.

9
Best score
1h 30m
Fastest victory
3h
Longest game
4
Biggest team
10
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= 11

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= 11