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Moxie

Overview

12
Games logged
7 won, 5 lost.
58.3%
Personal win rate
−1.8 pts vs community (60.1%).
1,102
Days active
4.0 games / year on average.
Lily
Favorite investigator
Most-played character.
5
Longest win streak
Consecutive victories in a row.
4
Longest loss streak
Consecutive defeats in a row.

Career arc

Dec 29, 2013
first game
Jan 4, 2017
last game

Wins vs losses

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

N= 12

Best & worst Ancient One (n ≥ 5)

  • Best
  • Personal nemesis
  • Unique AOs faced 6

Net record

+2
7 victories minus 5 defeats. Ahead of the 50/50 line by 8.3 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= 12

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= 10

Where they sit among peers

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

N= 716
49%ile

Below the median — outperforms 49% 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.

4.8eff. AOs

Career is spread across many Ancient Ones. Top foe: Yog-Sothoth (33% of all games). 6 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= 1
Ancient One Community loss % Personal wins Personal win %
Cthulhu 56% 1 / 1 100.0%

All Ancient Ones faced

Click a column header to sort.

N= 12
Ancient One Games Wins Win %
Yog-Sothoth 4 3 75.0%
Azathoth 2 2 100.0%
Yig 2 0 0.0%
Shub-Niggurath 2 0 0.0%
Cthulhu 1 1 100.0%
Syzygy 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= 37

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= 27

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.

6.3eff. chars

Most-played: Lily (27% of all games). 11 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= 7

Expansions mixed per game

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

N= 12

Time & Activity

Time at the table

Across 9 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 9
14h
Roughly 13h 41m spent summoning horrors. Averaging 91 min per game (−80 min vs the community's 171 min).

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= 12

Games per year

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

N= 12

Records

Trophy case

Career bests and lifetime tallies.

1h 15m
Fastest victory
1h 50m
Longest game
4
Biggest team
5
Monsters defeated
3
Investigators lost

How their games end

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

N= 12

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= 12