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Keith

Overview

23
Games logged
8 won, 15 lost.
34.8%
Personal win rate
−25.4 pts vs community (60.1%).
256
Days active
23.0 games / year on average.
"Skids"
Favorite investigator
Most-played character.
3
Longest win streak
Consecutive victories in a row.
5
Longest loss streak
Consecutive defeats in a row.

Career arc

Jan 13, 2016
first game
Sep 25, 2016
last game

Wins vs losses

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

N= 23

Best & worst Ancient One (n ≥ 5)

  • Best
  • Personal nemesis
  • Unique AOs faced 11

Net record

−7
8 victories minus 15 defeats. Below the 50/50 line by 15.2 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= 23

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= 20

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= 10

Where they sit among peers

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

N= 716
19%ile

Still learning — outperforms 19% 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.

9.3eff. AOs

Career is spread across many Ancient Ones. Top foe: Nephren-Ka (17% of all games). 11 unique AOs ever faced.

All Ancient Ones faced

Click a column header to sort.

N= 23
Ancient One Games Wins Win %
Nephren-Ka 4 2 50.0%
Yig 3 1 33.3%
Abhoth 3 3 100.0%
Yog-Sothoth 2 1 50.0%
Azathoth 2 1 50.0%
Rise of the Elder Things 2 0 0.0%
Hastur 2 0 0.0%
Syzygy 2 0 0.0%
Cthulhu 1 0 0.0%
Ithaqua 1 0 0.0%
Shub-Niggurath 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= 74

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= 86

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.

30.1eff. chars

Most-played: "Skids" (5% of all games). 35 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= 23

Expansions mixed per game

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

N= 23

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= 101

Time & Activity

Time at the table

Across 6 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 6
12h
Roughly 11h 50m spent summoning horrors. Averaging 118 min per game (−53 min vs the community's 171 min).

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= 23

Records

Trophy case

Career bests and lifetime tallies.

1h 50m
Fastest victory
2h 30m
Longest game
4
Biggest team
55
Monsters defeated
2
Investigators lost

How their games end

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

N= 23

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= 23