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City 17

Overview

12
Games logged
5 won, 7 lost.
41.7%
Personal win rate
−18.5 pts vs community (60.1%).
54
Days active
12.0 games / year on average.
Norman
Favorite investigator
Most-played character.
2
Longest win streak
Consecutive victories in a row.
3
Longest loss streak
Consecutive defeats in a row.

Career arc

Jul 16, 2014
first game
Sep 8, 2014
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 Azathoth — 20.0% (n=5)
  • Personal nemesis Azathoth — 20.0% (n=5)
  • Unique AOs faced 5

Net record

−2
5 victories minus 7 defeats. Below the 50/50 line by 8.3 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= 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= 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
26%ile

Below the median — outperforms 26% 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.

3.6eff. AOs

Career is spread across many Ancient Ones. Top foe: Azathoth (42% of all games). 5 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= 3
Ancient One Community loss % Personal wins Personal win %
Cthulhu 56% 1 / 3 33.3%

All Ancient Ones faced

Click a column header to sort.

N= 12
Ancient One Games Wins Win %
Azathoth 5 1 20.0%
Cthulhu 3 1 33.3%
Yog-Sothoth 2 2 100.0%
Shub-Niggurath 1 1 100.0%
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= 63

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= 61

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: Norman (16% of all games). 12 unique investigators ever fielded.

Expansions

Expansions mixed per game

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

N= 12

Records

Trophy case

Career bests and lifetime tallies.

6
Biggest team
18
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