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dkidluke

Overview

10
Games logged
4 won, 6 lost.
40.0%
Personal win rate
−20.1 pts vs community (60.1%).
493
Days active
7.4 games / year on average.
Diana
Favorite investigator
Most-played character.
2
Longest win streak
Consecutive victories in a row.
2
Longest loss streak
Consecutive defeats in a row.

Career arc

Apr 29, 2015
first game
Sep 3, 2016
last game

Wins vs losses

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

N= 10

Best & worst Ancient One (n ≥ 5)

  • Best Azathoth — 60.0% (n=5)
  • Personal nemesis Azathoth — 60.0% (n=5)
  • Unique AOs faced 4

Net record

−2
4 victories minus 6 defeats. Below the 50/50 line by 10.0 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= 10

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
22%ile

Still learning — outperforms 22% 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.

2.9eff. AOs

Career is spread across many Ancient Ones. Top foe: Azathoth (50% of all games). 4 unique AOs ever faced.

All Ancient Ones faced

Click a column header to sort.

N= 10
Ancient One Games Wins Win %
Azathoth 5 3 60.0%
Shub-Niggurath 2 0 0.0%
Yog-Sothoth 2 1 50.0%
Cthulhu 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= 36

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= 29

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.

10.5eff. chars

Most-played: Diana (14% 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= 10

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 12h 25m spent summoning horrors. Averaging 124 min per game (−47 min vs the community's 171 min).

Games per year

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

N= 10

Records

Trophy case

Career bests and lifetime tallies.

0
Best score
1h 50m
Fastest victory
3h
Longest game
4
Biggest team
10
Monsters defeated
1
Investigators lost

How their games end

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

N= 10

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= 10