← All contributors

pajavasara

Overview

19
Games logged
7 won, 12 lost.
36.8%
Personal win rate
−23.3 pts vs community (60.1%).
848
Days active
8.2 games / year on average.
Charlie
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

Feb 11, 2014
first game
Jun 8, 2016
last game

Wins vs losses

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

N= 19

Best & worst Ancient One (n ≥ 5)

  • Best Cthulhu — 0.0% (n=5)
  • Personal nemesis Cthulhu — 0.0% (n=5)
  • Unique AOs faced 7

Net record

−5
7 victories minus 12 defeats. Below the 50/50 line by 13.2 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= 19

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= 16

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= 16

Where they sit among peers

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

N= 716
20%ile

Still learning — outperforms 20% 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.

5.2eff. AOs

Career is spread across many Ancient Ones. Top foe: Cthulhu (26% of all games). 7 unique AOs ever faced.

All Ancient Ones faced

Click a column header to sort.

N= 19
Ancient One Games Wins Win %
Cthulhu 5 0 0.0%
Azathoth 4 1 25.0%
Shub-Niggurath 4 3 75.0%
Yog-Sothoth 3 2 66.7%
Abhoth 1 0 0.0%
Rise of the Elder Things 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= 82

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= 78

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.

18.6eff. chars

Most-played: Charlie (8% of all games). 31 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= 11

Expansions mixed per game

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

N= 19

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= 27

Time & Activity

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= 19

Games per year

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

N= 19

Records

Trophy case

Career bests and lifetime tallies.

9
Best score
4
Biggest team
34
Monsters defeated
7
Investigators lost

How their games end

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

N= 19

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= 19