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El Taquito Bandito

Overview

22
Games logged
8 won, 14 lost.
36.4%
Personal win rate
−23.8 pts vs community (60.1%).
2,203
Days active
3.6 games / year on average.
Diana
Favorite investigator
Most-played character.
3
Longest win streak
Consecutive victories in a row.
7
Longest loss streak
Consecutive defeats in a row.

Career arc

Jul 2, 2015
first game
Jul 12, 2021
last game

Wins vs losses

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

N= 22

Best & worst Ancient One (n ≥ 5)

  • Best
  • Personal nemesis
  • Unique AOs faced 13

Net record

−6
8 victories minus 14 defeats. Below the 50/50 line by 13.6 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= 22

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

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.

11.0eff. AOs

Career is spread across many Ancient Ones. Top foe: Azathoth (14% of all games). 13 unique AOs ever faced.

All Ancient Ones faced

Click a column header to sort.

N= 22
Ancient One Games Wins Win %
Azathoth 3 2 66.7%
Yig 3 1 33.3%
Abhoth 2 1 50.0%
Ithaqua 2 1 50.0%
Cthulhu 2 0 0.0%
Shub-Niggurath 2 0 0.0%
Rise of the Elder Things 2 2 100.0%
Hastur 1 0 0.0%
Antediluvium 1 1 100.0%
Nephren-Ka 1 0 0.0%
Shudde M'ell 1 0 0.0%
Syzygy 1 0 0.0%
Yog-Sothoth 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= 55

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= 64

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.

31.1eff. chars

Most-played: Diana (5% of all games). 40 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= 22

Expansions mixed per game

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

N= 22

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= 84

Time & Activity

Time at the table

Across 22 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 22
44h
Roughly 44h 5m spent summoning horrors. Averaging 120 min per game (−51 min vs the community's 171 min).

Game-length distribution

How long this contributor's games run, in minutes. The visible range clips a few long outliers.

N= 22

Quick wins or long grinds?

31min
Their victories average 101 min and defeats 131 min — they tend to close out the faster games.

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= 22

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= 22

Records

Trophy case

Career bests and lifetime tallies.

11
Best score
50m
Fastest victory
4h 30m
Longest game
8
Biggest team
38
Monsters defeated
8
Investigators lost

How their games end

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

N= 22

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= 22