whodiss

whodiss — CS2 Stats

FI76561197977252761[U:1:16987033]Steam profile ↗✓ No bans

968Tracked matches37%Win rate2020Tracked since
CSDB Rating6.3 SolidPositional Player
FaceitLevel 7Top 42.3% of ranked FACEIT players
WingmanLegendary Eagle
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Oct 2026 (12 days ago). Ranks are recorded once per day this page is viewed.

+5Tracked matches · now 968
0.0ppWin rate · 37.0% → 37.0%

Rating over time

34Days played since 2026-04-09

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Share this profile

CSDB.GGwhodissFACEITLevel 7STANDINGTop 42.3% of rankedcsdb.gg/stats

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Performance scores

Aim87
Positioning65
Utility56

0–100 skill scores via Leetify.

Recent form

COLD44–47–9Last 10044%Win rateLLWLLWLLLL

Last 10 vs previous 10: −10pp win rate · −0.03 avg rating · −4.9pp headshot accuracy · −52ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 19%
  • Avg reaction 483ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 21%
  • Avg reaction 525ms

Last 20

  • 5–12–3 · 25% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 24%
  • Avg reaction 551ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+0.9 against its own average).

Aim8.7
Utility5.6
Positioning6.5
Opening Duels4.6

Sharp aimer

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

b1t

Plays most like b1t 96% playstyle similarity

Most alike: opening-duel success, utility contribution.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Strengths

Aim. Aim score of 87 — the mechanical foundation is a clear strength.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim8.7
Positioning6.5
Utility5.6
Mechanics6.7
Opening Duels5.2
Win Impact0.7

Composite 6.3/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.04+0.02
first ⅓ avg 0.02 → last ⅓ avg 0.04
Reaction time549ms−19ms
first ⅓ avg 568ms → last ⅓ avg 549ms
Headshot accuracy23.7%+2.8%
first ⅓ avg 20.9% → last ⅓ avg 23.7%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.21Best match rating · 13–0 · cache, 13 Sept →
58%Best headshot accuracy · 13–0 · cache, 13 Sept →
375msFastest reaction time · 4–13 · anubis, 24 Oct →
13–0Biggest win · cache, 13 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L2Current streak
8–5In matches decided by ≤2 rounds

Map breakdown

cacheBest map · 56% over 18infernoWeakest map · 26% over 19
MapGradePlayedRecordWin rateAvg rating
infernoD195–1426%0.03
cacheA1810–856%0.05
nukeC156–940%0.04
dust2B105–550%0.03
trainC104–640%0.02
overpassA95–456%-0.00
ancientC83–538%0.01
anubis—42–250%-0.00
vertigo—42–250%0.03
mirage—32–167%-0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (26% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

23Matches
39%Win rate
0.89Avg K/D
—ADR
41%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
3Longest win streak

Recent Faceit resultsWWLLL

MapMatchesWin rateAvg K/DAvg kills
Inferno250%1.1620.0
Anubis1100%2.8620.0
Overpass10%0.8917.0
Mirage10%0.6215.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

23.6%Headshot accuracy
38.0%Accuracy (enemy spotted)
41.4%Spray accuracy
80.3%Counter-strafing
8.7°Preaim
542msReaction time
47.9%T opening success
53.8%CT opening success
0.61Enemies flashed / flash
3.7%Flash assists
11.25HE damage / grenade
10.32Flashes / match

Recommended for you

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

26% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient2–13-0.0121%30 Oct →
dust210–130.0511%30 Oct →
train13–11-0.0312%30 Oct →
cache3–130.0125%24 Oct →
anubis4–13-0.0125%24 Oct →
anubis13–7-0.0323%22 Sept →
cache10–130.0324%22 Sept →
dust27–130.0126%22 Sept →
vertigo7–130.0522%13 Sept →
dust22–13-0.0423%13 Sept →
cache13–00.2158%13 Sept →
train12–120.0622%13 Sept →
nuke1–13-0.0144%13 Sept →
inferno9–13-0.093%13 Sept →
cache11–60.0324%21 Aug →
overpass12–12-0.0231%18 Aug →
inferno12–120.1419%16 Aug →
cache11–130.0628%16 Aug →
train13–00.0323%9 Aug →
ancient1–13-0.0411%9 Aug →
nuke6–130.0221%17 Jul →
anubis5–130.0419%17 Jul →
ancient13–110.0733%17 Jul →
inferno10–130.0623%15 Jul →
vertigo7–130.0729%13 Jul →
inferno11–130.1028%29 Jun →
cache13–50.0323%29 Jun →
overpass13–40.1022%29 Jun →
inferno8–80.0020%29 Jun →
overpass9–50.0721%29 Jun →
nuke9–40.1118%29 Jun →
inferno8–80.0533%29 Jun →
inferno9–50.1216%29 Jun →
vertigo13–10-0.0327%26 Jun →
inferno13–8-0.0323%24 Jun →
ancient5–130.0233%24 Jun →
train9–130.0545%4 Jun →
cache13–40.0317%4 Jun →
inferno11–130.0424%19 May →
cache7–13-0.0332%19 May →
nuke12–12-0.0327%18 May →
cache13–80.1428%18 May →
inferno13–90.0230%17 May →
dust213–60.0323%17 May →
cache13–70.0827%17 May →
nuke1–13-0.0214%13 May →
inferno7–130.109%13 May →
cache7–13-0.0221%13 May →
inferno3–130.0316%9 May →
cache4–13-0.0517%8 May →
nuke9–130.0018%8 May →
cache11–130.0731%8 May →
nuke3–00.2157%8 May →
dust213–40.1422%8 May →
train12–12-0.0015%8 May →
inferno7–130.0328%8 May →
cache13–90.0421%7 May →
ancient13–80.0311%6 May →
train9–1-0.020%6 May →
nuke9–40.1323%6 May →
inferno5–9-0.0226%6 May →
cache13–70.0732%2 May →
vertigo13–40.0122%2 May →
overpass5–8-0.0922%2 May →
cache13–60.1126%2 May →
nuke8–130.0554%2 May →
dust21–13-0.0915%2 May →
cache13–110.0828%2 May →
nuke0–9-0.2114%2 May →
cache11–130.0123%29 Apr →
overpass13–110.0112%28 Apr →
inferno3–13-0.0015%28 Apr →
train12–12-0.0020%28 Apr →
dust213–60.0839%28 Apr →
ancient12–120.0111%26 Apr →
train4–130.0136%26 Apr →
overpass13–11-0.009%26 Apr →
anubis13–100.0118%26 Apr →
train13–30.0517%26 Apr →
dust213–40.0224%25 Apr →
inferno9–5-0.0316%25 Apr →
nuke9–70.0713%25 Apr →
overpass6–9-0.0811%25 Apr →
inferno5–130.0123%21 Apr →
overpass2–8-0.060%21 Apr →
nuke13–90.0827%21 Apr →
dust213–90.0733%20 Apr →
inferno8–13-0.0038%20 Apr →
overpass10–130.0728%19 Apr →
ancient13–110.0219%19 Apr →
nuke9–130.0030%19 Apr →
nuke13–60.1523%12 Apr →
mirage8–13-0.0015%12 Apr →
dust25–130.0425%11 Apr →
mirage13–90.0122%11 Apr →
ancient5–13-0.0024%11 Apr →
mirage13–11-0.0119%9 Apr →
inferno13–70.0110%9 Apr →
train8–130.0231%9 Apr →
nuke8–130.0819%9 Apr →

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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