Skully

Skully — CS2 Stats

76561199480199676[U:1:1519933948]Steam profile ↗✓ No bans

526Tracked matches41%Win rate2023Tracked since
CSDB Rating2.2 LearningPositional Player
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then — still 526 tracked matches. Play, then come back: the next observation lands here.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 54 days played since 8 Mar 2026. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 6,906 -2,456 8 Mar17 Jun · 11 days played
4,07510,117peak 10,1178 Mar17 Jun
10,117Peak Premier in tracked matches
54Days played since 2026-03-08

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim32
Positioning20
Utility2

0–100 skill scores via Leetify.

Recent form

COLD41509Last 10041%Win rateLLLLLLLWLL

Last 10 vs previous 10: −30pp win rate · −0.03 avg rating · −3.3pp headshot accuracy · +52ms reaction

Win rate down 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 05 · 0% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 10%
  • Avg reaction 722ms

Last 10

  • 19 · 10% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 12%
  • Avg reaction 731ms

Last 20

  • 5141 · 25% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 14%
  • Avg reaction 706ms

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 PlayerPositioning stands above the rest of this profile (+1.5 against its own average).

Aim3.2
Utility0.2
Positioning2.0
Opening Duels0.0
Clutch0.0

Limited utility dependence

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

iM

Plays most like iM 89% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; lower aim profile.

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

Areas to improve

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

Reaction time. 721ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim3.2
Positioning2.0
Utility0.2
Mechanics3.8
Opening Duels0.0
Win Impact2.1

Composite 2.2/10 (Learning), 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 rating-0.06+0.01
first ⅓ avg -0.07 → last ⅓ avg -0.06
Reaction time729ms−38ms
first ⅓ avg 766ms → last ⅓ avg 729ms
Headshot accuracy13.7%+0.0%
first ⅓ avg 13.7% → last ⅓ avg 13.7%

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

0.05Best match rating · 12–12 · cache, 7 May
33%Best headshot accuracy · 0–9 · inferno, 27 Jul
484msFastest reaction time · 7–13 · ancient, 27 Mar
13–2Biggest win · cache, 4 Jul

Across the last 100 tracked matches.

Highlights

5Longest win streak
L7Current streak
25In matches decided by ≤2 rounds
3Overtime games

Map breakdown

dust2Best map · 71% over 7ancientWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
cacheD2171433%-0.06
officeD1551033%-0.05
vertigoC135838%-0.05
anubisD112918%-0.05
trainC73443%-0.04
dust2S75271%-0.07
mirageS75271%-0.09
ancientD61517%-0.07
infernoA53260%-0.10
nuke31233%-0.09
overpass21150%-0.07
shelter110100%-0.06
alpine110100%-0.02
italy110100%-0.05

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

3Matches
33%Win rate
0.36Avg K/D
42.1ADR
42%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage250%0.458.5
Anubis10%0.173.0

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.

13.4%Headshot accuracy
30.4%Accuracy (enemy spotted)
31.9%Spray accuracy
66.9%Counter-strafing
9.2°Preaim
721msReaction time
16.8%T opening success
30.4%CT opening success
0.00Enemies flashed / flash
0.0%Flash assists
1.07HE damage / grenade
0.00Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 13.4357% — below the 15% mark we flag

    Aim Training
  2. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 720.9ms — above the 700ms mark we flag

    Aim Training
  3. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0 — below the 0.5 mark we flag

    Grenade Lineups
Spend your practice time on Ancient

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
cache10–13-0.090%29 Aug
cache8–13-0.1014%28 Aug
office4–13-0.089%15 Aug
train1–13-0.057%12 Aug
cache4–13-0.1120%7 Aug
ancient10–13-0.0220%2 Aug
cache2–13-0.1015%31 Jul
vertigo13–6-0.0613%30 Jul
vertigo10–13-0.0610%30 Jul
nuke5–9-0.1811%27 Jul
inferno0–9-0.1733%27 Jul
dust211–13-0.0316%27 Jul
anubis12–12-0.065%24 Jul
anubis8–13-0.0215%24 Jul
vertigo8–13-0.077%20 Jul
anubis13–9-0.029%20 Jul
office13–10-0.0519%15 Jul
shelter13–11-0.0613%11 Jul
office6–13-0.0519%10 Jul
office13–3-0.0316%9 Jul
cache13–2-0.0715%4 Jul
cache10–13-0.0526%3 Jul
cache13–5-0.0916%3 Jul
vertigo13–100.0014%30 Jun
vertigo13–5-0.0215%30 Jun
anubis2–13-0.0618%30 Jun
ancient2–13-0.055%30 Jun
cache13–70.0419%26 Jun
train13–10-0.0122%18 Jun
overpass4–13-0.092%17 Jun
train13–30.0313%17 Jun
train3–13-0.083%17 Jun
cache11–13-0.0513%16 Jun
ancient5–13-0.069%16 Jun
cache2–13-0.077%13 Jun
ancient7–13-0.0817%11 Jun
alpine13–4-0.0216%9 Jun
vertigo13–5-0.0014%9 Jun
train13–4-0.1019%9 Jun
italy13–6-0.0513%9 Jun
mirage5–13-0.124%7 Jun
vertigo9–13-0.0817%6 Jun
cache5–13-0.0717%6 Jun
vertigo13–8-0.0114%3 Jun
mirage15–15-0.0814%29 May
inferno16–13-0.0813%29 May
anubis12–12-0.0521%27 May
anubis12–12-0.0223%27 May
dust213–7-0.0621%22 May
mirage13–6-0.0727%22 May
office12–12-0.0712%20 May
cache13–4-0.1014%20 May
cache11–13-0.0711%20 May
office12–12-0.0419%13 May
office1–13-0.0629%13 May
office8–13-0.077%13 May
cache7–13-0.114%8 May
cache12–120.0516%7 May
cache13–9-0.079%7 May
inferno13–9-0.0719%3 May
dust213–10-0.0623%3 May
office2–9-0.0411%30 Apr
cache6–13-0.043%30 Apr
cache10–13-0.1018%30 Apr
cache13–5-0.0316%29 Apr
cache3–13-0.0423%29 Apr
cache13–9-0.0811%29 Apr
ancient13–4-0.0617%24 Apr
train9–13-0.0111%24 Apr
train8–13-0.0510%24 Apr
dust213–9-0.0616%22 Apr
nuke11–13-0.0913%17 Apr
dust213–2-0.073%17 Apr
office13–7-0.0910%15 Apr
office13–10-0.0415%14 Apr
vertigo11–13-0.0315%14 Apr
vertigo1–9-0.080%14 Apr
vertigo0–13-0.136%14 Apr
vertigo2–13-0.0819%9 Apr
vertigo7–13-0.0522%9 Apr
office12–12-0.0910%5 Apr
anubis13–5-0.0116%3 Apr
anubis3–13-0.1410%3 Apr
anubis7–13-0.029%2 Apr
ancient7–13-0.1311%27 Mar
inferno2–13-0.0930%27 Mar
overpass13–5-0.0623%27 Mar
nuke13–7-0.0125%27 Mar
anubis12–12-0.0622%19 Mar
office1–13-0.0313%19 Mar
anubis6–13-0.1115%18 Mar
office6–13-0.046%18 Mar
office13–9-0.0121%18 Mar
mirage13–10-0.0919%17 Mar
mirage13–10-0.1114%17 Mar
mirage13–11-0.0611%10 Mar
inferno16–12-0.0911%10 Mar
dust24–13-0.0913%9 Mar
mirage13–9-0.1213%9 Mar
dust213–4-0.100%8 Mar

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 →