snuck

snuck — CS2 Stats

76561199232307444[U:1:1272041716]Steam profile ↗✓ No bans

38Tracked matches29%Win rate2026Tracked since
280Hours in CS1Hrs last 2 wks
CSDB Rating3.6 LearningPositional Player
WingmanSilver IV
Ladder ranks via Leetify

Performance scores

Aim53
Positioning56
Utility12

0–100 skill scores via Leetify.

Recent form

STEADY13–17–4Last 3438%Win rateLTWWLWLLLW

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · −0.6pp headshot accuracy · +33ms reaction

Win rate 0pp 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

  • 2–2–1 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 9%
  • Avg reaction 534ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 10%
  • Avg reaction 573ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 10%
  • Avg reaction 556ms

Newest first, from the last 34 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 (+3.2 against its own average).

Aim5.3
Utility1.2
Positioning5.6
Opening Duels0.5

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

jL

Plays most like jL 74% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower opening-duel success; lower 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

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. 557ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% 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

Aim5.3
Positioning5.6
Utility1.2
Mechanics3.7
Opening Duels1.1
Win Impact0.0

Composite 3.6/10 (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 rating0.01+0.04
first ⅓ avg -0.03 → last ⅓ avg 0.01
Reaction time579ms+35ms
first ⅓ avg 544ms → last ⅓ avg 579ms
Headshot accuracy10.0%+1.0%
first ⅓ avg 9.0% → last ⅓ avg 10.0%

Rolling 5-match average across the last 34 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.24Best match rating · 9–1 · nuke, 31 Jul →
23%Best headshot accuracy · 12–12 · inferno, 22 Apr →
406msFastest reaction time · 3–13 · anubis, 16 Sept →
13–2Biggest win · mirage, 1 Jul →

Across the last 34 tracked matches.

Highlights

2Longest win streak

Map breakdown

nukeBest map · 40% over 5infernoWeakest map · 37% over 19
MapGradePlayedRecordWin rateAvg rating
infernoC197–1237%0.00
nukeC52–340%0.02
mirage—31–233%-0.01
dust2—31–233%0.05
anubis—21–150%-0.04
cache—11–0100%0.05
vertigo—10–10%0.01

Across the last 34 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (37% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

3,687Lifetime kills
1.09K/D · Top 50% of tracked players
256Matches
41.0%Match win rate
36.2%Headshot %
3.1%Shot accuracy
667MVPs
61Hours (in match)
133Bombs planted
46Bombs defused

Most-used weapons

Lifetime map wins

1,032inferno
153dust2
87nuke
42vertigo
19ar_shoots
14lake
7train
7safehouse

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

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

10.4%Headshot accuracy
34.3%Accuracy (enemy spotted)
37.3%Spray accuracy
66.4%Counter-strafing
9.4°Preaim
557msReaction time
37.6%T opening success
31.2%CT opening success
0.24Enemies flashed / flash
4.6%Flash assists
4.26HE damage / grenade
0.53Flashes / 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 10.4163% — below the 15% mark we flag

    Aim Training →
  2. 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 0.2442 — below the 0.5 mark we flag

    Grenade Lineups →
  3. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 37.5641% — below the 40% mark we flag

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.

37% 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
inferno5–13-0.107%25 Oct →
inferno8–8-0.054%7 Oct →
inferno9–20.218%7 Oct →
inferno9–20.0214%7 Oct →
inferno6–9-0.0311%7 Oct →
inferno9–60.064%7 Oct →
mirage4–13-0.0713%29 Sept →
mirage6–13-0.108%29 Sept →
dust210–130.0318%25 Sept →
dust210–00.1412%24 Sept →
cache13–50.0512%21 Sept →
dust29–13-0.0214%16 Sept →
anubis3–13-0.0114%16 Sept →
inferno3–130.028%18 Aug →
inferno3–13-0.030%18 Aug →
nuke13–100.038%17 Aug →
nuke5–130.016%17 Aug →
inferno9–50.0316%3 Aug →
inferno9–40.1117%3 Aug →
vertigo8–80.0110%3 Aug →
inferno7–90.0414%3 Aug →
nuke4–9-0.0210%31 Jul →
nuke9–10.2416%31 Jul →
anubis13–6-0.064%2 Jul →
inferno11–130.007%2 Jul →
inferno1–13-0.022%1 Jul →
mirage13–20.1310%1 Jul →
nuke5–9-0.140%3 Jun →
inferno6–9-0.129%3 Jun →
inferno9–20.0813%3 Jun →
inferno12–120.0723%22 Apr →
inferno4–5-0.157%22 Apr →
inferno2–13-0.056%20 Apr →
inferno12–12-0.0217%20 Apr →

Match data via Leetify.

Recent teammates

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

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