snorkle

snorkle — CS2 Stats

US76561198784892323[U:1:824626595]Steam profile ↗✓ No bans

181Tracked matches61%Win rate2026Tracked since
187Hours in CS28Hrs last 2 wks
CSDB Rating4.5 DevelopingPositional Player
Ladder ranks via Leetify

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches83——
Win rate52%——
K/D2.13——
Headshot %62%——

Measured 4 Sep 2026 → 3 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

Performance scores

Aim44
Positioning60
Utility16

0–100 skill scores via Leetify.

Recent form

HOT46–47–7Last 10046%Win rateWWWWWTWLWL

Last 10 vs previous 10: +20pp win rate · +0.05 avg rating · −2.1pp headshot accuracy · +10ms reaction

Win rate up 20pp 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

  • 5–0 · 100% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 11%
  • Avg reaction 619ms

Last 10

  • 7–2–1 · 70% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 13%
  • Avg reaction 626ms

Last 20

  • 12–6–2 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 14%
  • Avg reaction 621ms

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 (+2 against its own average).

Aim4.4
Utility1.6
Positioning6.0
Opening Duels4.5

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

donk

Plays most like donk 76% 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

Reaction time. 622ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 60% 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

Aim4.4
Positioning6.0
Utility1.6
Mechanics2.3
Opening Duels4.9
Win Impact8.6

Composite 4.5/10 (Developing), 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 rating0.02+0.03
first ⅓ avg -0.02 → last ⅓ avg 0.02
Reaction time613ms+65ms
first ⅓ avg 548ms → last ⅓ avg 613ms
Headshot accuracy13.3%+2.0%
first ⅓ avg 11.3% → last ⅓ avg 13.3%

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

0.22Best match rating · 13–0 · nuke, 30 Sept →
40%Best headshot accuracy · 13–4 · dust2, 9 Sept →
367msFastest reaction time · 5–13 · train, 10 Sept →
13–0Biggest win · nuke, 30 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W5Current streak
4–8In matches decided by ≤2 rounds

Map breakdown

nukeBest map · 70% over 10cacheWeakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
trainB2513–1252%-0.01
officeC218–1338%0.00
mirageB168–850%-0.04
dust2C135–838%-0.00
nukeS107–370%0.01
cacheD50–50%-0.05
ancient—40–40%-0.04
inferno—33–0100%-0.00
anubis—11–0100%0.04
italy—11–0100%0.02
overpass—10–10%-0.02

Across the last 100 tracked matches.

Lifetime stats

6,044Lifetime kills
1.01K/D · Top 50% of tracked players
322Matches
32.9%Match win rate
46.3%Headshot % · Top 50% of tracked players
0.0%Shot accuracy
350MVPs
102Hours (in match)
63Bombs planted
57Bombs defused

Most-used weapons

Lifetime map wins

734office
325nuke
250train
178dust2
111inferno
13italy
6vertigo

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.

13.8%Headshot accuracy
36.0%Accuracy (enemy spotted)
31.3%Spray accuracy
60.2%Counter-strafing
9.7°Preaim
622msReaction time
49.7%T opening success
49.6%CT opening success
0.26Enemies flashed / flash
4.0%Flash assists
2.15HE damage / grenade
2.29Flashes / 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 13.7807% — 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 0.26 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Cache

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

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
train13–3-0.0211%2 Oct →
nuke13–2-0.039%2 Oct →
train13–40.046%30 Sept →
nuke13–00.2215%30 Sept →
nuke9–00.0614%30 Sept →
mirage12–12-0.0110%30 Sept →
nuke13–30.0213%29 Sept →
dust26–130.0318%29 Sept →
dust213–50.0318%29 Sept →
mirage11–130.0018%29 Sept →
train8–1-0.0019%29 Sept →
cache11–13-0.0715%29 Sept →
office13–30.0510%28 Sept →
train10–13-0.058%28 Sept →
dust212–12-0.0124%28 Sept →
mirage13–4-0.0410%27 Sept →
nuke13–6-0.0421%27 Sept →
inferno13–30.0118%27 Sept →
dust27–13-0.0122%27 Sept →
train2–13-0.027%25 Sept →
mirage13–50.039%25 Sept →
mirage9–13-0.0817%25 Sept →
ancient3–13-0.0410%25 Sept →
dust210–20.1920%25 Sept →
office11–13-0.066%25 Sept →
train13–10-0.0213%22 Sept →
office13–100.0713%22 Sept →
inferno13–10-0.0214%22 Sept →
mirage5–130.0014%22 Sept →
dust210–130.0113%22 Sept →
train6–50.0111%21 Sept →
train13–80.129%21 Sept →
office9–130.116%21 Sept →
dust23–13-0.0211%21 Sept →
mirage9–13-0.078%21 Sept →
nuke13–5-0.013%21 Sept →
train4–130.004%21 Sept →
train9–13-0.058%21 Sept →
mirage13–110.0213%21 Sept →
anubis13–70.0410%19 Sept →
mirage13–4-0.0010%19 Sept →
dust29–13-0.049%19 Sept →
nuke6–130.019%19 Sept →
train2–13-0.0912%19 Sept →
ancient4–130.0129%19 Sept →
office3–13-0.0614%17 Sept →
train13–60.0112%17 Sept →
office10–13-0.038%17 Sept →
train7–130.0118%17 Sept →
mirage13–100.0113%17 Sept →
mirage11–13-0.1316%17 Sept →
mirage10–13-0.0712%16 Sept →
cache5–13-0.054%15 Sept →
dust24–13-0.0410%15 Sept →
mirage13–6-0.066%15 Sept →
mirage12–12-0.079%15 Sept →
mirage13–4-0.0413%15 Sept →
nuke7–13-0.0817%14 Sept →
dust213–8-0.046%14 Sept →
mirage13–0-0.065%14 Sept →
office13–60.0910%13 Sept →
train1–3-0.020%13 Sept →
office13–100.016%12 Sept →
italy13–90.0214%12 Sept →
office13–70.047%12 Sept →
train1–13-0.133%12 Sept →
ancient4–13-0.072%12 Sept →
train13–50.0114%11 Sept →
office7–13-0.0214%11 Sept →
office4–13-0.090%10 Sept →
ancient12–12-0.079%10 Sept →
inferno9–70.004%10 Sept →
train5–13-0.098%10 Sept →
office13–110.0417%10 Sept →
dust213–8-0.0513%9 Sept →
dust213–4-0.0040%9 Sept →
office2–13-0.060%9 Sept →
nuke13–9-0.083%9 Sept →
train13–10-0.0218%8 Sept →
train13–50.0411%8 Sept →
overpass11–13-0.0211%4 Sept →
office4–130.0213%4 Sept →
cache5–13-0.067%4 Sept →
train13–80.065%4 Sept →
office12–12-0.0510%3 Sept →
train8–13-0.019%3 Sept →
train13–40.1118%3 Sept →
office8–13-0.0124%3 Sept →
nuke12–120.0212%3 Sept →
office9–130.084%3 Sept →
train11–13-0.0314%2 Sept →
office13–10.047%2 Sept →
office13–10-0.036%31 Aug →
cache3–130.0011%31 Aug →
train13–20.0110%31 Aug →
train0–7-0.0720%31 Aug →
office11–13-0.0518%31 Aug →
cache0–5-0.040%31 Aug →
dust210–13-0.057%31 Aug →
office12–12-0.0818%30 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.