Snickarn

Snickarn — CS2 Stats

76561197961218067[U:1:952339]Steam profile ↗✓ No bans

707Tracked matches53%Win rate2021Tracked since
CSDB Rating4.1 DevelopingAll-Rounder
Premier CS Rating14,704Blue band · top ~30% of ranked players (population est.)
FaceitLevel 5Top 67.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 14 Nov 2024 (700 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 14,704 -2,365 3 Mar – 14 Nov · 33 days played
12,55517,692peak 17,6923 Mar14 Nov
18,176Peak Premier in tracked matches
41Days played since 2024-03-03

Premier CS Rating

  • 2,988 below peak (17,692)
  • +2,149 over 30 days · improving
  • Next: Purple band at 15,000 — 296 to go
  • Reached: Purple band · Blue band · Light Blue band

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

Share this profile

CSDB.GGSnickarnFACEITLevel 5STANDINGTop 67.6% of rankedPREMIER14,704 · Blue bandcsdb.gg/stats

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Performance scores

Aim42
Positioning39
Utility40

0–100 skill scores via Leetify.

Recent form

STEADY52–46–2Last 10052%Win rateLLWWWLLLLW

Last 10 vs previous 10: −40pp win rate · +0.02 avg rating · −1.3pp headshot accuracy · −34ms reaction

Win rate down 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 541ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 550ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 14%
  • Avg reaction 567ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim4.2
Utility4.0
Positioning3.9
Opening Duels2.4
Clutch4.2

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 81% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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. 578ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

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

Aim4.2
Positioning3.9
Utility4.0
Mechanics6.2
Opening Duels1.6
Win Impact6.1

Composite 4.1/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02+0.01
first ⅓ avg -0.03 → last ⅓ avg -0.02
Reaction time582ms−11ms
first ⅓ avg 593ms → last ⅓ avg 582ms
Headshot accuracy15.6%+0.1%
first ⅓ avg 15.5% → last ⅓ avg 15.6%

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

0.14Best match rating · 13–3 · dust2, 2 May →
30%Best headshot accuracy · 13–10 · dust2, 21 Aug →
391msFastest reaction time · 4–13 · dust2, 6 May →
13–1Biggest win · anubis, 23 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L2Current streak
7–8In matches decided by ≤2 rounds
11Overtime games

Map breakdown

vertigoBest map · 65% over 20infernoWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
ancientB2512–1348%-0.02
vertigoS2013–765%-0.02
nukeA1811–761%-0.01
anubisA138–562%-0.01
infernoD81–713%-0.02
cacheA53–260%-0.05
overpass—40–40%-0.07
dust2—32–167%0.01
mirage—31–233%-0.03
basalt—11–0100%-0.08

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

88Matches
48%Win rate
0.89Avg K/D
66.5ADR
39%Headshot %

Clutches & streaks

41%1v1 clutch win
10%1v2 clutch win
6Longest win streak

Recent Faceit resultsWLWWL

MapMatchesWin rateAvg K/DAvg kills
Nuke1450%0.7512.1
Ancient1242%0.8212.8
Vertigo1258%1.0314.3
Cache838%0.5010.6
Anubis771%0.9714.3
Dust2633%0.5810.8
Inferno540%1.0015.6

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.

14.8%Headshot accuracy
28.6%Accuracy (enemy spotted)
26.3%Spray accuracy
78.1%Counter-strafing
11.5°Preaim
578msReaction time
38.5%T opening success
34.2%CT opening success
0.53Enemies flashed / flash
3.2%Flash assists
13.12HE damage / grenade
3.39Flashes / 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 14.7689% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.3941 — below the 4 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 38.4704% — 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.

13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno8–13-0.0415%6 Sept →
nuke11–13-0.0617%5 Sept →
cache13–8-0.0116%5 Sept →
ancient13–11-0.028%5 Sept →
nuke13–70.0210%1 Sept →
ancient9–13-0.037%30 Aug →
cache13–16-0.049%30 Aug →
cache10–13-0.0616%29 Aug →
vertigo8–130.0114%23 Aug →
anubis13–10.0520%23 Aug →
cache13–9-0.129%23 Aug →
cache19–17-0.0111%21 Aug →
nuke13–6-0.0418%21 Aug →
dust213–10-0.0430%21 Aug →
ancient13–7-0.049%21 Aug →
ancient9–13-0.035%16 Aug →
basalt13–3-0.0818%14 Nov →
inferno13–16-0.0312%14 Nov →
nuke13–1-0.0214%14 Nov →
nuke13–20.0118%2 Nov →
vertigo16–120.0418%2 Nov →
anubis13–40.0716%2 Nov →
mirage13–40.0617%1 Nov →
anubis10–13-0.0516%1 Nov →
nuke11–13-0.0515%31 Oct →
vertigo7–13-0.0619%28 Oct →
ancient4–13-0.1320%28 Oct →
ancient13–70.0024%27 Oct →
mirage9–13-0.0517%24 Oct →
vertigo6–13-0.0416%24 Oct →
vertigo13–6-0.0127%24 Oct →
ancient13–80.0420%24 Oct →
vertigo13–16-0.0214%21 Oct →
nuke11–13-0.0211%18 Oct →
ancient13–80.0618%18 Oct →
anubis7–13-0.0515%18 Oct →
nuke12–160.0613%18 Oct →
ancient13–80.1018%14 Oct →
inferno11–130.0321%14 Oct →
ancient15–150.0618%13 Oct →
ancient13–16-0.0514%1 Oct →
vertigo10–0-0.0820%1 Oct →
inferno7–13-0.0216%26 Sept →
ancient14–16-0.0218%26 Sept →
anubis13–10-0.0417%20 Sept →
ancient8–13-0.0614%13 May →
anubis13–9-0.0515%13 May →
nuke13–2-0.0421%11 May →
nuke13–30.0321%6 May →
dust24–13-0.0813%6 May →
vertigo13–2-0.0610%6 May →
vertigo13–6-0.0512%6 May →
vertigo13–110.0424%2 May →
nuke7–130.0018%2 May →
dust213–30.1417%2 May →
nuke6–13-0.0518%19 Apr →
vertigo13–80.0513%19 Apr →
ancient13–90.0012%14 Apr →
nuke11–13-0.049%14 Apr →
anubis13–70.1114%14 Apr →
ancient13–8-0.0210%12 Apr →
vertigo8–13-0.057%12 Apr →
anubis13–90.0011%12 Apr →
ancient12–16-0.0418%10 Apr →
vertigo13–60.045%10 Apr →
anubis5–13-0.1014%10 Apr →
vertigo13–5-0.0115%10 Apr →
ancient9–13-0.0530%9 Apr →
anubis13–11-0.013%8 Apr →
overpass11–13-0.0611%8 Apr →
overpass4–13-0.090%7 Apr →
ancient13–9-0.087%7 Apr →
vertigo6–13-0.0217%7 Apr →
vertigo6–13-0.0225%1 Apr →
vertigo13–8-0.0418%25 Mar →
anubis4–13-0.0615%25 Mar →
overpass8–13-0.1019%25 Mar →
nuke13–7-0.0111%24 Mar →
nuke13–11-0.0112%24 Mar →
inferno8–13-0.069%24 Mar →
ancient13–8-0.035%24 Mar →
anubis8–13-0.0613%24 Mar →
inferno6–13-0.0417%24 Mar →
ancient13–40.0121%24 Mar →
nuke13–9-0.0114%23 Mar →
ancient9–13-0.0610%23 Mar →
vertigo13–7-0.0113%23 Mar →
mirage7–13-0.0819%23 Mar →
overpass6–13-0.0425%23 Mar →
ancient13–11-0.0519%23 Mar →
inferno13–50.0227%23 Mar →
nuke13–110.0416%23 Mar →
vertigo13–10-0.0420%23 Mar →
anubis13–80.0119%22 Mar →
ancient15–15-0.0218%10 Mar →
ancient7–130.0211%4 Mar →
nuke13–60.0215%4 Mar →
ancient9–13-0.0515%3 Mar →
vertigo13–100.0222%3 Mar →
inferno11–13-0.0416%3 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 →

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