SnkAlex

SnkAlex — CS2 Stats

FR76561199197067227[U:1:1236801499]Steam profile ↗✓ No bans

1,033Tracked matches41%Win rate2021Tracked since
712Hours in CS
CSDB Rating5.1 DevelopingSupport
Premier CS Rating15,100Purple band · top ~28% of ranked players (population est.)
WingmanGold Nova III
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Sep 2026 (44 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: 15,100 -3,493 13 Oct – 18 Sept · 13 days played
15,10018,896peak 18,89613 Oct18 Sept
18,896Peak Premier in tracked matches
1,544Highest Faceit ELO seen on CSDB
47Days played since 2025-10-06

Faceit ELO

  • At peak — 1,544
  • Next: Level 9 at 1,751 — 207 to go
  • Reached: Level 8 · Level 7 · Level 6 · Level 5

Premier CS Rating

  • 3,796 below peak (18,896)
  • Next: Pink band at 20,000 — 4,900 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.

How this compares with the same rank

Median values for Purple band among CSDB-tracked players (n=37,767), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerPurple band medianPink band medianvs Pink band
Headshot rate46.0%44.4%46.9%meets
Shot accuracy3.4%11.9%13.0%9.6% short
Kill/death ratio1.521.031.08above
Match win rate49.1%45.2%46.7%above

This profile matches the typical Pink band player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGSnkAlexPREMIER15,100 · Purple bandPEAK ELO1,544csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim73
Positioning47
Utility53

0–100 skill scores via Leetify.

Recent form

COLD50–44–6Last 10050%Win rateLLLLWLLWLW

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · −5.7pp headshot accuracy · −20ms 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

  • 1–4 · 20% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 494ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 10%
  • Avg reaction 507ms

Last 20

  • 6–13–1 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 517ms

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: Support — Utility contribution stands above the rest of this profile (+1.5 against its own average).

Aim7.3
Utility5.3
Positioning4.7
Opening Duels1.2
Clutch3.8

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 88% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; lower aim profile.

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

CSDB Rating breakdown

Aim7.3
Positioning4.7
Utility5.3
Mechanics5.9
Opening Duels1.1
Win Impact2.1

Composite 5.1/10 (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 rating0.00−0.01
first ⅓ avg 0.02 → last ⅓ avg 0.00
Reaction time539ms−42ms
first ⅓ avg 581ms → last ⅓ avg 539ms
Headshot accuracy14.1%+2.0%
first ⅓ avg 12.0% → last ⅓ avg 14.1%

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

0.17Best match rating · 13–1 · dust2, 15 Jul →
38%Best headshot accuracy · 6–13 · anubis, 21 Aug →
422msFastest reaction time · 1–13 · ancient, 17 Nov →
13–1Biggest win · dust2, 15 Jul →

Across the last 100 tracked matches.

Highlights

7Longest win streak
L4Current streak
6–5In matches decided by ≤2 rounds
7Overtime games

Map breakdown

officeBest map · 83% over 6nukeWeakest map · 11% over 9
MapGradePlayedRecordWin rateAvg rating
mirageB168–850%0.00
dust2B147–750%0.01
anubisC114–736%0.01
infernoA117–464%-0.00
ancientA116–555%-0.01
nukeD91–811%0.01
cacheC83–538%0.01
officeS65–183%0.01
overpassA53–260%0.01
train—33–0100%0.05
vertigo—20–20%-0.01
palacio—22–0100%0.05
italy—10–10%0.03
golden—11–0100%0.01

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (11% over 9). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

40,502Lifetime kills
1.52K/D · Top 5% of Purple band
1,506Matches
49.1%Match win rate · Top 25% of Purple band
46.0%Headshot % · Top 50% of Purple band
3.4%Shot accuracy
3,319MVPs
712Hours (in match)
2,167Bombs planted
400Bombs defused

Most-used weapons

Lifetime map wins

2,577inferno
2,512dust2
1,504nuke
1,129vertigo
530train
400office
30italy

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

Faceit stats

Combat

305Matches
52%Win rate
1.13Avg K/D
76.2ADR
33%Headshot %

Clutches & streaks

39%1v1 clutch win
21%1v2 clutch win
9Longest win streak

Recent Faceit resultsLWLWL

MapMatchesWin rateAvg K/DAvg kills
Anubis7059%1.1914.8
Ancient5357%1.0515.3
Dust25347%1.0514.5
Inferno4736%1.2617.3
Vertigo3765%1.1115.2
Nuke2162%1.1815.4
Mirage1354%0.9712.8
Train520%1.0313.2

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.

14.4%Headshot accuracy
35.8%Accuracy (enemy spotted)
35.8%Spray accuracy
76.6%Counter-strafing
8.3°Preaim
533msReaction time
28.7%T opening success
38.6%CT opening success
0.58Enemies flashed / flash
5.3%Flash assists
6.76HE damage / grenade
11.48Flashes / 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 14.3836% — below the 15% mark we flag

    Aim Training →
  2. 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 28.6613% — below the 40% mark we flag

Spend your practice time on Nuke

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

11% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis11–130.0522%20 Sept →
anubis7–13-0.067%18 Sept →
dust29–13-0.0413%18 Sept →
mirage5–13-0.047%17 Sept →
mirage13–100.039%16 Sept →
inferno2–13-0.068%16 Sept →
italy4–130.037%16 Sept →
mirage13–110.058%16 Sept →
overpass4–13-0.085%16 Sept →
dust213–50.0211%15 Sept →
inferno3–13-0.0414%15 Sept →
cache9–130.0319%15 Sept →
dust24–13-0.033%13 Sept →
anubis13–9-0.0025%9 Sept →
mirage9–13-0.029%8 Sept →
mirage1–13-0.0412%8 Sept →
ancient13–110.0111%7 Sept →
inferno13–7-0.0118%7 Sept →
anubis11–130.018%7 Sept →
nuke12–120.0436%7 Sept →
ancient2–13-0.0233%7 Sept →
inferno13–11-0.0211%5 Sept →
cache3–13-0.009%5 Sept →
cache13–70.0617%5 Sept →
mirage11–13-0.036%5 Sept →
train13–50.0523%5 Sept →
nuke6–130.0023%3 Sept →
dust213–100.0115%3 Sept →
dust213–100.1223%3 Sept →
ancient13–90.0217%2 Sept →
mirage9–13-0.059%2 Sept →
mirage13–50.1017%2 Sept →
dust23–13-0.0112%22 Aug →
anubis13–50.1019%21 Aug →
anubis6–13-0.0438%21 Aug →
nuke9–13-0.0415%3 Aug →
dust29–13-0.0224%3 Aug →
dust29–13-0.0913%3 Aug →
cache11–13-0.0115%31 Jul →
inferno13–6-0.009%31 Jul →
anubis7–130.029%29 Jul →
ancient5–13-0.047%28 Jul →
cache4–13-0.0311%28 Jul →
cache13–90.056%16 Jul →
dust213–10.1712%15 Jul →
nuke14–160.0216%15 Jul →
ancient15–15-0.0711%14 Jul →
inferno8–13-0.067%14 Jul →
anubis7–130.0220%2 Jul →
overpass13–30.0410%2 Jul →
vertigo9–13-0.0512%1 Jul →
train13–9-0.0316%30 Jun →
anubis13–80.018%30 Jun →
anubis9–13-0.026%29 Jun →
inferno13–110.0111%29 Jun →
cache13–70.0027%29 Jun →
inferno8–130.0318%29 Jun →
ancient13–20.0220%29 Jun →
nuke13–80.037%28 Jun →
nuke8–130.0313%27 Jun →
mirage13–30.0912%27 Jun →
nuke15–150.0221%26 Jun →
mirage13–100.0113%26 Jun →
overpass13–40.0117%25 Jun →
ancient6–1-0.018%25 Jun →
cache7–13-0.0621%25 Jun →
office13–5-0.0513%17 Nov →
ancient1–13-0.0613%17 Nov →
mirage9–13-0.0011%13 Nov →
office6–130.0131%13 Nov →
ancient13–90.027%12 Nov →
dust216–120.0310%9 Nov →
office13–90.000%8 Nov →
ancient8–130.018%6 Nov →
vertigo12–120.039%6 Nov →
nuke3–90.0011%31 Oct →
nuke10–13-0.0113%30 Oct →
inferno16–12-0.029%29 Oct →
mirage9–13-0.0217%25 Oct →
office13–70.0413%25 Oct →
office13–60.117%25 Oct →
mirage13–110.0510%24 Oct →
anubis13–9-0.0311%17 Oct →
office13–9-0.0416%15 Oct →
dust222–190.0312%15 Oct →
dust213–40.0013%14 Oct →
overpass15–150.0710%13 Oct →
train13–60.1316%12 Oct →
inferno13–100.0416%7 Oct →
mirage9–13-0.033%7 Oct →
overpass13–50.027%7 Oct →
inferno13–50.1215%7 Oct →
dust29–130.0418%7 Oct →
mirage13–10-0.0316%7 Oct →
palacio13–60.0313%7 Oct →
golden13–50.0114%7 Oct →
dust212–12-0.0217%6 Oct →
palacio13–60.0813%6 Oct →
ancient13–6-0.047%6 Oct →
mirage13–11-0.0510%6 Oct →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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