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SmulaN

SmulaN — CS2 Stats

SE76561198785988288[U:1:825722560]Steam profile ↗✓ No bans

2,364Tracked matches41%Win rate2025Tracked since
CSDB Rating1.4 LearningClutch Specialist
Premier CS Rating2,974Grey band · top ~87.4% of ranked players (population est.)
CSDB Leaderboard#200131 of 251490 tracked
FaceitLevel 1 · 484 ELOTop 100.0% of ranked FACEIT players
WingmanSilver IV
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Oct 2026 (yesterday). 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: 2,974 +691 6 Sept – 13 Oct · 19 days played
2,0723,534peak 3,5346 Sept13 Oct
Faceit ELO: 484 +0 6 Sept – 20 Sept · 3 observations
484484peak 4846 Sept20 Sept
3,631Peak Premier in tracked matches
484Highest Faceit ELO seen on CSDB
23Days played since 2026-09-06

Faceit ELO

  • At peak — 484
  • Next: Level 2 at 501 — 17 to go

Premier CS Rating

  • 560 below peak (3,534)
  • +902 over 30 days · improving
  • Next: Light Blue band at 5,000 — 2,026 to go

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGSmulaNFACEITLevel 1 · 484 ELOSTANDINGTop 100.0% of rankedPREMIER2,974 · Grey bandPEAK ELO484csdb.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

Aim9
Positioning26
Utility5

0–100 skill scores via Leetify.

Recent form

COLD44–55–1Last 10044%Win rateWLLLLLWLWL

Last 10 vs previous 10: −20pp win rate · +0.02 avg rating · +0.1pp headshot accuracy · +26ms reaction

Win rate down 20pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 4%
  • Avg reaction 714ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 5%
  • Avg reaction 735ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 5%
  • Avg reaction 722ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+2.2 against its own average).

Aim0.9
Utility0.5
Positioning2.6
Opening Duels0.0
Clutch4.0

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

jL

Plays most like jL 75% playstyle similarity

Most alike: positioning profile, utility contribution.

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

CT openings. Opening success drops from 45% on T to 25% on CT — first contacts on the defending side are being lost.

Reaction time. 720ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 57% 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

Aim0.9
Positioning2.6
Utility0.5
Mechanics1.6
Opening Duels1.9
Win Impact2.1

Composite 1.4/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.07−0.02
first ⅓ avg -0.06 → last ⅓ avg -0.07
Reaction time704ms+32ms
first ⅓ avg 672ms → last ⅓ avg 704ms
Headshot accuracy6.8%−0.9%
first ⅓ avg 7.7% → last ⅓ avg 6.8%

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

0.09Best match rating · 13–6 · dust2, 13 Oct →
19%Best headshot accuracy · 9–13 · nuke, 4 Oct →
398msFastest reaction time · 3–7 · rush_001, 7 Oct →
13–1Biggest win · train, 7 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
4–4In matches decided by ≤2 rounds
4Overtime games

Map breakdown

mirageBest map · 56% over 9nukeWeakest map · 11% over 9
MapGradePlayedRecordWin rateAvg rating
infernoC2511–1444%-0.06
cacheB136–746%-0.04
anubisB115–645%-0.06
mirageA95–456%-0.03
nukeD91–811%-0.10
ancientD93–633%-0.06
vertigoB84–450%-0.08
dust2B84–450%-0.04
train—32–167%-0.02
overpass—21–150%-0.03
rush_001—10–10%-0.15
shelter—11–0100%-0.03
debris—11–0100%-0.08

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.

Faceit stats

Combat

159Matches
47%Win rate
0.56Avg K/D
49.3ADR
28%Headshot %

Clutches & streaks

40%1v1 clutch win
7%1v2 clutch win
6Longest win streak

Recent Faceit resultsWWLWW

MapMatchesWin rateAvg K/DAvg kills
Inferno2756%0.628.8
Anubis2650%0.589.6
Ancient2532%0.539.2
Cache2138%0.658.0
Dust22152%0.548.9
Nuke1856%0.527.7
Mirage1638%0.386.2
Vertigo560%0.6211.0

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.

8.4%Headshot accuracy
30.6%Accuracy (enemy spotted)
31.3%Spray accuracy
57.0%Counter-strafing
15.4°Preaim
720msReaction time
45.4%T opening success
25.4%CT opening success
0.00Enemies flashed / flash
0.0%Flash assists
1.60HE damage / grenade
0.30Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 15.3543° — above the 12° mark we flag

    Aim Training →
  2. 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 8.4487% — below the 15% mark we flag

    Aim Training →
  3. 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 719.6182ms — above the 700ms mark we flag

    Aim Training →
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
mirage13–6-0.027%14 Oct →
vertigo4–13-0.080%14 Oct →
inferno10–13-0.053%13 Oct →
cache3–13-0.023%13 Oct →
mirage11–13-0.076%13 Oct →
dust20–13-0.157%13 Oct →
mirage13–10-0.049%13 Oct →
nuke8–13-0.066%13 Oct →
dust213–60.0911%13 Oct →
inferno4–9-0.154%13 Oct →
inferno3–13-0.083%12 Oct →
anubis6–13-0.133%11 Oct →
ancient13–11-0.055%11 Oct →
cache13–90.008%11 Oct →
inferno9–5-0.156%11 Oct →
mirage3–13-0.036%10 Oct →
cache3–13-0.048%10 Oct →
inferno4–9-0.073%10 Oct →
ancient13–8-0.086%10 Oct →
inferno9–7-0.205%10 Oct →
mirage13–8-0.0012%8 Oct →
inferno5–13-0.0714%8 Oct →
cache5–13-0.096%8 Oct →
rush_0013–7-0.150%7 Oct →
vertigo9–6-0.077%7 Oct →
train13–4-0.0518%7 Oct →
train13–10.013%7 Oct →
train5–13-0.017%7 Oct →
anubis13–9-0.079%7 Oct →
ancient10–13-0.0816%6 Oct →
nuke6–9-0.273%6 Oct →
inferno9–5-0.0712%6 Oct →
ancient9–13-0.0710%5 Oct →
cache3–13-0.030%4 Oct →
nuke9–13-0.0919%4 Oct →
dust215–15-0.0516%4 Oct →
ancient13–10-0.0012%3 Oct →
cache13–7-0.0411%3 Oct →
inferno7–13-0.105%3 Oct →
anubis11–13-0.0410%3 Oct →
nuke4–13-0.0411%3 Oct →
cache13–40.056%3 Oct →
mirage13–9-0.0313%3 Oct →
cache13–2-0.044%2 Oct →
mirage1–13-0.0313%2 Oct →
inferno16–13-0.015%2 Oct →
ancient2–13-0.033%1 Oct →
nuke11–13-0.0916%1 Oct →
cache3–13-0.116%1 Oct →
ancient1–13-0.098%1 Oct →
inferno13–90.007%1 Oct →
dust214–16-0.0710%1 Oct →
cache3–13-0.092%30 Sept →
nuke9–13-0.123%30 Sept →
vertigo13–4-0.108%30 Sept →
cache13–90.0111%30 Sept →
shelter13–6-0.034%29 Sept →
mirage13–7-0.015%29 Sept →
dust213–3-0.047%29 Sept →
anubis13–6-0.027%29 Sept →
inferno9–13-0.0810%29 Sept →
debris9–6-0.086%29 Sept →
inferno10–13-0.066%29 Sept →
anubis5–13-0.079%29 Sept →
inferno13–60.0310%29 Sept →
ancient3–13-0.089%28 Sept →
inferno13–2-0.0311%28 Sept →
anubis13–10-0.058%28 Sept →
inferno6–13-0.069%28 Sept →
overpass5–13-0.087%26 Sept →
cache13–10.017%26 Sept →
inferno7–13-0.0812%26 Sept →
anubis13–110.0112%26 Sept →
vertigo2–13-0.028%26 Sept →
ancient8–13-0.0910%26 Sept →
inferno10–13-0.0216%25 Sept →
vertigo7–13-0.086%25 Sept →
inferno2–9-0.245%25 Sept →
vertigo13–7-0.0312%25 Sept →
vertigo9–6-0.1412%25 Sept →
anubis5–13-0.0512%25 Sept →
nuke5–13-0.046%25 Sept →
nuke1–9-0.176%24 Sept →
vertigo2–13-0.100%23 Sept →
cache0–13-0.133%22 Sept →
dust213–50.0211%22 Sept →
inferno13–8-0.045%21 Sept →
anubis13–8-0.090%21 Sept →
nuke13–5-0.0316%21 Sept →
inferno6–9-0.105%21 Sept →
mirage8–13-0.0510%21 Sept →
anubis10–13-0.058%20 Sept →
inferno9–50.065%20 Sept →
inferno9–40.0211%20 Sept →
dust26–13-0.112%20 Sept →
overpass13–60.026%20 Sept →
inferno8–13-0.023%20 Sept →
inferno16–14-0.038%20 Sept →
dust213–3-0.048%20 Sept →
anubis4–13-0.065%20 Sept →

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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