Samila

Samila — CS2 Stats

FI76561199086258518[U:1:1125992790]Steam profile ↗✓ No bans

1,926Tracked matches25%Win rate2022Tracked since
CSDB Rating3.5 LearningClutch Specialist
Premier CS Rating6,606Light Blue band · top ~71.1% of ranked players (population est.)
FaceitLevel 2 · 664 ELOTop 97.9% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 31 Oct 2026 (5 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: 6,606 +640 13 Aug – 31 Oct · 27 days played
5,0399,698peak 9,69813 Aug31 Oct
Faceit ELO: 664 +0 13 Sept – 24 Sept · 2 observations
664664peak 66413 Sept24 Sept
9,698Peak Premier in tracked matches
664Highest Faceit ELO seen on CSDB
26Days played since 2026-08-13

Faceit ELO

  • At peak — 664
  • Next: Level 3 at 751 — 87 to go
  • Reached: Level 2
  • Level 2 first seen 2026-09-13

Premier CS Rating

  • 3,092 below peak (9,698)
  • -892 over 30 days · declining
  • +640 over 90 days
  • Next: Blue band at 10,000 — 3,394 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-09-13

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.GGSamilaFACEITLevel 2 · 664 ELOSTANDINGTop 97.9% of rankedPREMIER6,606 · Light Blue bandPEAK ELO664csdb.gg/stats

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Performance scores

Aim39
Positioning52
Utility42

0–100 skill scores via Leetify.

Recent form

COLD40–55–5Last 10040%Win rateLLWLLLLLWL

Last 10 vs previous 10: +10pp win rate · −0.02 avg rating · +1.5pp headshot accuracy · −38ms reaction

Win rate +10pp 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 -0.02
  • Avg headshot accuracy 18%
  • Avg reaction 600ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 15%
  • Avg reaction 630ms

Last 20

  • 3–15–2 · 15% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 14%
  • Avg reaction 648ms

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 (+4.2 against its own average).

Aim3.9
Utility4.2
Positioning5.2
Opening Duels3.8
Clutch10.0

Strong CT-side openerLimited utility dependenceReliable in 1v1s

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

device

Plays most like device 74% 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

T-side openings. Opening success drops from 57% on CT to 31% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 644ms 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

Aim3.9
Positioning5.2
Utility4.2
Mechanics4.7
Opening Duels3.5
Win Impact0.0

Composite 3.5/10 (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-0.01−0.03
first ⅓ avg 0.02 → last ⅓ avg -0.01
Reaction time631ms+12ms
first ⅓ avg 619ms → last ⅓ avg 631ms
Headshot accuracy13.9%−1.5%
first ⅓ avg 15.4% → last ⅓ avg 13.9%

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 · 8–2 · dust2, 22 Aug →
32%Best headshot accuracy · 2–13 · anubis, 21 Aug →
438msFastest reaction time · 3–13 · inferno, 16 Aug →
13–1Biggest win · nuke, 1 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L2Current streak
4–8In matches decided by ≤2 rounds
12Overtime games

Map breakdown

nukeBest map · 52% over 25ancientWeakest map · 10% over 10
MapGradePlayedRecordWin rateAvg rating
nukeB2513–1252%0.04
infernoC219–1243%0.03
anubisB157–847%-0.01
dust2C135–838%0.02
ancientD101–910%0.00
mirageD71–614%-0.01
vertigo—32–167%0.00
overpass—32–167%0.03
cache—20–20%0.02
train—10–10%0.06

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (10% over 10). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

55Matches
35%Win rate
0.90Avg K/D
101.3ADR
33%Headshot %

Clutches & streaks

100%1v1 clutch win
0%1v2 clutch win
3Longest win streak

Recent Faceit resultsLWWWL

MapMatchesWin rateAvg K/DAvg kills
Inferno560%1.3020.6
Anubis425%0.8010.8
Vertigo367%0.7611.3
Ancient250%1.0614.0
Nuke250%1.0613.0
Overpass10%0.428.0

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.

13.9%Headshot accuracy
29.4%Accuracy (enemy spotted)
29.2%Spray accuracy
71.2%Counter-strafing
9.4°Preaim
644msReaction time
31.2%T opening success
57.0%CT opening success
0.42Enemies flashed / flash
7.9%Flash assists
8.61HE damage / grenade
3.63Flashes / 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 13.9045% — 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 0.4156 — 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 31.1509% — below the 40% mark we flag

Spend your practice time on Ancient

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

10% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage11–130.0124%31 Oct →
anubis4–13-0.0424%31 Oct →
anubis13–60.0414%31 Oct →
dust27–13-0.0619%31 Oct →
nuke2–13-0.078%31 Oct →
inferno8–13-0.089%16 Oct →
ancient8–13-0.0515%16 Oct →
inferno6–13-0.068%16 Oct →
inferno16–14-0.097%16 Oct →
inferno9–130.0317%10 Oct →
anubis5–13-0.069%10 Oct →
mirage5–13-0.0517%10 Oct →
mirage4–13-0.0323%10 Oct →
nuke10–13-0.0110%10 Oct →
dust26–13-0.0419%17 Sept →
inferno15–150.048%17 Sept →
mirage11–13-0.0410%8 Sept →
ancient7–130.009%8 Sept →
nuke13–90.0613%7 Sept →
anubis15–15-0.0014%7 Sept →
vertigo9–60.003%4 Sept →
mirage6–130.0516%4 Sept →
ancient10–13-0.0418%3 Sept →
nuke11–13-0.0713%2 Sept →
anubis9–13-0.0114%2 Sept →
ancient9–130.056%2 Sept →
inferno6–9-0.0115%2 Sept →
nuke16–140.1617%1 Sept →
ancient10–13-0.0221%1 Sept →
inferno13–4-0.0114%1 Sept →
nuke13–10.0814%1 Sept →
dust213–70.0111%1 Sept →
anubis16–12-0.0419%31 Aug →
inferno6–13-0.0322%31 Aug →
overpass9–60.1312%31 Aug →
overpass9–7-0.0816%31 Aug →
train10–130.0613%29 Aug →
vertigo7–130.038%29 Aug →
nuke13–90.098%29 Aug →
cache4–13-0.019%29 Aug →
inferno13–100.0116%29 Aug →
dust29–13-0.0223%26 Aug →
vertigo13–10-0.0220%25 Aug →
inferno8–130.0711%25 Aug →
dust212–12-0.0411%25 Aug →
nuke13–90.0010%25 Aug →
nuke12–160.0422%25 Aug →
anubis13–60.007%25 Aug →
nuke3–130.0616%25 Aug →
anubis16–120.0012%24 Aug →
nuke13–40.0322%24 Aug →
dust213–100.0315%24 Aug →
inferno13–50.119%24 Aug →
ancient11–13-0.018%24 Aug →
dust213–50.0519%24 Aug →
dust210–13-0.0310%23 Aug →
ancient13–160.0217%23 Aug →
inferno13–160.0815%23 Aug →
anubis12–100.063%22 Aug →
nuke5–130.1614%22 Aug →
dust212–120.1231%22 Aug →
dust28–20.1717%22 Aug →
dust28–130.1319%22 Aug →
inferno6–130.0522%22 Aug →
inferno13–40.0723%22 Aug →
inferno13–70.1116%21 Aug →
anubis2–13-0.0332%21 Aug →
nuke13–90.0722%21 Aug →
nuke8–130.0615%21 Aug →
dust213–50.0615%20 Aug →
cache9–130.0417%20 Aug →
nuke13–70.0113%20 Aug →
nuke13–160.0714%20 Aug →
nuke13–9-0.0317%20 Aug →
anubis13–90.0018%20 Aug →
nuke10–4-0.0122%20 Aug →
nuke9–130.0713%19 Aug →
nuke13–16-0.0013%19 Aug →
nuke13–100.0413%19 Aug →
inferno13–100.1011%19 Aug →
overpass8–80.0416%19 Aug →
anubis7–13-0.0513%18 Aug →
nuke13–20.0119%18 Aug →
mirage13–70.027%18 Aug →
inferno13–70.1514%17 Aug →
anubis13–5-0.0214%17 Aug →
ancient13–100.0510%17 Aug →
nuke11–130.0422%17 Aug →
inferno3–130.019%16 Aug →
anubis2–13-0.0424%16 Aug →
inferno4–13-0.0413%16 Aug →
mirage9–130.0132%15 Aug →
nuke7–130.0117%15 Aug →
inferno9–50.1524%15 Aug →
dust214–16-0.0710%15 Aug →
ancient11–130.0111%15 Aug →
anubis9–13-0.038%15 Aug →
inferno11–13-0.0414%14 Aug →
nuke13–50.0614%14 Aug →
ancient8–130.0215%13 Aug →

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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