LowCiel

LowCiel — CS2 Stats

76561198080069312[U:1:119803584]Steam profile ↗✓ No bans

2,873Tracked matches57%Win rate2021Tracked since
CSDB Rating6.2 SolidPositional Player
Premier CS Rating18,108Purple band · top ~16% of ranked players (population est.)
FaceitLevel 6 · 1,072 ELOTop 54.0% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 10 Oct 2026 (4 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: 18,108 +3,641 10 Aug – 10 Oct · 25 days played
14,44718,108peak 18,10810 Aug10 Oct
Faceit ELO: 1,072 +0 20 Sept – 24 Sept · 2 observations
1,0721,072peak 1,07220 Sept24 Sept
18,370Peak Premier in tracked matches
1,072Highest Faceit ELO seen on CSDB
37Days played since 2026-08-10

Faceit ELO

  • At peak — 1,072
  • Next: Level 6 at 1,201 — 129 to go
  • Reached: Level 5 · Level 4 · Level 3 · Level 2
  • Level 5 first seen 2026-09-20
  • Level 4 first seen 2026-09-20

Premier CS Rating

  • At peak — 18,108
  • +1,550 over 30 days · improving
  • Next: Pink band at 20,000 — 1,892 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-20
  • Blue band first seen 2026-09-20

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.GGLowCielFACEITLevel 6 · 1,072 ELOSTANDINGTop 54.0% of rankedPREMIER18,108 · Purple bandPEAK ELO1,072csdb.gg/stats

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Performance scores

Aim75
Positioning58
Utility30

0–100 skill scores via Leetify.

Recent form

STEADY58–38–4Last 10058%Win rateLLWWLWWLWL

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating · +4.6pp headshot accuracy · +13ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 633ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 17%
  • Avg reaction 629ms

Last 20

  • 9–10–1 · 45% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 623ms

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 (+1.8 against its own average).

Aim7.5
Utility3.0
Positioning5.8
Opening Duels3.3
Clutch3.8

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 91% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower opening-duel success; lower utility contribution.

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

Strengths

T openings. 61% T opening-duel success — entries that actually open the round.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

CT openings. Opening success drops from 61% on T to 44% on CT — first contacts on the defending side are being lost.

Reaction time. 595ms 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

Aim7.5
Positioning5.8
Utility3.0
Mechanics6.6
Opening Duels5.6
Win Impact7.4

Composite 6.2/10 (Solid), 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 rating-0.02−0.02
first ⅓ avg 0.00 → last ⅓ avg -0.02
Reaction time601ms−1ms
first ⅓ avg 602ms → last ⅓ avg 601ms
Headshot accuracy14.3%−0.6%
first ⅓ avg 14.9% → last ⅓ avg 14.3%

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

0.11Best match rating · 13–9 · dust2, 13 Aug →
30%Best headshot accuracy · 13–10 · dust2, 14 Aug →
422msFastest reaction time · 13–10 · inferno, 7 Sept →
12–1Biggest win · ancient, 10 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L2Current streak
10–8In matches decided by ≤2 rounds
9Overtime games

Map breakdown

anubisBest map · 75% over 16infernoWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
dust2A3321–1264%-0.00
ancientA1610–663%-0.02
anubisS1612–475%-0.00
mirageC114–736%-0.03
nukeC83–538%-0.02
cacheA74–357%0.00
infernoD72–529%-0.01
vertigo—22–0100%0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

853Matches
49%Win rate
0.99Avg K/D
74.4ADR
32%Headshot %

Clutches & streaks

39%1v1 clutch win
20%1v2 clutch win
7Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Dust223555%1.0515.3
Ancient18752%0.9514.9
Anubis13347%0.9214.4
Vertigo7141%1.0115.0
Mirage6152%1.1115.1
Inferno3642%1.0015.7
Train1718%0.9817.0
Nuke1040%0.8516.5

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.

14.6%Headshot accuracy
38.2%Accuracy (enemy spotted)
42.1%Spray accuracy
79.7%Counter-strafing
9.2°Preaim
595msReaction time
61.0%T opening success
43.5%CT opening success
0.48Enemies flashed / flash
5.6%Flash assists
5.99HE damage / grenade
2.86Flashes / 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 14.607% — 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 0.4849 — below the 0.5 mark we flag

    Grenade Lineups →
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.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient6–13-0.0213%10 Oct →
mirage4–13-0.0610%10 Oct →
mirage13–50.007%10 Oct →
cache13–9-0.0318%10 Oct →
anubis11–130.0414%7 Oct →
inferno13–90.0027%5 Oct →
ancient13–10-0.0329%5 Oct →
mirage7–13-0.0225%5 Oct →
anubis13–10-0.059%4 Oct →
dust210–13-0.0520%4 Oct →
dust27–13-0.027%4 Oct →
dust213–11-0.0318%4 Oct →
dust28–13-0.0521%3 Oct →
anubis3–13-0.056%3 Oct →
nuke12–12-0.0411%3 Oct →
ancient10–13-0.019%3 Oct →
anubis13–8-0.0620%2 Oct →
dust213–11-0.058%2 Oct →
ancient10–13-0.0812%2 Oct →
dust213–11-0.0014%2 Oct →
mirage15–15-0.0216%30 Sept →
dust216–12-0.0314%30 Sept →
anubis13–8-0.0110%29 Sept →
ancient13–90.0511%29 Sept →
anubis13–11-0.015%23 Sept →
dust213–80.0317%23 Sept →
anubis13–80.0114%17 Sept →
inferno3–13-0.0511%16 Sept →
anubis13–60.0424%13 Sept →
inferno11–13-0.0012%12 Sept →
anubis13–8-0.017%11 Sept →
dust213–6-0.0320%10 Sept →
ancient12–1-0.0413%10 Sept →
dust213–7-0.0124%9 Sept →
inferno13–100.0125%7 Sept →
cache13–80.0316%7 Sept →
mirage3–13-0.096%7 Sept →
dust211–130.0423%7 Sept →
vertigo13–60.0112%7 Sept →
anubis5–130.0212%5 Sept →
inferno10–130.0219%5 Sept →
dust213–9-0.0215%5 Sept →
anubis13–6-0.0118%4 Sept →
dust213–90.0512%4 Sept →
mirage11–13-0.048%4 Sept →
nuke15–150.0113%3 Sept →
dust216–13-0.055%3 Sept →
ancient13–60.019%3 Sept →
nuke13–8-0.058%2 Sept →
anubis13–70.050%2 Sept →
dust211–13-0.0212%2 Sept →
dust213–11-0.017%2 Sept →
cache13–50.020%31 Aug →
dust29–13-0.057%31 Aug →
nuke10–13-0.024%30 Aug →
ancient13–30.0117%29 Aug →
ancient16–13-0.038%29 Aug →
dust26–13-0.0410%27 Aug →
dust24–13-0.119%27 Aug →
ancient13–40.0415%27 Aug →
dust213–20.0219%27 Aug →
vertigo13–5-0.010%26 Aug →
ancient16–14-0.0216%25 Aug →
cache15–15-0.0214%24 Aug →
mirage9–13-0.0511%24 Aug →
mirage13–7-0.0112%24 Aug →
dust213–8-0.066%24 Aug →
ancient10–13-0.0812%24 Aug →
anubis13–90.0615%23 Aug →
dust213–110.039%23 Aug →
dust213–50.1114%23 Aug →
dust213–40.038%23 Aug →
mirage13–5-0.033%23 Aug →
dust26–13-0.0213%23 Aug →
ancient7–13-0.104%20 Aug →
dust213–70.0829%20 Aug →
ancient13–60.0511%18 Aug →
dust27–130.1013%18 Aug →
mirage14–160.0319%17 Aug →
dust213–70.107%17 Aug →
inferno11–130.026%17 Aug →
cache13–50.0222%17 Aug →
cache8–13-0.0228%15 Aug →
inferno6–13-0.077%15 Aug →
anubis6–13-0.0320%15 Aug →
nuke7–13-0.0616%15 Aug →
anubis16–140.0319%15 Aug →
nuke13–20.0018%15 Aug →
dust213–10-0.0830%14 Aug →
ancient13–6-0.0312%14 Aug →
dust213–7-0.0414%14 Aug →
mirage13–11-0.0120%14 Aug →
nuke11–130.0612%14 Aug →
nuke13–11-0.0512%13 Aug →
ancient3–13-0.0224%13 Aug →
dust213–90.1118%13 Aug →
anubis13–6-0.0311%13 Aug →
dust27–13-0.0711%12 Aug →
dust29–130.0321%10 Aug →
cache10–130.0015%10 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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