dLs-

dLs- — CS2 Stats

76561198948544260[U:1:988278532]Steam profile ↗✓ No bans

1,402Tracked matches53%Win rate2020Tracked since
3,534Hours in CS19Hrs last 2 wks
CSDB Rating7.0 StrongPositional Player
Premier CS Rating19,688Top 50% of 204,316 CSDB-tracked playersPurple band · top ~9.7% of ranked players (population est.)
CSDB Leaderboard#87041 of 251438 tracked
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Oct 2026 (2 days ago). Ranks are recorded once per day this page is viewed.

+263Premier CS Rating · 19,425 → 19,688

Rating over time

Premier CS Rating: 19,688 +1,327 30 Aug – 13 Oct · 20 days played
18,24320,495peak 20,49530 Aug13 Oct
20,495Peak Premier in tracked matches
1,565Highest Faceit ELO seen on CSDB
37Days played since 2026-08-09

Faceit ELO

  • At peak — 1,565
  • Next: Level 9 at 1,751 — 186 to go
  • Reached: Level 8 · Level 7 · Level 6 · Level 5

Premier CS Rating

  • 807 below peak (20,495)
  • +1,065 over 30 days · improving
  • Next: Pink band at 20,000 — 312 to go
  • Reached: Pink band · 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 rate48.0%44.3%46.9%above
Shot accuracy12.5%11.9%13.0%0.5% short
Kill/death ratio1.131.031.08above
Match win rate45.9%45.2%46.7%meets

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.GGdLs-PREMIER19,688 · Purple bandPEAK ELO1,565csdb.gg/stats

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Performance scores

Aim86
Positioning73
Utility38

0–100 skill scores via Leetify.

Recent form

STEADY54–42–4Last 10054%Win rateWLWLWTLWWW

Last 10 vs previous 10: +20pp win rate · +0.03 avg rating · +0.8pp headshot accuracy · +37ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 18%
  • Avg reaction 472ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating 0.07
  • Avg headshot accuracy 18%
  • Avg reaction 508ms

Last 20

  • 10–8–2 · 50% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 18%
  • Avg reaction 489ms

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 (+2.8 against its own average).

Aim8.6
Utility3.8
Positioning7.3
Opening Duels5.7
Clutch1.4

Sharp aimerLimited 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 86% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: 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

Aim. Aim score of 86 — the mechanical foundation is a clear strength.

T openings. 76% 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 76% on T to 55% on CT — first contacts on the defending side are being lost.

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

Aim8.6
Positioning7.3
Utility3.8
Mechanics6.6
Opening Duels8.2
Win Impact6.1

Composite 7.0/10 (Strong), 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 rating0.05+0.03
first ⅓ avg 0.02 → last ⅓ avg 0.05
Reaction time501ms−59ms
first ⅓ avg 560ms → last ⅓ avg 501ms
Headshot accuracy18.2%−6.6%
first ⅓ avg 24.8% → last ⅓ avg 18.2%

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

0.19Best match rating · 9–4 · inferno, 11 Oct →
75%Best headshot accuracy · 3–0 · cache, 23 Aug →
359msFastest reaction time · 9–6 · inferno, 11 Oct →
13–1Biggest win · ancient, 9 Aug →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

mirageBest map · 67% over 18infernoWeakest map · 37% over 19
MapGradePlayedRecordWin rateAvg rating
dust2A2212–1055%0.04
infernoC197–1237%0.05
mirageS1812–667%0.03
nukeC156–940%0.03
anubisA106–460%0.05
ancientA85–363%0.02
cacheA53–260%0.04
overpass—11–0100%0.05
vertigo—11–0100%0.18
train—11–0100%-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (37% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

88,504Lifetime kills
1.13K/D · Top 50% of Purple band
4,064Matches
45.9%Match win rate · Top 50% of Purple band
48.0%Headshot % · Top 50% of Purple band
12.5%Shot accuracy · Top 50% of Purple band
11,669MVPs
1,670Hours (in match)
5,154Bombs planted
1,199Bombs defused

Most-used weapons

AK-4730,611
AWP13,657
P2501,764
FAMAS1,365
MAC-101,337
P901,258

Lifetime map wins

11,694dust2
8,988inferno
1,408vertigo
1,368nuke
985train
343office
283cbble
58lake

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

Faceit stats

Combat

730Matches
50%Win rate
1.14Avg K/D
84.0ADR
44%Headshot %

Clutches & streaks

27%1v1 clutch win
29%1v2 clutch win
11Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage12146%1.0614.8
Dust25768%1.3216.4
Inferno4567%1.2617.3
Anubis3954%1.1617.3
Ancient3540%1.0015.9
Vertigo1233%0.9618.3
Nuke540%1.3217.4
Overpass2100%1.7219.0

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.

17.2%Headshot accuracy
38.0%Accuracy (enemy spotted)
38.7%Spray accuracy
79.9%Counter-strafing
7.6°Preaim
494msReaction time
75.9%T opening success
55.4%CT opening success
0.54Enemies flashed / flash
4.9%Flash assists
10.08HE damage / grenade
4.23Flashes / match

Recommended for you

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.

37% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis13–100.0317%13 Oct →
mirage9–130.0417%13 Oct →
nuke13–70.0724%13 Oct →
dust28–13-0.0018%11 Oct →
anubis13–70.0515%11 Oct →
nuke8–8-0.079%11 Oct →
inferno6–90.1130%11 Oct →
inferno9–40.1928%11 Oct →
nuke9–70.0810%11 Oct →
inferno9–60.1516%11 Oct →
inferno8–80.1522%10 Oct →
ancient13–110.0112%6 Oct →
nuke10–130.0112%4 Oct →
anubis7–130.0716%4 Oct →
overpass13–80.0516%4 Oct →
dust213–100.0013%4 Oct →
inferno13–90.0931%4 Oct →
nuke11–130.0313%3 Oct →
nuke9–130.0218%3 Oct →
dust28–13-0.0322%3 Oct →
dust213–40.0616%3 Oct →
cache13–70.0228%3 Oct →
anubis13–70.0414%1 Oct →
inferno13–90.0522%1 Oct →
cache10–130.0720%30 Sept →
mirage13–110.0821%30 Sept →
dust25–130.0121%30 Sept →
inferno1–13-0.0214%30 Sept →
dust213–80.1020%30 Sept →
dust27–130.0325%28 Sept →
inferno4–13-0.078%28 Sept →
mirage13–110.0517%28 Sept →
nuke11–130.0414%27 Sept →
nuke13–8-0.017%26 Sept →
anubis10–130.0811%26 Sept →
ancient13–70.0013%26 Sept →
mirage13–50.1615%26 Sept →
vertigo13–30.1824%26 Sept →
dust20–8-0.0725%26 Sept →
mirage13–80.0130%25 Sept →
nuke12–120.0715%24 Sept →
inferno13–50.1428%24 Sept →
nuke11–130.0016%23 Sept →
cache13–110.0928%23 Sept →
inferno15–15-0.0226%23 Sept →
ancient13–80.0426%23 Sept →
anubis13–80.0521%21 Sept →
mirage13–110.0120%20 Sept →
anubis13–80.1016%20 Sept →
mirage13–80.0314%20 Sept →
inferno11–130.0018%19 Sept →
nuke13–110.0723%19 Sept →
inferno13–70.1741%19 Sept →
ancient13–10-0.0315%19 Sept →
inferno14–16-0.0122%19 Sept →
dust214–16-0.0013%16 Sept →
anubis6–13-0.0118%16 Sept →
ancient5–130.0214%16 Sept →
dust213–70.1621%14 Sept →
nuke13–110.0518%13 Sept →
nuke4–130.0925%13 Sept →
dust213–70.0111%10 Sept →
inferno5–130.0219%9 Sept →
ancient5–130.0520%9 Sept →
mirage8–130.0521%8 Sept →
dust213–60.1633%8 Sept →
train13–11-0.0136%7 Sept →
dust28–130.0526%7 Sept →
inferno13–110.0418%3 Sept →
nuke13–110.0431%3 Sept →
dust213–6-0.0139%3 Sept →
mirage13–100.0110%3 Sept →
mirage13–30.0723%2 Sept →
inferno1–13-0.0510%2 Sept →
ancient11–13-0.0313%30 Aug →
anubis12–160.0522%30 Aug →
inferno1–13-0.0423%30 Aug →
anubis13–40.0216%30 Aug →
mirage13–3-0.029%30 Aug →
dust213–110.0137%28 Aug →
nuke4–130.0230%27 Aug →
dust213–80.0526%25 Aug →
cache5–130.0225%24 Aug →
mirage13–5-0.0329%24 Aug →
dust213–90.0337%23 Aug →
inferno5–13-0.0119%23 Aug →
mirage13–50.1026%23 Aug →
cache3–0-0.0275%23 Aug →
inferno8–13-0.0219%19 Aug →
mirage8–13-0.0614%19 Aug →
dust213–90.0332%19 Aug →
dust27–130.0942%18 Aug →
mirage7–13-0.0317%18 Aug →
dust211–130.0518%11 Aug →
dust213–80.1322%10 Aug →
mirage7–13-0.0629%10 Aug →
dust29–13-0.0418%10 Aug →
mirage13–90.0724%9 Aug →
ancient13–10.1116%9 Aug →
mirage4–130.0424%9 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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