Black Tulip

Black Tulip — CS2 Stats

DE76561198054011818[U:1:93746090]Steam profile ↗✓ No bans

1,261Tracked matches39%Win rate2020Tracked since
3,021Hours in CS5Hrs last 2 wks
CSDB Rating4.7 DevelopingPositional Player
Premier CS Rating12,639Blue band · top ~40.9% of ranked players (population est.)
WingmanGold Nova III
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Sep 2026 (9 days ago). Ranks are recorded once per day this page is viewed.

+184Premier CS Rating · 12,455 → 12,639

Rating over time

Premier CS Rating: 12,639 -2,021 25 May – 2 Oct · 24 days played
12,31015,352peak 15,35225 May2 Oct
15,712Peak Premier in tracked matches
36Days played since 2026-05-25

Premier CS Rating

  • 2,713 below peak (15,352)
  • +329 over 30 days · steady
  • -1,136 over 90 days
  • Next: Purple band at 15,000 — 2,361 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.

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches23——
Win rate30%——
K/D0.71——
Headshot %40%——

Measured 30 Aug 2026 → 2 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate40.6%42.0%44.3%3.7% short
Shot accuracy17.8%9.6%11.9%above
Kill/death ratio1.020.981.03meets
Match win rate34.8%43.8%45.2%10.4% short

This profile matches the typical Purple band player on 2 of 4 comparable metrics.

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

Share this profile

CSDB.GGBlack TulipPREMIER12,639 · Blue bandcsdb.gg/stats

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Performance scores

Aim54
Positioning59
Utility54

0–100 skill scores via Leetify.

Recent form

COLD41–53–6Last 10041%Win rateLTWLLWTLLL

Last 10 vs previous 10: −30pp win rate · −0.00 avg rating · −1.1pp headshot accuracy · +60ms reaction

Win rate down 30pp 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

  • 1–3–1 · 20% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 575ms

Last 10

  • 2–6–2 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 12%
  • Avg reaction 589ms

Last 20

  • 7–11–2 · 35% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 12%
  • Avg reaction 559ms

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 (+0.9 against its own average).

Aim5.4
Utility5.4
Positioning5.9
Opening Duels3.7

Strong CT-side openerLimited 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 78% playstyle similarity

Most alike: utility contribution, positioning profile.

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

Reaction time. 579ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 70% 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

Aim5.4
Positioning5.9
Utility5.4
Mechanics4.4
Opening Duels5.0
Win Impact1.4

Composite 4.7/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.03−0.02
first ⅓ avg -0.00 → last ⅓ avg -0.03
Reaction time581ms−74ms
first ⅓ avg 656ms → last ⅓ avg 581ms
Headshot accuracy13.9%−0.8%
first ⅓ avg 14.8% → 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

0.21Best match rating · 9–6 · inferno, 12 Jul →
38%Best headshot accuracy · 11–13 · ancient, 14 Jul →
438msFastest reaction time · 5–9 · inferno, 21 Aug →
13–0Biggest win · cache, 28 Jul →

Across the last 100 tracked matches.

Highlights

3Longest win streak
12–7In matches decided by ≤2 rounds
12Overtime games

Map breakdown

anubisBest map · 50% over 16dust2Weakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
infernoB2913–1645%0.00
ancientD185–1328%-0.02
anubisB168–850%-0.01
nukeC135–838%-0.01
cacheB84–450%-0.02
dust2D51–420%-0.03
mirageC52–340%-0.00
vertigo—31–233%0.02
overpass—32–167%0.06

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

108,438Lifetime kills
1.02K/D · Top 50% of Blue band
5,574Matches
34.8%Match win rate
40.6%Headshot %
17.8%Shot accuracy · Top 10% of Blue band
13,001MVPs
1,819Hours (in match)
5,071Bombs planted
1,060Bombs defused

Most-used weapons

AWP16,506
SG 55314,133
AK-477,157
AUG7,047
P902,743

Lifetime map wins

9,611inferno
1,715dust2
1,634vertigo
1,593cbble
1,249nuke
889train
175office
169lake

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.2%Headshot accuracy
33.9%Accuracy (enemy spotted)
36.6%Spray accuracy
69.8%Counter-strafing
10.4°Preaim
579msReaction time
46.0%T opening success
54.3%CT opening success
0.56Enemies flashed / flash
4.0%Flash assists
11.76HE damage / grenade
3.42Flashes / 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 14.202% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.4226 — below the 4 mark we flag

    Grenade Lineups →
Spend your practice time on Dust 2

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno2–130.0312%2 Oct →
dust215–15-0.0217%2 Oct →
inferno13–3-0.0314%2 Oct →
dust22–13-0.015%23 Sept →
dust211–13-0.0312%23 Sept →
nuke13–11-0.0210%23 Sept →
anubis15–150.0012%14 Sept →
inferno7–9-0.0615%14 Sept →
vertigo3–9-0.130%14 Sept →
anubis13–16-0.0420%13 Sept →
inferno12–16-0.067%13 Sept →
nuke13–10-0.0217%13 Sept →
ancient9–13-0.0412%13 Sept →
cache16–120.038%10 Sept →
ancient9–13-0.0410%10 Sept →
anubis13–11-0.0213%10 Sept →
inferno11–13-0.0511%9 Sept →
cache13–10-0.0113%9 Sept →
ancient3–13-0.1012%9 Sept →
ancient13–3-0.0022%9 Sept →
inferno13–6-0.017%9 Sept →
dust27–13-0.0917%9 Sept →
inferno5–9-0.1017%21 Aug →
ancient4–13-0.0411%10 Aug →
inferno13–10.0919%10 Aug →
nuke11–13-0.0316%7 Aug →
inferno12–16-0.0215%7 Aug →
anubis11–13-0.0125%7 Aug →
inferno6–13-0.039%5 Aug →
ancient13–3-0.0030%5 Aug →
cache13–20.005%5 Aug →
mirage6–13-0.0229%4 Aug →
ancient9–13-0.0317%4 Aug →
inferno13–10-0.016%3 Aug →
anubis16–140.0420%3 Aug →
inferno5–130.0116%30 Jul →
ancient15–15-0.0310%30 Jul →
anubis13–10-0.0012%28 Jul →
inferno7–13-0.0417%28 Jul →
cache13–00.016%28 Jul →
ancient9–13-0.0513%27 Jul →
ancient5–13-0.0018%26 Jul →
cache12–16-0.0510%26 Jul →
anubis13–110.0722%26 Jul →
ancient10–13-0.065%26 Jul →
nuke8–80.0217%25 Jul →
inferno8–80.059%25 Jul →
ancient13–110.0012%15 Jul →
anubis4–130.0117%15 Jul →
ancient11–130.0138%14 Jul →
mirage13–110.0613%13 Jul →
inferno13–7-0.0114%13 Jul →
cache12–16-0.088%13 Jul →
mirage8–130.0218%13 Jul →
ancient12–160.0310%12 Jul →
anubis9–30.0016%12 Jul →
overpass9–70.1611%12 Jul →
nuke1–9-0.165%12 Jul →
inferno9–60.2125%12 Jul →
vertigo9–70.074%12 Jul →
vertigo8–80.1312%12 Jul →
nuke13–80.0315%11 Jul →
ancient13–100.0417%11 Jul →
anubis11–13-0.0723%11 Jul →
cache8–13-0.0517%11 Jul →
dust213–6-0.0026%11 Jul →
anubis7–13-0.0319%8 Jul →
inferno6–13-0.0813%5 Jul →
nuke7–130.0220%5 Jul →
nuke6–130.019%5 Jul →
inferno9–60.1615%5 Jul →
inferno9–7-0.0121%5 Jul →
inferno9–40.1116%4 Jul →
inferno6–9-0.0323%4 Jul →
inferno8–130.0411%1 Jul →
nuke4–13-0.014%1 Jul →
overpass4–13-0.0223%21 Jun →
inferno13–10-0.059%21 Jun →
mirage13–8-0.0313%21 Jun →
ancient13–11-0.0611%21 Jun →
ancient6–130.017%18 Jun →
inferno13–5-0.0120%18 Jun →
anubis2–13-0.1116%17 Jun →
ancient2–13-0.0112%17 Jun →
anubis13–50.0013%17 Jun →
inferno10–13-0.049%14 Jun →
inferno4–13-0.0324%14 Jun →
inferno5–9-0.0522%7 Jun →
inferno9–6-0.0012%7 Jun →
nuke6–130.0121%6 Jun →
anubis13–11-0.0310%6 Jun →
cache7–130.0111%31 May →
nuke13–100.0123%31 May →
anubis4–130.0011%31 May →
nuke13–10-0.0125%30 May →
anubis13–110.0214%30 May →
overpass13–20.047%28 May →
nuke8–13-0.0216%28 May →
mirage13–16-0.039%25 May →
inferno13–60.0718%25 May →

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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