Da lad Kaiser

Da lad Kaiser — CS2 Stats

CA76561198081370655[U:1:121104927]Steam profile ↗✓ No bans

410Tracked matches45%Win rate2020Tracked since
1,270Hours in CS
CSDB Rating5.2 DevelopingPositional Player
Premier CS Rating16,089Purple band · top ~24.1% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 20 Sep 2026 (28 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: 16,089 +2,005 20 Jun – 20 Sept · 9 days played
12,96316,608peak 16,60820 Jun20 Sept
16,969Peak Premier in tracked matches
27Days played since 2025-06-20

Premier CS Rating

  • 519 below peak (16,608)
  • Next: Pink band at 20,000 — 3,911 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.

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 rate36.1%44.3%46.9%10.8% short
Shot accuracy17.9%11.9%13.0%above
Kill/death ratio1.061.031.080.02 short
Match win rate44.1%45.2%46.7%2.6% short

This profile matches the typical Pink band player on 1 of 4 comparable metrics.

Widest gap: Headshot rate. 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.GGDa lad KaiserPREMIER16,089 · Purple bandcsdb.gg/stats

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Performance scores

Aim68
Positioning51
Utility39

0–100 skill scores via Leetify.

Recent form

COLD45–49–6Last 10045%Win rateLLWLLWLLLL

Last 10 vs previous 10: −20pp win rate · −0.03 avg rating · +10.4pp headshot accuracy · +28ms reaction

Win rate down 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

  • 1–4 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 22%
  • Avg reaction 625ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 29%
  • Avg reaction 567ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 24%
  • Avg reaction 553ms

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 (+1.7 against its own average).

Aim6.8
Utility3.9
Positioning5.1
Opening Duels1.1

Strong CT-side openerEffective flashesLimited 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

iM

Plays most like iM 89% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; lower opening-duel success.

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 45% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 566ms 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

Aim6.8
Positioning5.1
Utility3.9
Mechanics7.2
Opening Duels1.8
Win Impact3.3

Composite 5.2/10 (Developing), 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-0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.00
Reaction time569ms−97ms
first ⅓ avg 667ms → last ⅓ avg 569ms
Headshot accuracy22.6%−1.4%
first ⅓ avg 24.1% → last ⅓ avg 22.6%

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

0.13Best match rating · 13–2 · cache, 4 Sept →
100%Best headshot accuracy · 6–2 · inferno, 19 Sept →
328msFastest reaction time · 6–2 · inferno, 19 Sept →
13–0Biggest win · dust2, 1 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L2Current streak
4–10In matches decided by ≤2 rounds
7Overtime games

Map breakdown

mirageBest map · 55% over 20anubisWeakest map · 25% over 8
MapGradePlayedRecordWin rateAvg rating
dust2B3015–1550%0.02
infernoB2612–1446%0.01
mirageA2011–955%-0.01
anubisD82–625%-0.01
cacheD72–529%0.01
train—31–233%0.02
ancient—32–167%-0.01
nuke—20–20%-0.06
overpass—10–10%-0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

54,951Lifetime kills
1.06K/D · Top 50% of Purple band
2,675Matches
44.1%Match win rate
36.1%Headshot %
17.9%Shot accuracy · Top 10% of Purple band
7,439MVPs
1,270Hours (in match)
3,238Bombs planted
907Bombs defused

Most-used weapons

AWP14,027
AK-4711,933
Tec-91,707
P901,369
P2501,289

Lifetime map wins

9,047dust2
4,106inferno
920nuke
600cbble
360train
243vertigo
28lake
19ar_baggage

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.

20.1%Headshot accuracy
33.8%Accuracy (enemy spotted)
34.7%Spray accuracy
82.2%Counter-strafing
11.3°Preaim
566msReaction time
26.4%T opening success
44.8%CT opening success
0.75Enemies flashed / flash
7.6%Flash assists
8.47HE damage / grenade
3.67Flashes / 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. Grenades & Utility

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

    Flashes per match 3.6695 — below the 4 mark we flag

    Grenade Lineups →
  2. 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 26.4053% — below the 40% mark we flag

Spend your practice time on Anubis

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

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno4–13-0.0529%20 Sept →
inferno6–13-0.0129%20 Sept →
dust213–110.0123%20 Sept →
mirage4–13-0.0512%20 Sept →
cache2–13-0.0918%19 Sept →
inferno6–2-0.03100%19 Sept →
dust26–13-0.0217%19 Sept →
cache6–13-0.0123%19 Sept →
mirage9–13-0.0219%19 Sept →
inferno5–13-0.0223%19 Sept →
dust213–90.0512%19 Sept →
mirage7–13-0.0130%14 Sept →
inferno13–100.0826%14 Sept →
inferno11–130.026%14 Sept →
inferno4–13-0.0221%14 Sept →
mirage13–50.0324%14 Sept →
mirage14–16-0.0313%14 Sept →
dust27–13-0.0120%4 Sept →
mirage13–40.0122%4 Sept →
dust214–16-0.0718%4 Sept →
inferno13–9-0.057%4 Sept →
cache13–20.1312%4 Sept →
dust210–130.0116%1 Sept →
inferno13–90.0118%1 Sept →
anubis5–13-0.0620%1 Sept →
anubis15–15-0.0415%29 Aug →
cache13–3-0.0215%29 Aug →
mirage13–80.0215%29 Aug →
inferno13–30.0332%29 Aug →
inferno3–20.0757%29 Aug →
cache1–40.0617%29 Aug →
dust26–130.0716%29 Aug →
inferno7–13-0.0322%29 Aug →
inferno7–13-0.0514%29 Aug →
dust27–130.0725%17 May →
cache10–13-0.0510%17 May →
cache12–120.0422%17 May →
train8–13-0.0318%16 May →
mirage13–80.0119%16 May →
anubis6–13-0.0417%25 Apr →
inferno12–12-0.0414%20 Apr →
ancient13–8-0.0317%20 Apr →
anubis11–130.0521%20 Apr →
inferno13–30.0536%20 Apr →
dust216–12-0.0013%20 Apr →
mirage13–80.0614%19 Apr →
dust213–60.0123%19 Apr →
mirage11–13-0.0518%1 Oct →
dust213–50.0330%1 Oct →
inferno5–13-0.0419%1 Oct →
dust212–120.0118%1 Sept →
dust21–130.0163%1 Sept →
nuke7–13-0.0329%30 Aug →
ancient13–4-0.0220%30 Aug →
mirage13–7-0.0329%30 Aug →
dust213–00.0931%1 Aug →
dust211–130.0836%1 Aug →
dust216–13-0.0033%26 Jul →
mirage3–13-0.0715%26 Jul →
mirage6–13-0.0718%24 Jul →
inferno13–70.0630%24 Jul →
dust213–90.0828%24 Jul →
inferno13–90.0212%24 Jul →
overpass6–13-0.0225%24 Jul →
mirage13–60.0723%24 Jul →
inferno13–90.000%15 Jul →
mirage12–120.0332%15 Jul →
dust213–90.0448%9 Jul →
dust26–13-0.0538%9 Jul →
inferno5–130.0245%9 Jul →
dust27–130.1251%9 Jul →
dust23–10-0.0150%9 Jul →
mirage13–11-0.0033%30 Jun →
inferno7–90.0224%29 Jun →
inferno3–13-0.0414%27 Jun →
dust213–9-0.0320%27 Jun →
dust213–80.0132%27 Jun →
dust213–80.0214%26 Jun →
dust213–100.0818%26 Jun →
dust213–110.0111%25 Jun →
anubis4–13-0.018%25 Jun →
dust211–13-0.0419%25 Jun →
inferno11–130.0715%25 Jun →
anubis13–70.0624%25 Jun →
train1–13-0.0128%23 Jun →
inferno11–130.0226%23 Jun →
mirage6–13-0.0616%21 Jun →
anubis4–13-0.0520%21 Jun →
ancient9–130.0121%21 Jun →
dust215–150.0310%21 Jun →
mirage13–9-0.0217%21 Jun →
inferno13–10.0414%21 Jun →
anubis13–90.0511%20 Jun →
dust213–80.0925%20 Jun →
nuke3–13-0.0930%20 Jun →
mirage13–40.0427%20 Jun →
mirage13–80.0119%20 Jun →
train13–50.0826%20 Jun →
inferno13–30.0118%20 Jun →
dust213–16-0.0221%20 Jun →

Match data via Leetify.

Recent teammates

Milestones

100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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