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Dadelol

Dadelol — CS2 Stats

DE76561198757031390[U:1:796765662]Steam profile ↗✓ No bans

413Tracked matches46%Win rate2026Tracked since
436Hours in CS32Hrs last 2 wks
CSDB Rating3.5 LearningPositional Player
Premier CS Rating1,231Grey band · top ~94.8% of ranked players (population est.)
CSDB Leaderboard#198857 of 247855 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Sep 2026 (yesterday). 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: 1,231 -160 11 Sept – 30 Sept · 2 days played
1,2311,391peak 1,39111 Sept30 Sept
1,864Peak Premier in tracked matches
20Days played since 2026-08-28

Premier CS Rating

  • 160 below peak (1,391)
  • Next: Light Blue band at 5,000 — 3,769 to go

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 Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate32.2%38.2%39.9%7.7% short
Shot accuracy0.0%3.6%7.0%7.0% short
Kill/death ratio0.630.830.920.29 short
Match win rate36.3%40.2%42.3%6.0% short

This profile sits below the typical Light Blue band player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Light Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGDadelolPREMIER1,231 · Grey bandcsdb.gg/stats

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Performance scores

Aim50
Positioning52
Utility5

0–100 skill scores via Leetify.

Recent form

STEADY45–50–5Last 10045%Win rateWWWWLTLWLT

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating · +1.6pp headshot accuracy · −10ms 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

  • 4–1 · 80% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 8%
  • Avg reaction 709ms

Last 10

  • 5–3–2 · 50% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 8%
  • Avg reaction 626ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 7%
  • Avg reaction 630ms

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 (+2.6 against its own average).

Aim5.0
Utility0.5
Positioning5.2
Opening Duels2.2

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

s1mple

Plays most like s1mple 79% 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

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

Reaction time. 586ms 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

Aim5.0
Positioning5.2
Utility0.5
Mechanics5.0
Opening Duels1.4
Win Impact3.8

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-0.04−0.01
first ⅓ avg -0.03 → last ⅓ avg -0.04
Reaction time593ms+9ms
first ⅓ avg 585ms → last ⅓ avg 593ms
Headshot accuracy7.7%−3.9%
first ⅓ avg 11.6% → last ⅓ avg 7.7%

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 · 10–0 · ancient, 11 Sept →
67%Best headshot accuracy · 1–2 · cache, 10 Sept →
328msFastest reaction time · 9–1 · dust2, 23 Sept →
13–1Biggest win · inferno, 11 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W4Current streak
5–5In matches decided by ≤2 rounds
2Overtime games

Map breakdown

infernoBest map · 47% over 43nukeWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
infernoB4320–2347%-0.02
anubisC114–736%-0.01
dust2C104–640%-0.06
cacheD103–730%-0.05
mirageC73–443%-0.03
nukeD72–529%-0.06
office—43–175%-0.05
ancient—32–167%-0.02
vertigo—32–167%-0.02
train—11–0100%0.02
boulder—11–0100%0.04

Across the last 100 tracked matches.

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

Lifetime stats

8,281Lifetime kills
0.63K/D
673Matches
36.3%Match win rate
32.2%Headshot %
0.0%Shot accuracy
719MVPs
224Hours (in match)
563Bombs planted
69Bombs defused

Most-used weapons

M4A4 / M4A1-S3,048
AK-471,368
MP7940
AUG898
SG 553492
P2000 / USP-S322
P90247
Glock-18181
FAMAS157
Five-SeveN120

Lifetime map wins

1,269inferno
947dust2
595nuke
150vertigo
132office
81train

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.

7.5%Headshot accuracy
36.8%Accuracy (enemy spotted)
39.2%Spray accuracy
72.6%Counter-strafing
11.4°Preaim
586msReaction time
27.2%T opening success
41.4%CT opening success
0.04Enemies flashed / flash
0.0%Flash assists
3.93HE damage / grenade
0.10Flashes / 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 7.4918% — 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 0.0366 — 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 27.1778% — below the 40% mark we flag

Spend your practice time on Nuke

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.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–9-0.015%30 Sept →
dust213–8-0.0112%30 Sept →
inferno13–10-0.044%30 Sept →
anubis13–80.017%30 Sept →
dust20–13-0.1011%30 Sept →
ancient12–12-0.133%30 Sept →
mirage3–13-0.0710%30 Sept →
inferno13–50.018%30 Sept →
dust213–16-0.0110%30 Sept →
anubis12–120.1211%30 Sept →
nuke11–13-0.077%30 Sept →
nuke0–8-0.110%30 Sept →
inferno8–13-0.019%30 Sept →
cache5–13-0.066%30 Sept →
mirage13–8-0.062%30 Sept →
inferno13–2-0.0314%30 Sept →
nuke13–8-0.012%29 Sept →
cache4–13-0.069%29 Sept →
inferno13–40.096%29 Sept →
inferno8–13-0.018%29 Sept →
inferno11–00.049%28 Sept →
anubis6–13-0.034%27 Sept →
office13–8-0.0615%27 Sept →
train13–110.0210%27 Sept →
cache4–13-0.052%27 Sept →
ancient13–11-0.059%27 Sept →
mirage4–13-0.1011%27 Sept →
dust24–13-0.118%27 Sept →
inferno5–13-0.063%27 Sept →
nuke0–13-0.058%27 Sept →
vertigo6–13-0.0618%27 Sept →
anubis10–13-0.064%26 Sept →
inferno5–13-0.069%26 Sept →
inferno13–3-0.0111%26 Sept →
inferno0–10-0.0411%24 Sept →
boulder10–60.047%24 Sept →
dust29–13-0.0710%24 Sept →
inferno13–10-0.0010%24 Sept →
nuke7–13-0.096%24 Sept →
anubis6–13-0.0619%24 Sept →
cache2–13-0.0812%24 Sept →
inferno13–60.019%24 Sept →
inferno13–40.048%23 Sept →
mirage11–13-0.024%23 Sept →
nuke13–6-0.0210%23 Sept →
dust29–1-0.110%23 Sept →
inferno10–13-0.0112%23 Sept →
vertigo13–50.028%23 Sept →
vertigo13–9-0.0316%23 Sept →
inferno12–120.0210%21 Sept →
inferno11–13-0.0916%21 Sept →
anubis13–110.0210%20 Sept →
anubis7–13-0.014%20 Sept →
anubis6–13-0.027%20 Sept →
inferno13–40.037%14 Sept →
dust212–12-0.077%13 Sept →
cache6–13-0.0916%13 Sept →
anubis13–50.0016%13 Sept →
inferno13–3-0.0513%13 Sept →
inferno12–120.0313%12 Sept →
mirage14–160.0117%11 Sept →
inferno13–60.0111%11 Sept →
cache13–8-0.107%11 Sept →
inferno6–13-0.086%11 Sept →
ancient10–00.137%11 Sept →
cache7–130.008%11 Sept →
inferno13–10.038%11 Sept →
mirage6–30.0912%11 Sept →
inferno13–20.0513%11 Sept →
inferno5–13-0.1213%11 Sept →
inferno9–130.0211%10 Sept →
dust28–13-0.0614%10 Sept →
mirage13–10-0.059%10 Sept →
inferno13–5-0.037%10 Sept →
anubis3–13-0.049%10 Sept →
anubis13–2-0.0513%10 Sept →
cache13–6-0.0015%10 Sept →
cache1–2-0.0267%10 Sept →
inferno5–130.065%10 Sept →
dust213–11-0.0310%9 Sept →
inferno6–13-0.0811%9 Sept →
inferno8–13-0.087%9 Sept →
inferno3–90.1010%9 Sept →
inferno13–3-0.0415%6 Sept →
inferno7–13-0.0816%6 Sept →
inferno2–13-0.0815%6 Sept →
nuke2–13-0.075%6 Sept →
inferno9–13-0.078%6 Sept →
inferno13–20.1011%6 Sept →
office5–13-0.0414%6 Sept →
office13–5-0.024%4 Sept →
office13–10-0.0814%4 Sept →
cache13–10-0.008%30 Aug →
inferno8–13-0.049%30 Aug →
inferno13–6-0.0410%30 Aug →
inferno4–13-0.065%29 Aug →
inferno8–130.027%29 Aug →
inferno13–7-0.082%29 Aug →
inferno8–130.039%29 Aug →
inferno13–11-0.065%28 Aug →

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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