ShockeDC

ShockeDC — CS2 Stats

IM76561198119033465[U:1:158767737]Steam profile ↗✓ No bans

213Tracked matches34%Win rate2024Tracked since
947Hours in CS7Hrs last 2 wks
CSDB Rating5.7 SolidAll-Rounder
Premier CS Rating22,286Top 50% of 215,386 CSDB-tracked playersPink band · top ~6% of ranked players (population est.)
CSDB Leaderboard#53443 of 261515 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 4 Nov 2026 (10 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 22,286 → 22,286
+1Tracked matches · now 213
0.0ppWin rate · 34.5% → 34.5%

Rating over time

Premier CS Rating: 22,286 +5,180 16 Mar – 4 Nov · 37 days played
16,76822,403peak 22,40316 Mar4 Nov
22,508Peak Premier in tracked matches
54Days played since 2026-03-16

Premier CS Rating

  • 117 below peak (22,403)
  • +360 over 30 days · steady
  • +373 over 90 days
  • Next: Red band at 25,000 — 2,714 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Pink band first seen 2026-09-30
  • Purple band first seen 2026-09-30

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 Pink band among CSDB-tracked players (n=38,294), 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 playerPink band medianRed band medianvs Red band
Headshot rate42.1%46.9%49.3%7.2% short
Shot accuracy2.1%13.0%13.4%11.3% short
Kill/death ratio1.251.081.12above
Match win rate44.2%46.7%48.5%4.3% short

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

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

Share this profile

CSDB.GGShockeDCPREMIER22,286 · Pink bandcsdb.gg/stats

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Performance scores

Aim73
Positioning60
Utility57

0–100 skill scores via Leetify.

Recent form

COLD45–53–2Last 10045%Win rateLLLLLLLWWL

Last 10 vs previous 10: −20pp win rate · +0.02 avg rating · +2.3pp headshot accuracy · −36ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 0–5 · 0% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 21%
  • Avg reaction 480ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 22%
  • Avg reaction 535ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 21%
  • Avg reaction 552ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim7.3
Utility5.7
Positioning6.0
Opening Duels4.7
Clutch6.0

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

m0NESY

Plays most like m0NESY 91% 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. 556ms 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

Aim7.3
Positioning6.0
Utility5.7
Mechanics5.1
Opening Duels6.2
Win Impact0.0

Composite 5.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02−0.04
first ⅓ avg 0.06 → last ⅓ avg 0.02
Reaction time573ms−77ms
first ⅓ avg 650ms → last ⅓ avg 573ms
Headshot accuracy23.0%−0.6%
first ⅓ avg 23.6% → last ⅓ avg 23.0%

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 · 13–2 · mirage, 19 Apr →
50%Best headshot accuracy · 2–13 · dust2, 21 Jul →
414msFastest reaction time · 10–13 · ancient, 14 Sept →
13–0Biggest win · dust2, 10 Jun →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L7Current streak
8–10In matches decided by ≤2 rounds
4Overtime games

Map breakdown

nukeBest map · 60% over 5mirageWeakest map · 38% over 26
MapGradePlayedRecordWin rateAvg rating
dust2B4321–2249%0.05
mirageC2610–1638%0.06
infernoA116–555%0.05
anubisB63–350%0.04
nukeA53–260%0.03
ancient—40–40%-0.00
cache—20–20%-0.04
overpass—22–0100%0.03
vertigo—10–10%-0.02

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (38% over 26). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

28,666Lifetime kills
1.25K/D · Top 25% of Pink band
1,501Matches
44.2%Match win rate
42.1%Headshot %
2.1%Shot accuracy
3,662MVPs
513Hours (in match)
1,694Bombs planted
357Bombs defused

Most-used weapons

Lifetime map wins

8,895dust2
740inferno
459nuke
117train
73vertigo
47office
17ar_shoots
13dust

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

Faceit stats

Combat

6Matches
33%Win rate
0.62Avg K/D
57.7ADR
36%Headshot %

Clutches & streaks

50%1v1 clutch win
0%1v2 clutch win
2Longest win streak

Recent Faceit resultsWLLLL

MapMatchesWin rateAvg K/DAvg kills
Dust2333%0.789.3
Mirage250%0.528.5
Inferno10%0.365.0

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.

21.6%Headshot accuracy
35.1%Accuracy (enemy spotted)
41.6%Spray accuracy
73.0%Counter-strafing
10.7°Preaim
556msReaction time
53.5%T opening success
55.9%CT opening success
0.67Enemies flashed / flash
5.2%Flash assists
8.14HE damage / grenade
14.86Flashes / match

Recommended for you

Spend your practice time on Mirage

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

38% win rate across 26 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust26–13-0.0019%4 Nov →
cache10–13-0.0015%4 Nov →
dust211–130.1224%3 Nov →
dust23–130.0022%17 Oct →
ancient9–130.0225%17 Oct →
ancient5–13-0.0825%17 Oct →
dust28–130.1231%15 Oct →
dust213–100.0221%5 Oct →
dust213–30.1118%23 Sept →
mirage11–130.0321%21 Sept →
mirage6–130.0329%18 Sept →
dust213–20.0128%17 Sept →
dust27–130.0427%17 Sept →
dust29–1-0.0229%17 Sept →
inferno9–130.0916%14 Sept →
ancient10–130.0616%14 Sept →
nuke13–11-0.049%14 Sept →
dust213–90.0120%14 Sept →
nuke2–13-0.089%14 Sept →
dust26–13-0.0315%11 Sept →
mirage11–13-0.0315%11 Sept →
mirage13–7-0.0023%6 Sept →
cache4–13-0.0924%1 Sept →
inferno0–13-0.0526%1 Sept →
mirage12–160.0523%31 Aug →
ancient11–13-0.0121%3 Aug →
mirage13–90.0240%31 Jul →
dust213–110.0226%31 Jul →
dust212–120.1420%25 Jul →
dust213–90.0119%25 Jul →
dust22–13-0.0850%21 Jul →
dust213–90.1827%17 Jul →
dust29–130.0028%17 Jul →
inferno16–130.1114%16 Jul →
mirage7–130.0421%13 Jul →
dust213–50.0917%7 Jul →
dust21–130.0116%5 Jul →
overpass13–60.0125%2 Jul →
anubis4–130.0417%1 Jul →
dust213–9-0.0418%27 Jun →
inferno13–110.0720%27 Jun →
mirage3–13-0.0423%27 Jun →
mirage6–130.0029%27 Jun →
inferno13–60.0928%27 Jun →
dust213–100.0336%26 Jun →
dust29–130.0630%26 Jun →
mirage13–160.1634%26 Jun →
mirage9–00.1821%26 Jun →
nuke5–130.1821%26 Jun →
dust28–20.1114%26 Jun →
mirage8–13-0.0120%21 Jun →
dust213–70.0720%19 Jun →
dust28–130.1024%15 Jun →
mirage13–90.1818%11 Jun →
dust24–130.0833%10 Jun →
dust213–00.1114%10 Jun →
dust213–80.0734%4 Jun →
dust210–130.0125%3 Jun →
anubis7–130.0224%27 May →
dust213–100.0220%27 May →
anubis3–130.0445%27 May →
dust210–130.0724%25 May →
dust23–13-0.0429%25 May →
mirage11–13-0.0422%25 May →
dust213–10-0.0420%25 May →
mirage13–110.1027%24 May →
inferno13–50.0923%24 May →
nuke13–30.0630%24 May →
inferno10–13-0.0131%24 May →
nuke13–70.0120%24 May →
dust210–130.0432%24 May →
dust213–110.1941%5 May →
mirage8–130.1625%3 May →
dust213–90.0927%1 May →
dust22–130.0220%1 May →
mirage11–130.1626%1 May →
mirage13–80.1024%28 Apr →
mirage6–130.0619%28 Apr →
anubis13–70.0520%21 Apr →
mirage13–20.2126%19 Apr →
mirage11–130.0822%19 Apr →
mirage13–7-0.0524%18 Apr →
mirage9–13-0.0131%15 Apr →
mirage13–20.0723%15 Apr →
dust29–130.0432%15 Apr →
anubis13–110.0122%15 Apr →
dust213–110.1226%13 Apr →
overpass13–30.0520%13 Apr →
inferno16–130.0623%12 Apr →
dust213–20.0511%9 Apr →
vertigo12–12-0.0213%9 Apr →
dust211–130.0322%9 Apr →
dust20–110.0111%8 Apr →
inferno6–130.0622%8 Apr →
inferno8–130.0127%2 Apr →
anubis13–110.0627%1 Apr →
mirage13–40.1730%22 Mar →
dust211–130.0313%18 Mar →
inferno13–90.0515%16 Mar →
mirage11–13-0.0426%16 Mar →

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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