deeK

deeK — CS2 Stats

76561197960432287[U:1:166559]Steam profile ↗✓ No bans

1,513Tracked matches69%Win rate2020Tracked since
CSDB Rating6.5 SolidPositional Player
CSDB Leaderboard#44456 of 253372 tracked
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 22,800 +2,837 13 Mar – 12 Jul · 18 days played
19,96325,108peak 25,10813 Mar12 Jul
25,108Peak Premier in tracked matches
43Days played since 2025-03-11

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim81
Positioning57
Utility23

0–100 skill scores via Leetify.

Recent form

STEADY58–39–3Last 10058%Win rateLWWWLWWLWW

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · +4.3pp headshot accuracy · +33ms 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

  • 3–2 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 24%
  • Avg reaction 608ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 29%
  • Avg reaction 594ms

Last 20

  • 15–5 · 75% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 27%
  • Avg reaction 577ms

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).

Aim8.1
Utility2.3
Positioning5.7
Opening Duels4.5
Clutch3.4

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 83% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower opening-duel success; 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

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. 592ms 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

Aim8.1
Positioning5.7
Utility2.3
Mechanics8.3
Opening Duels3.4
Win Impact10.0

Composite 6.5/10 (Solid), 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 rating0.01−0.01
first ⅓ avg 0.02 → last ⅓ avg 0.01
Reaction time590ms+27ms
first ⅓ avg 564ms → last ⅓ avg 590ms
Headshot accuracy26.2%+4.2%
first ⅓ avg 22.0% → last ⅓ avg 26.2%

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

0.16Best match rating · 13–8 · ancient, 28 Mar →
50%Best headshot accuracy · 13–11 · ancient, 1 Sept →
438msFastest reaction time · 8–13 · ancient, 17 Jul →
13–1Biggest win · ancient, 25 Mar →

Across the last 100 tracked matches.

Highlights

8Longest win streak
13–7In matches decided by ≤2 rounds
18Overtime games

Map breakdown

ancientBest map · 74% over 23nukeWeakest map · 40% over 15
MapGradePlayedRecordWin rateAvg rating
ancientS2317–674%0.02
infernoA2213–959%0.00
nukeC156–940%0.02
mirageB157–847%0.01
dust2C104–640%-0.00
anubisA95–456%0.01
train—44–0100%0.06
cache—11–0100%-0.02
overpass—11–0100%0.08

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (40% over 15). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

816Matches
51%Win rate
1.07Avg K/D
73.8ADR
51%Headshot %

Clutches & streaks

37%1v1 clutch win
20%1v2 clutch win
9Longest win streak

Recent Faceit resultsWWWWL

MapMatchesWin rateAvg K/DAvg kills
Ancient17646%1.0715.7
Inferno17559%1.1615.4
Mirage13351%1.0115.0
Nuke13160%1.1415.5
Anubis10743%1.0015.1
Dust25740%0.9314.2
Train1040%0.9314.3
Vertigo933%0.9414.7

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.

25.5%Headshot accuracy
32.5%Accuracy (enemy spotted)
33.5%Spray accuracy
87.3%Counter-strafing
8.2°Preaim
592msReaction time
43.1%T opening success
44.3%CT opening success
0.54Enemies flashed / flash
5.5%Flash assists
8.95HE damage / grenade
9.15Flashes / match

Recommended for you

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.

40% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis9–13-0.0622%11 Jul →
cache19–17-0.0215%11 Jul →
nuke13–40.0233%11 Jul →
ancient16–130.0027%13 Sept →
dust29–130.0024%13 Sept →
nuke13–110.0322%13 Sept →
nuke13–110.0438%5 Sept →
dust27–13-0.0733%1 Sept →
ancient13–11-0.0150%1 Sept →
ancient13–80.1023%1 Sept →
inferno13–70.0120%1 Sept →
ancient13–100.0439%1 Sept →
inferno13–8-0.0515%21 Jul →
nuke13–90.0513%21 Jul →
ancient13–110.0128%21 Jul →
inferno6–13-0.0322%17 Jul →
ancient13–100.0627%17 Jul →
overpass13–40.0829%17 Jul →
ancient8–13-0.0330%17 Jul →
inferno13–50.0421%15 Jul →
nuke6–13-0.0229%15 Jul →
nuke13–70.0546%14 Jul →
ancient8–130.0020%12 Jul →
anubis13–60.0333%12 Jul →
anubis19–16-0.0019%10 Jul →
inferno13–5-0.0113%10 Jul →
mirage13–160.0522%5 Jul →
nuke7–130.0112%2 Jul →
anubis13–4-0.0319%1 Jul →
mirage12–120.0727%30 Jun →
mirage11–130.0545%30 Jun →
inferno16–130.0630%30 Jun →
nuke3–13-0.0819%30 Jun →
mirage13–20.0323%28 Jun →
mirage2–6-0.0132%28 Jun →
ancient19–16-0.0015%27 Jun →
nuke6–13-0.0220%27 Jun →
inferno11–13-0.0217%22 Jun →
dust29–130.0116%21 Jun →
anubis13–5-0.0027%31 May →
inferno1–13-0.0517%29 May →
nuke13–160.0215%29 May →
anubis18–220.0331%25 Apr →
nuke5–13-0.0216%25 Apr →
ancient13–50.0827%25 Apr →
inferno10–130.0230%20 Apr →
ancient13–40.0738%20 Apr →
inferno16–14-0.0318%20 Apr →
ancient5–13-0.0710%16 Apr →
ancient8–13-0.119%16 Apr →
inferno13–11-0.0319%6 Apr →
train13–110.0025%4 Apr →
ancient13–70.0318%4 Apr →
mirage13–60.0528%4 Apr →
inferno13–40.0418%4 Apr →
ancient11–13-0.0433%4 Apr →
inferno13–90.0627%3 Apr →
nuke13–160.0725%3 Apr →
nuke13–110.0516%3 Apr →
dust213–90.0223%2 Apr →
mirage9–130.0122%29 Mar →
anubis6–130.0424%28 Mar →
nuke15–150.0321%28 Mar →
ancient13–80.1625%28 Mar →
nuke11–130.0217%27 Mar →
ancient13–90.0715%27 Mar →
inferno7–13-0.0521%27 Mar →
train13–90.0132%27 Mar →
inferno13–20.0026%26 Mar →
train13–60.1539%26 Mar →
ancient13–20.1228%26 Mar →
ancient13–10-0.0430%26 Mar →
dust213–100.0821%26 Mar →
ancient13–10.0111%25 Mar →
inferno8–13-0.048%24 Mar →
dust213–50.0024%23 Mar →
dust216–19-0.0526%23 Mar →
mirage13–9-0.0322%23 Mar →
inferno12–160.0721%22 Mar →
mirage16–140.0111%22 Mar →
inferno15–15-0.0229%21 Mar →
inferno6–13-0.0618%19 Mar →
dust23–13-0.098%19 Mar →
mirage13–100.0032%19 Mar →
ancient13–16-0.0118%19 Mar →
ancient13–70.0733%19 Mar →
mirage14–16-0.0316%18 Mar →
dust210–13-0.0221%18 Mar →
mirage13–4-0.0216%18 Mar →
anubis13–110.1121%17 Mar →
mirage13–30.0731%17 Mar →
dust213–110.0824%17 Mar →
inferno13–110.1135%17 Mar →
inferno13–20.0218%16 Mar →
inferno13–100.0318%13 Mar →
ancient13–100.0314%13 Mar →
mirage14–16-0.0028%13 Mar →
mirage7–13-0.0214%13 Mar →
train13–80.0829%12 Mar →
anubis11–13-0.009%11 Mar →

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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