osk4r

osk4r — CS2 Stats

76561198331684548[U:1:371418820]Steam profile ↗2 game bans

1,019Tracked matches39%Win rate2020Tracked since
CSDB Rating6.4 SolidPositional Player
FaceitLevel 9Top 20.7% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 25 Sep 2026 (36 days ago). Ranks are recorded once per day this page is viewed.

+19Tracked matches · now 1,019
+10.7ppWin rate · 28.6% → 39.3%

Rating over time

57Days played since 2025-10-31

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Share this profile

CSDB.GGosk4rFACEITLevel 9STANDINGTop 20.7% of rankedcsdb.gg/stats

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Performance scores

Aim77
Positioning74
Utility69

0–100 skill scores via Leetify.

Recent form

STEADY38–57–5Last 10038%Win rateLWLLLWWLWL

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · −5.2pp headshot accuracy · −76ms reaction

Win rate 0pp 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

  • 1–4 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 16%
  • Avg reaction 477ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 15%
  • Avg reaction 487ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 18%
  • Avg reaction 525ms

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 (+1.9 against its own average).

Aim7.7
Utility6.9
Positioning7.4
Opening Duels3.6
Clutch4.2

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

NiKo

Plays most like NiKo 79% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

CSDB Rating breakdown

Aim7.7
Positioning7.4
Utility6.9
Mechanics5.9
Opening Duels5.3
Win Impact1.4

Composite 6.4/10 (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 rating0.05+0.04
first ⅓ avg 0.02 → last ⅓ avg 0.05
Reaction time526ms−58ms
first ⅓ avg 584ms → last ⅓ avg 526ms
Headshot accuracy17.6%−1.1%
first ⅓ avg 18.7% → last ⅓ avg 17.6%

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

0.34Best match rating · 9–2 · sanctum, 30 Jan →
67%Best headshot accuracy · 13–3 · inferno, 31 Oct →
359msFastest reaction time · 0–9 · inferno, 28 Jul →
13–3Biggest win · dust2, 6 Oct →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

infernoBest map · 50% over 8nukeWeakest map · 0% over 6
MapGradePlayedRecordWin rateAvg rating
mirageD3310–2330%0.05
dust2B199–1047%0.02
cacheC176–1135%0.02
infernoB84–450%0.01
anubisD62–433%0.02
nukeD60–60%-0.04
ancient—42–250%0.02
vertigo—32–167%0.07
shelter—11–0100%0.05
overpass—10–10%0.07
sanctum—11–0100%0.34
palacio—11–0100%-0.01

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (0% over 6). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

258Matches
59%Win rate
1.33Avg K/D
75.9ADR
42%Headshot %

Clutches & streaks

41%1v1 clutch win
28%1v2 clutch win
11Longest win streak

Recent Faceit resultsLWLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage9063%1.2015.0
Anubis2861%1.1816.0
Vertigo2268%1.6315.9
Dust21850%1.3019.1
Ancient1155%1.2017.3
Inferno425%0.6811.5
Overpass30%0.6611.7
Cache3100%1.4417.0

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.

17.4%Headshot accuracy
34.9%Accuracy (enemy spotted)
39.3%Spray accuracy
76.4%Counter-strafing
8.6°Preaim
525msReaction time
53.2%T opening success
49.3%CT opening success
0.69Enemies flashed / flash
8.6%Flash assists
14.65HE damage / grenade
11.16Flashes / 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.

0% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis4–130.0522%18 Oct →
dust213–80.046%10 Oct →
nuke10–13-0.0124%10 Oct →
anubis6–130.0016%10 Oct →
dust25–13-0.0616%10 Oct →
cache8–70.0722%10 Oct →
mirage13–110.139%10 Oct →
anubis4–13-0.0015%9 Oct →
mirage13–50.1112%8 Oct →
mirage11–130.1914%6 Oct →
dust213–30.1213%6 Oct →
ancient3–130.0618%5 Oct →
cache13–50.099%27 Sept →
mirage10–130.0623%27 Sept →
cache3–13-0.0336%21 Sept →
mirage12–120.0016%20 Sept →
cache12–120.0324%20 Sept →
mirage13–110.2320%19 Sept →
dust20–13-0.0627%19 Sept →
dust213–80.1719%19 Sept →
mirage5–20.0917%19 Sept →
ancient13–40.0512%18 Sept →
mirage3–13-0.0421%7 Sept →
vertigo9–60.2119%5 Sept →
mirage13–100.0823%4 Sept →
mirage8–130.0316%29 Aug →
cache7–130.0614%27 Aug →
mirage6–13-0.0316%27 Aug →
cache9–130.0313%25 Aug →
mirage4–130.0315%23 Aug →
mirage7–130.0219%21 Aug →
cache8–130.0318%19 Aug →
mirage11–130.0417%18 Aug →
nuke7–13-0.0714%17 Aug →
vertigo7–9-0.075%15 Aug →
cache5–130.0211%2 Aug →
inferno3–13-0.0420%1 Aug →
cache7–13-0.0510%1 Aug →
anubis13–8-0.0212%1 Aug →
dust23–13-0.0225%1 Aug →
cache3–130.0212%31 Jul →
mirage4–130.0525%31 Jul →
dust27–130.1015%31 Jul →
dust25–90.0723%31 Jul →
shelter13–30.0524%30 Jul →
inferno0–9-0.0313%28 Jul →
nuke8–80.0730%27 Jul →
cache7–130.0418%27 Jul →
inferno9–60.0922%27 Jul →
mirage13–90.0518%26 Jul →
mirage10–13-0.0711%14 Jul →
mirage10–130.0320%13 Jul →
dust213–110.0618%10 Jul →
mirage9–130.0617%27 Jun →
dust29–130.0219%26 Jun →
cache13–90.1111%26 Jun →
cache13–110.0010%21 Jun →
mirage7–13-0.048%21 Jun →
dust25–13-0.0311%20 Jun →
mirage4–130.0914%20 Jun →
mirage13–160.0614%20 Jun →
ancient13–50.0020%14 Jun →
mirage13–100.028%8 Jun →
mirage4–130.0712%7 Jun →
dust28–130.0320%6 Jun →
dust213–7-0.0018%29 May →
dust213–100.0417%29 May →
overpass2–130.075%29 May →
cache13–8-0.047%23 May →
cache8–130.039%9 May →
inferno9–50.1520%9 May →
ancient5–13-0.0421%29 Apr →
dust25–13-0.0729%29 Apr →
cache13–8-0.0324%29 Apr →
cache6–13-0.0535%28 Apr →
inferno3–9-0.1412%17 Mar →
inferno4–90.0120%17 Mar →
anubis13–80.0511%16 Mar →
dust213–5-0.0516%16 Mar →
mirage6–130.0314%15 Mar →
sanctum9–20.3417%30 Jan →
mirage12–12-0.0212%30 Jan →
dust22–13-0.029%27 Dec →
nuke5–9-0.058%27 Dec →
dust26–13-0.0717%27 Dec →
mirage13–30.0821%14 Dec →
palacio13–7-0.0119%14 Dec →
mirage15–15-0.0111%7 Dec →
mirage10–130.0435%1 Dec →
mirage10–130.0517%17 Nov →
mirage13–50.0917%17 Nov →
mirage13–30.1922%17 Nov →
inferno13–110.0719%9 Nov →
anubis9–130.0423%9 Nov →
vertigo13–50.0813%9 Nov →
mirage3–130.0015%9 Nov →
dust213–110.0524%9 Nov →
inferno13–3-0.0167%31 Oct →
nuke6–9-0.118%31 Oct →
nuke6–9-0.0925%31 Oct →

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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