owche

owche — CS2 Stats

76561197964521475[U:1:4255747]Steam profile ↗✓ No bans

546Tracked matches63%Win rate2020Tracked since
CSDB Rating5.6 SolidPositional Player
FaceitLevel 5Top 67.6% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGowcheFACEITLevel 5STANDINGTop 67.6% of rankedcsdb.gg/stats

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Performance scores

Aim56
Positioning56
Utility43

0–100 skill scores via Leetify.

Recent form

STEADY57–36–7Last 10057%Win rateTWLWWLTWWL

Last 10 vs previous 10: +10pp win rate · +0.00 avg rating · +5.0pp headshot accuracy · +5ms 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

  • 3–1–1 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 31%
  • Avg reaction 657ms

Last 10

  • 5–3–2 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 27%
  • Avg reaction 676ms

Last 20

  • 9–8–3 · 45% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 25%
  • Avg reaction 673ms

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 (+1.5 against its own average).

Aim5.6
Utility4.3
Positioning5.6
Opening Duels2.4

Strong CT-side openerLimited 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

NiKo

Plays most like NiKo 83% playstyle similarity

Most alike: positioning profile, utility contribution.

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

T-side openings. Opening success drops from 47% on CT to 28% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 649ms 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

Aim5.6
Positioning5.6
Utility4.3
Mechanics6.5
Opening Duels2.2
Win Impact9.3

Composite 5.6/10 (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 rating-0.01−0.02
first ⅓ avg 0.01 → last ⅓ avg -0.01
Reaction time656ms+14ms
first ⅓ avg 641ms → last ⅓ avg 656ms
Headshot accuracy23.8%+0.4%
first ⅓ avg 23.4% → last ⅓ avg 23.8%

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

0.10Best match rating · 13–3 · vertigo, 20 Mar →
45%Best headshot accuracy · 7–13 · nuke, 24 Jul →
430msFastest reaction time · 10–13 · dust2, 7 Jan →
13–0Biggest win · train, 24 May →

Across the last 100 tracked matches.

Highlights

5Longest win streak
7–5In matches decided by ≤2 rounds

Map breakdown

mirageBest map · 75% over 8dust2Weakest map · 35% over 17
MapGradePlayedRecordWin rateAvg rating
dust2C176–1135%-0.01
nukeB147–750%0.00
infernoA127–558%-0.02
ancientA117–464%-0.01
cacheC83–538%-0.01
mirageS86–275%0.02
anubisS86–275%0.00
trainB84–450%-0.03
overpassA53–260%0.01
vertigo—33–0100%0.02
grail—32–167%-0.01
agency—11–0100%0.02
jura—11–0100%-0.02
office—11–0100%-0.02

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (35% over 17). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

23.2%Headshot accuracy
29.4%Accuracy (enemy spotted)
31.9%Spray accuracy
79.2%Counter-strafing
10.8°Preaim
649msReaction time
27.8%T opening success
47.3%CT opening success
0.52Enemies flashed / flash
5.7%Flash assists
8.78HE damage / grenade
2.85Flashes / 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 2.8451 — 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 27.8143% — below the 40% mark we flag

Spend your practice time on Dust 2

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

35% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache12–12-0.0139%8 Aug →
cache13–70.0429%2 Aug →
nuke7–13-0.0445%24 Jul →
dust213–6-0.0121%19 Jul →
nuke13–60.0419%19 Jul →
inferno3–13-0.0329%19 Jul →
cache12–12-0.0419%18 Jul →
vertigo13–7-0.0423%18 Jul →
cache13–20.0440%18 Jul →
mirage3–13-0.0410%18 Jul →
dust213–110.0524%18 Jul →
dust23–13-0.0023%15 Jul →
inferno13–6-0.0117%15 Jul →
cache12–12-0.0318%15 Jul →
cache6–13-0.0830%15 Jul →
dust27–13-0.0526%11 Jul →
nuke13–80.0520%11 Jul →
mirage13–50.0521%11 Jul →
cache3–50.0027%11 Jul →
inferno6–13-0.0620%11 Jul →
overpass13–90.0031%11 Jul →
anubis13–9-0.0114%11 Jul →
dust213–11-0.0732%10 Jul →
ancient11–130.0323%4 Jul →
inferno13–4-0.1019%4 Jul →
cache8–20.0115%4 Jul →
inferno13–11-0.0213%3 May →
dust210–130.0113%7 Jan →
overpass13–10-0.0016%21 Sept →
dust213–110.0222%21 Sept →
overpass7–130.0123%31 Jul →
overpass13–60.0322%31 Jul →
train5–130.0241%21 Jun →
nuke4–13-0.0319%20 Jun →
nuke13–9-0.0828%28 May →
mirage13–9-0.0219%28 May →
train13–110.0120%24 May →
train13–00.0228%24 May →
nuke10–20.0514%23 May →
ancient8–13-0.039%16 May →
agency13–60.0223%15 May →
grail13–10-0.0926%15 May →
anubis8–13-0.0418%11 May →
anubis13–50.0222%10 May →
train13–6-0.0227%10 May →
jura13–11-0.0212%10 May →
nuke9–13-0.0620%10 May →
grail13–90.0221%8 May →
grail5–130.0222%8 May →
ancient13–11-0.0322%3 May →
nuke6–13-0.0424%3 May →
inferno13–8-0.0222%3 May →
vertigo13–70.0124%3 May →
train5–13-0.0916%3 May →
dust21–13-0.0125%3 May →
ancient10–13-0.0125%2 May →
dust212–120.0232%2 May →
inferno11–13-0.0322%2 May →
train9–13-0.0326%2 May →
inferno7–130.0336%1 May →
nuke8–130.0029%29 Apr →
ancient13–8-0.0323%29 Apr →
ancient10–13-0.0338%25 Apr →
mirage13–20.0129%25 Apr →
dust212–120.0324%25 Apr →
nuke13–40.0022%25 Apr →
inferno13–50.0022%15 Apr →
dust213–90.0230%15 Apr →
dust28–13-0.0522%13 Apr →
nuke12–12-0.0326%12 Apr →
mirage13–3-0.0038%12 Apr →
nuke13–70.0924%12 Apr →
dust211–130.0928%10 Apr →
dust28–13-0.0618%6 Apr →
nuke9–130.0125%6 Apr →
office13–6-0.0233%6 Apr →
anubis13–40.0310%6 Apr →
mirage13–10.0938%6 Apr →
ancient13–5-0.0321%6 Apr →
dust25–13-0.0413%6 Apr →
anubis13–4-0.0013%3 Apr →
ancient13–6-0.0216%3 Apr →
mirage11–130.0328%3 Apr →
train3–13-0.0345%30 Mar →
inferno4–13-0.0322%30 Mar →
mirage13–40.0725%30 Mar →
anubis13–50.0727%29 Mar →
ancient13–9-0.0015%29 Mar →
dust213–7-0.0410%23 Mar →
inferno13–5-0.0323%23 Mar →
dust27–13-0.0535%22 Mar →
inferno13–60.0820%22 Mar →
overpass12–120.0227%22 Mar →
train13–10-0.0714%22 Mar →
nuke7–10.0915%22 Mar →
ancient13–70.0928%22 Mar →
anubis7–13-0.0124%21 Mar →
vertigo13–30.1024%20 Mar →
ancient13–9-0.0219%20 Mar →
anubis13–7-0.0417%20 Mar →

Match data via Leetify.

Recent teammates

Milestones

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

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