scapa

scapa — CS2 Stats

76561197975270848[U:1:15005120]Steam profile ↗✓ No bans

851Tracked matches50%Win rate2020Tracked since
CSDB Rating5.5 SolidSupport
FaceitLevel 5Top 67.6% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

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

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Performance scores

Aim57
Positioning53
Utility64

0–100 skill scores via Leetify.

Recent form

COLD51–46–3Last 10051%Win rateLWLLLWLWLL

Last 10 vs previous 10: −20pp win rate · −0.03 avg rating · −1.1pp headshot accuracy · −27ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 20%
  • Avg reaction 652ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 19%
  • Avg reaction 595ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 20%
  • Avg reaction 608ms

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: Support — Utility contribution stands above the rest of this profile (+2.2 against its own average).

Aim5.7
Utility6.4
Positioning5.3
Opening Duels1.9
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

iM

Plays most like iM 74% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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

CT openings. Opening success drops from 56% on T to 36% on CT — first contacts on the defending side are being lost.

Reaction time. 613ms 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

Aim5.7
Positioning5.3
Utility6.4
Mechanics6.0
Opening Duels4.0
Win Impact5.0

Composite 5.5/10 (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 rating-0.02−0.01
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time614ms−91ms
first ⅓ avg 705ms → last ⅓ avg 614ms
Headshot accuracy20.8%+1.9%
first ⅓ avg 18.9% → last ⅓ avg 20.8%

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 · dust2, 15 Jul →
41%Best headshot accuracy · 13–8 · cache, 14 Sept →
430msFastest reaction time · 13–10 · inferno, 5 Oct →
13–0Biggest win · dust2, 22 Apr →

Across the last 100 tracked matches.

Highlights

5Longest win streak
10–6In matches decided by ≤2 rounds
8Overtime games

Map breakdown

ancientBest map · 59% over 22anubisWeakest map · 40% over 5
MapGradePlayedRecordWin rateAvg rating
dust2C2511–1444%-0.01
ancientA2213–959%-0.00
nukeA1810–856%-0.00
infernoB179–853%-0.03
anubisC52–340%-0.01
cache—33–0100%0.04
brewery—30–30%-0.04
dogtown—31–233%0.03
overpass—21–150%0.01
vertigo—11–0100%0.02
train—10–10%-0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (40% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

855Matches
51%Win rate
0.97Avg K/D
72.8ADR
41%Headshot %

Clutches & streaks

37%1v1 clutch win
15%1v2 clutch win
9Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Ancient7450%0.9414.2
Nuke6664%1.0715.1
Dust25944%0.9014.3
Inferno3850%0.9213.8
Anubis3330%0.8914.9
Mirage650%1.3614.7
Vertigo560%0.7511.4
Cache475%1.2120.0

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.

20.7%Headshot accuracy
32.0%Accuracy (enemy spotted)
34.8%Spray accuracy
77.1%Counter-strafing
11.7°Preaim
613msReaction time
55.5%T opening success
36.2%CT opening success
0.70Enemies flashed / flash
12.1%Flash assists
10.09HE damage / grenade
8.74Flashes / 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. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 36.2433% — below the 40% mark we flag

Spend your practice time on Anubis

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 5 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust211–13-0.0523%18 Oct →
ancient13–8-0.059%18 Oct →
inferno8–13-0.0726%18 Oct →
nuke2–13-0.1332%18 Oct →
dust22–13-0.0610%16 Oct →
ancient13–8-0.0318%16 Oct →
nuke9–13-0.0619%16 Oct →
ancient13–110.0519%16 Oct →
inferno4–13-0.0511%16 Oct →
anubis7–13-0.0626%16 Oct →
dust25–13-0.0618%13 Oct →
inferno7–13-0.0738%13 Oct →
dust213–10-0.0316%13 Oct →
ancient10–13-0.0310%13 Oct →
dust216–140.0522%9 Oct →
inferno13–9-0.0913%9 Oct →
ancient7–13-0.0122%9 Oct →
cache13–110.0725%9 Oct →
ancient7–13-0.0116%9 Oct →
inferno13–10-0.0123%6 Oct →
dust213–110.0226%6 Oct →
ancient11–13-0.027%6 Oct →
cache13–70.0121%5 Oct →
inferno13–10-0.0238%5 Oct →
ancient7–13-0.1014%5 Oct →
dust213–90.0116%5 Oct →
nuke11–13-0.0214%5 Oct →
cache13–80.0441%14 Sept →
inferno13–60.0334%14 Sept →
vertigo13–90.0215%14 Sept →
nuke13–60.0221%14 Sept →
nuke13–80.0319%12 Sept →
dust29–13-0.0623%12 Sept →
nuke13–50.0721%1 Sept →
inferno13–50.0115%23 Oct →
ancient13–80.0315%23 Oct →
dust23–110.0237%23 Oct →
nuke13–90.0420%23 Oct →
overpass13–10.0429%23 Oct →
ancient10–130.0120%23 Oct →
nuke9–13-0.0118%30 Jul →
overpass11–13-0.0116%30 Jul →
dust213–30.1021%15 Jul →
ancient13–20.0822%10 Jul →
nuke13–60.0521%19 May →
ancient13–100.0315%19 May →
brewery8–80.0320%9 May →
dogtown9–70.0416%9 May →
dogtown8–80.0624%9 May →
dogtown1–90.000%9 May →
brewery4–9-0.1315%9 May →
brewery4–9-0.0222%9 May →
dust211–130.0323%27 Apr →
ancient13–60.0435%23 Apr →
inferno13–9-0.0322%23 Apr →
dust212–12-0.0515%22 Apr →
dust213–0-0.0223%22 Apr →
ancient12–16-0.0131%7 Apr →
nuke19–170.0415%7 Apr →
ancient9–13-0.0420%7 Apr →
inferno6–13-0.0027%7 Apr →
nuke11–13-0.0116%6 Apr →
inferno8–13-0.0019%6 Apr →
ancient19–16-0.0121%6 Apr →
inferno10–13-0.0220%6 Apr →
dust213–11-0.0323%2 Apr →
ancient3–13-0.0211%2 Apr →
dust213–30.0636%2 Apr →
nuke22–180.0316%2 Apr →
inferno13–16-0.0415%23 Mar →
dust210–13-0.0321%23 Mar →
inferno13–100.0115%17 Mar →
dust27–130.0131%28 Feb →
ancient13–90.0126%28 Feb →
train9–13-0.028%15 Feb →
dust213–80.0223%15 Feb →
nuke8–13-0.0117%15 Feb →
dust210–13-0.0519%15 Feb →
anubis13–40.0513%10 Feb →
ancient16–14-0.0417%10 Feb →
dust213–10-0.0616%10 Feb →
dust25–13-0.0431%10 Feb →
ancient13–80.0822%2 Feb →
nuke7–13-0.0921%2 Feb →
inferno13–11-0.0413%2 Feb →
nuke13–90.0115%2 Feb →
anubis8–13-0.0014%2 Feb →
ancient13–11-0.0114%2 Feb →
inferno16–12-0.0222%5 Jan →
dust28–13-0.0327%5 Jan →
ancient13–6-0.0312%4 Jan →
inferno4–13-0.0718%4 Jan →
dust213–80.0421%4 Jan →
dust27–13-0.0810%4 Jan →
dust28–13-0.0516%4 Jan →
nuke13–9-0.0012%3 Jan →
anubis3–13-0.0318%3 Jan →
anubis13–10-0.0014%3 Jan →
nuke13–70.0724%3 Jan →
nuke4–13-0.0630%22 Dec →

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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