Claudia Black

Claudia Black — CS2 Stats

IS76561198211396032[U:1:251130304]Steam profile ↗✓ No bans

1,926Tracked matches38%Win rate2021Tracked since
3,194Hours in CS6Hrs last 2 wks
CSDB Rating5.7 SolidPositional Player
FaceitLevel 3Top 90.6% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches16——
Win rate38%——
K/D1.05——
Headshot %47%——

Measured 11 Sep 2026 → 14 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 3 among CSDB-tracked players (n=10,231), 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 playerLevel 3 medianLevel 4 medianvs Level 4
Headshot rate42.2%41.8%42.7%meets
Shot accuracy10.8%12.2%11.3%0.5% short
Kill/death ratio1.170.980.99above
Match win rate48.7%43.3%43.9%above

This profile matches the typical Level 4 player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGClaudia BlackFACEITLevel 3STANDINGTop 90.6% of rankedcsdb.gg/stats

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Performance scores

Aim74
Positioning63
Utility45

0–100 skill scores via Leetify.

Recent form

COLD41–46–13Last 10041%Win rateTLLLLTLWLW

Last 10 vs previous 10: −10pp win rate · −0.04 avg rating · +2.0pp headshot accuracy · +34ms 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

  • 0–4–1 · 0% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 24%
  • Avg reaction 639ms

Last 10

  • 2–6–2 · 20% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 19%
  • Avg reaction 562ms

Last 20

  • 5–12–3 · 25% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 18%
  • Avg reaction 545ms

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 (+2.5 against its own average).

Aim7.4
Utility4.5
Positioning6.3
Opening Duels4.4
Clutch0.0

Limited 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

donk

Plays most like donk 95% 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

Reaction time. 552ms 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

Aim7.4
Positioning6.3
Utility4.5
Mechanics6.8
Opening Duels4.0
Win Impact1.2

Composite 5.7/10 (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+0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time562ms−47ms
first ⅓ avg 609ms → last ⅓ avg 562ms
Headshot accuracy16.0%+0.8%
first ⅓ avg 15.2% → last ⅓ avg 16.0%

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

0.12Best match rating · 3–13 · inferno, 13 Oct →
50%Best headshot accuracy · 0–8 · mirage, 13 Oct →
391msFastest reaction time · 12–12 · nuke, 18 Aug →
13–1Biggest win · cache, 7 Jun →

Across the last 100 tracked matches.

Highlights

5Longest win streak
5–9In matches decided by ≤2 rounds

Map breakdown

vertigoBest map · 63% over 8infernoWeakest map · 14% over 7
MapGradePlayedRecordWin rateAvg rating
cacheA2716–1159%0.02
dust2C176–1135%-0.01
mirageB168–850%0.02
nukeD92–722%-0.00
vertigoA85–363%0.03
infernoD71–614%0.03
anubisD51–420%0.00
overpassD51–420%0.01
ancient—30–30%0.03
train—20–20%0.03
office—11–0100%0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

79,930Lifetime kills
1.17K/D · Top 25% of Level 3 players
3,829Matches
48.7%Match win rate · Top 25% of Level 3 players
42.2%Headshot % · Top 50% of Level 3 players
10.8%Shot accuracy
10,040MVPs
1,548Hours (in match)
2,854Bombs planted
1,111Bombs defused

Most-used weapons

AK-4727,239
AWP6,552
SSG 081,947
FAMAS1,317
P901,127
Nova1,073

Lifetime map wins

10,459dust2
3,448inferno
2,334nuke
2,064vertigo
1,231office
1,011train
187cbble
55italy

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

Faceit stats

Combat

77Matches
51%Win rate
1.17Avg K/D
94.8ADR
35%Headshot %

Clutches & streaks

0%1v1 clutch win
100%1v2 clutch win
4Longest win streak

Recent Faceit resultsLLLLW

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.

15.7%Headshot accuracy
34.3%Accuracy (enemy spotted)
38.8%Spray accuracy
80.4%Counter-strafing
8.9°Preaim
552msReaction time
47.8%T opening success
44.5%CT opening success
0.41Enemies flashed / flash
4.5%Flash assists
9.97HE damage / grenade
3.36Flashes / 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

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4116 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Inferno

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient12–120.0414%13 Oct →
mirage8–130.0321%13 Oct →
inferno3–130.1223%13 Oct →
ancient11–130.0211%13 Oct →
mirage0–8-0.1050%13 Oct →
mirage12–12-0.0217%5 Oct →
anubis2–13-0.0616%5 Oct →
vertigo13–9-0.0014%5 Oct →
inferno8–130.009%5 Oct →
anubis13–110.0612%26 Sept →
mirage5–130.0819%22 Aug →
dust23–130.0420%22 Aug →
inferno4–130.0115%18 Aug →
nuke12–12-0.026%18 Aug →
vertigo8–130.0821%18 Aug →
mirage13–40.1021%18 Aug →
cache13–50.109%18 Aug →
ancient10–130.0219%13 Aug →
train10–130.0726%13 Aug →
vertigo13–100.0713%14 Jul →
mirage8–2-0.056%14 Jul →
dust213–11-0.0611%30 Jun →
dust26–130.0220%25 Jun →
cache12–12-0.018%25 Jun →
anubis8–130.019%25 Jun →
inferno7–130.0814%25 Jun →
vertigo4–13-0.0812%25 Jun →
cache13–11-0.0220%20 Jun →
vertigo13–50.0015%20 Jun →
dust213–8-0.0522%20 Jun →
cache13–8-0.0014%18 Jun →
dust21–13-0.143%18 Jun →
mirage12–120.0619%8 Jun →
nuke12–12-0.0116%8 Jun →
cache13–10.0433%7 Jun →
anubis7–130.0221%7 Jun →
mirage13–3-0.0018%7 Jun →
cache8–90.0621%7 Jun →
overpass11–130.049%7 Jun →
dust210–130.0211%7 Jun →
cache13–50.1118%11 May →
nuke13–11-0.0213%11 May →
cache13–110.0816%11 May →
cache12–12-0.079%10 May →
mirage11–130.029%10 May →
cache13–90.0112%10 May →
vertigo13–10.0616%9 May →
dust212–120.0718%9 May →
cache13–50.025%9 May →
overpass10–130.0118%9 May →
mirage13–70.0117%8 May →
cache12–12-0.049%8 May →
mirage13–90.0315%8 May →
overpass11–5-0.0132%8 May →
cache0–5-0.0550%7 May →
dust210–13-0.037%7 May →
nuke10–130.0013%7 May →
mirage13–90.0423%7 May →
cache12–120.0315%5 May →
dust25–13-0.1016%5 May →
vertigo4–130.0022%5 May →
cache3–130.0413%5 May →
dust212–120.0118%4 May →
cache11–13-0.0713%4 May →
cache13–3-0.0216%4 May →
nuke13–50.0220%4 May →
mirage8–13-0.0117%3 May →
dust212–12-0.0114%3 May →
cache13–70.0126%3 May →
cache9–13-0.0515%2 May →
dust210–13-0.0616%2 May →
dust211–130.0310%1 May →
cache13–2-0.019%1 May →
overpass5–13-0.0210%1 May →
cache11–130.0115%1 May →
cache13–40.0115%29 Apr →
cache13–20.0611%29 Apr →
cache13–40.0820%29 Apr →
cache13–90.008%29 Apr →
cache13–80.1123%29 Apr →
cache11–130.0716%28 Apr →
inferno13–70.035%27 Apr →
dust213–100.0818%27 Apr →
dust213–7-0.0121%26 Apr →
overpass6–130.0110%26 Apr →
inferno11–13-0.0126%26 Apr →
dust213–10-0.0628%26 Apr →
mirage5–13-0.0016%26 Apr →
office13–60.0421%26 Apr →
nuke6–130.0511%26 Apr →
anubis9–13-0.0217%23 Apr →
inferno6–13-0.0213%23 Apr →
dust213–7-0.0116%23 Apr →
nuke4–13-0.0113%23 Apr →
nuke12–12-0.0310%22 Apr →
vertigo13–30.0712%22 Apr →
train6–13-0.0124%22 Apr →
mirage13–5-0.0415%22 Apr →
nuke4–90.003%22 Apr →
mirage13–60.1018%21 Apr →

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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