mASTERcHIEF117 — CS2 Stats

76561198272006832[U:1:311741104]

233Tracked matches40%Win rate2023Tracked since

CSDB Rating4.1 DevelopingClutch Specialist

Ladder ranks via Leetify

Performance scores

Aim54

Positioning42

Utility56

0–100 skill scores via Leetify.

Recent form

COLD41–55–4Last 10041%Win rateWLLWLLLLLW

Last 10 vs previous 10: -40pp win rate · -0.07 avg rating

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion well above par.

Aim5.4

Aggression2.7

Utility5.6

Positioning4.2

Opening Duels0.0

Clutch10.0

Reliable in 1v1s

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

Plays most like NiKo 79% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-fight frequency; 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. 720ms 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

Aim5.4

Positioning4.2

Utility5.6

Mechanics6.7

Opening Duels0.8

Win Impact1.7

Composite 4.1/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00+0.04

first ⅓ avg -0.03 → last ⅓ avg 0.00

Reaction time719ms−56ms

first ⅓ avg 775ms → last ⅓ avg 719ms

Headshot accuracy11.1%−0.7%

first ⅓ avg 11.8% → last ⅓ avg 11.1%

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.

Highlights

0.20Best rating — dust2 13–7

13–1Biggest win — dust2

6Longest win streak

9–7In matches decided by ≤2 rounds

3Overtime games

Map breakdown

nukeBest map · 58% over 12anubisWeakest map · 18% over 11

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	36	18–18	50%	-0.02
inferno	C	14	5–9	36%	-0.03
nuke	A	12	7–5	58%	-0.03
anubis	D	11	2–9	18%	-0.02
mirage	D	10	3–7	30%	-0.01
ancient	B	8	4–4	50%	0.01
overpass	C	5	2–3	40%	0.01
train	—	3	0–3	0%	-0.00
cache	—	1	0–1	0%	-0.08

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

8Matches

12%Win rate

0.57Avg K/D

52.6ADR

42%Headshot %

Clutches & streaks

100%1v1 clutch win

0%1v2 clutch win

1Longest win streak

Recent Faceit resultsLWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	3	0%	0.59	10.0
Inferno	2	0%	0.54	8.5
Vertigo	1	0%	0.82	14.0
Nuke	1	100%	0.40	6.0
Anubis	1	0%	0.50	8.0

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.

10.9%Headshot accuracy

37.5%Accuracy (enemy spotted)

40.1%Spray accuracy

79.9%Counter-strafing

10.2°Preaim

720msReaction time

23.7%T opening success

36.6%CT opening success

0.60Enemies flashed / flash

5.7%Flash assists

13.23HE damage / grenade

10.12Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 10.8957% — below the 15% mark we flag
Aim Training →
Best CS2 Settings
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 719.9712ms — above the 700ms mark we flag
Aim Training →
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 23.69% — 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.

18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	13–9	-0.06	14%	27 Jul →
nuke	11–13	-0.03	13%	27 Jul →
dust2	7–13	-0.04	10%	26 Jul →
dust2	16–14	-0.01	5%	26 Jul →
dust2	5–13	-0.06	13%	14 Jul →
anubis	9–13	-0.05	9%	14 Jul →
cache	7–13	-0.08	0%	13 Jul →
inferno	5–13	-0.01	6%	6 May →
anubis	5–13	-0.00	4%	6 May →
nuke	13–11	0.02	12%	6 May →
nuke	11–13	-0.05	6%	29 Apr →
ancient	13–11	0.10	8%	29 Apr →
mirage	13–6	0.10	15%	29 Apr →
dust2	13–1	0.05	20%	29 Apr →
anubis	13–5	0.05	8%	29 Apr →
mirage	13–10	0.00	11%	28 Apr →
inferno	13–10	-0.01	9%	15 Apr →
dust2	5–13	0.04	9%	30 Mar →
inferno	13–6	0.05	18%	30 Mar →
mirage	4–13	0.05	11%	30 Mar →
overpass	4–13	0.08	6%	30 Mar →
dust2	13–10	-0.05	11%	27 Mar →
anubis	14–16	0.02	11%	23 Mar →
nuke	9–13	0.03	12%	18 Mar →
dust2	9–13	-0.01	17%	18 Mar →
inferno	8–13	-0.07	17%	18 Mar →
overpass	1–13	-0.04	18%	18 Mar →
anubis	11–13	0.05	17%	17 Mar →
mirage	1–13	-0.03	2%	17 Mar →
dust2	13–11	0.10	17%	16 Mar →
dust2	5–13	-0.07	17%	16 Mar →
inferno	10–13	0.01	12%	16 Mar →
ancient	6–13	0.07	9%	16 Mar →
anubis	4–13	-0.01	10%	16 Mar →
overpass	7–13	-0.01	13%	16 Mar →
mirage	8–13	0.00	12%	16 Mar →
dust2	13–7	0.20	15%	7 Mar →
ancient	13–7	-0.01	10%	7 Mar →
dust2	8–13	-0.04	14%	7 Mar →
dust2	10–13	-0.07	13%	5 Mar →
mirage	12–12	-0.03	18%	3 Mar →
mirage	2–13	-0.10	3%	2 Mar →
inferno	9–13	0.07	9%	2 Mar →
ancient	3–13	0.00	14%	2 Mar →
ancient	4–13	0.02	18%	2 Mar →
dust2	2–13	-0.04	14%	2 Mar →
nuke	13–11	-0.03	19%	4 Dec →
nuke	13–9	-0.05	21%	3 Dec →
dust2	8–13	-0.07	16%	29 Nov →
inferno	8–13	-0.07	9%	3 Nov →
nuke	5–13	-0.04	13%	30 Oct →
nuke	11–2	-0.05	11%	4 Oct →
dust2	12–12	-0.04	18%	4 Oct →
dust2	13–7	-0.01	16%	4 Oct →
inferno	13–5	-0.07	27%	29 Sept →
dust2	16–14	-0.09	17%	29 Sept →
dust2	13–10	-0.03	18%	20 Sept →
inferno	2–13	-0.03	23%	2 Sept →
inferno	12–12	-0.10	4%	2 Sept →
dust2	10–13	-0.01	13%	1 Sept →
dust2	5–13	-0.01	7%	28 Aug →
dust2	8–13	0.00	24%	27 Aug →
nuke	4–13	-0.05	16%	27 Aug →
anubis	12–12	-0.11	11%	26 Aug →
anubis	5–13	-0.11	0%	24 Aug →
anubis	3–13	-0.09	0%	20 Aug →
dust2	13–5	-0.02	18%	20 Aug →
mirage	8–13	-0.07	11%	8 Aug →
mirage	1–6	-0.05	36%	8 Aug →
dust2	11–13	-0.01	19%	8 Aug →
dust2	13–3	-0.04	16%	7 Aug →
ancient	13–4	-0.02	18%	7 Aug →
ancient	4–13	-0.04	3%	6 Aug →
dust2	13–8	-0.03	15%	5 Aug →
mirage	13–4	-0.02	15%	4 Aug →
anubis	11–13	0.01	13%	22 Jul →
ancient	13–10	-0.05	10%	20 Jul →
nuke	13–6	-0.01	12%	20 Jul →
overpass	13–9	-0.03	7%	20 Jul →
train	9–13	-0.01	13%	20 Jul →
dust2	5–13	-0.08	16%	20 Jul →
dust2	3–13	-0.09	9%	20 Jul →
overpass	13–6	0.04	12%	20 Jul →
dust2	13–7	-0.03	6%	4 Jul →
dust2	13–11	0.06	9%	4 Jul →
anubis	13–9	-0.02	16%	3 Jul →
dust2	10–13	-0.03	6%	3 Jul →
dust2	9–13	-0.06	9%	3 Jul →
train	8–13	-0.05	12%	3 Jul →
inferno	4–13	-0.08	13%	3 Jul →
dust2	13–6	-0.03	19%	2 Jul →
nuke	13–8	-0.06	9%	2 Jul →
inferno	13–2	0.04	5%	2 Jul →
dust2	13–8	-0.04	8%	2 Jul →
inferno	10–13	-0.09	12%	2 Jul →
dust2	13–4	-0.06	6%	27 Jun →
nuke	13–4	-0.03	13%	26 Jun →
dust2	13–11	-0.06	3%	26 Jun →
train	11–13	0.04	13%	26 Jun →
inferno	13–11	-0.09	4%	25 Jun →