nnailer — CS2 Stats

76561197998698781[U:1:38433053]

1,427Tracked matches47%Win rate2021Tracked since

CSDB Rating5.0 Developing

Premier CS Rating12,157Blue band · top ~43.5% of ranked players (population est.)

CSDB Leaderboard#20463 of 29461 tracked

FaceitLevel 5Top 67.6% of ranked FACEIT players

WingmanSilver IV

Ladder ranks via Leetify

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Performance scores

Aim52

Positioning56

Utility69

0–100 skill scores via Leetify.

Recent form

STEADY47–50–3Last 10047%Win rateWWLLWLLWWW

Last 10 vs previous 10: +10pp win rate · -0.02 avg rating

Player DNA

Aim5.2

Aggression8.7

Utility6.9

Positioning5.6

Opening Duels4.3

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.

Your pro match

Plays most like device 87% playstyle similarity

Most alike: opening-duel success, utility contribution.

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 →

Strengths & areas to improve

Areas to improve

T-side openings. Opening success drops from 55% on CT to 39% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 624ms 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

Aim5.2

Positioning5.6

Utility6.9

Mechanics4.9

Opening Duels4.3

Win Impact3.9

Composite 5.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00+0.01

first ⅓ avg -0.01 → last ⅓ avg 0.00

Reaction time631ms−15ms

first ⅓ avg 646ms → last ⅓ avg 631ms

Headshot accuracy20.0%+2.0%

first ⅓ avg 18.0% → last ⅓ avg 20.0%

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.

Highlights

0.13Best rating — inferno 4–0

13–1Biggest win — ancient

6Longest win streak

W2Current streak

5–10In matches decided by ≤2 rounds

13Overtime games

Map breakdown

anubisBest map · 78% over 9infernoWeakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	21	8–13	38%	-0.01
ancient	B	20	9–11	45%	-0.00
nuke	C	14	6–8	43%	0.00
cache	B	13	6–7	46%	-0.02
mirage	A	10	6–4	60%	0.00
anubis	S	9	7–2	78%	-0.02
inferno	D	9	3–6	33%	0.00
overpass	—	3	1–2	33%	-0.02
vertigo	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

230Matches

50%Win rate

0.95Avg K/D

80.1ADR

41%Headshot %

Clutches & streaks

37%1v1 clutch win

17%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	62	53%	0.96	14.5
Dust2	41	54%	0.93	14.2
Anubis	36	47%	0.96	15.1
Inferno	26	50%	0.91	14.6
Ancient	22	27%	0.79	14.4
Vertigo	16	56%	0.88	15.8
Nuke	14	79%	1.25	18.1
Cache	11	45%	1.02	14.3

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.

20.1%Headshot accuracy

31.2%Accuracy (enemy spotted)

36.1%Spray accuracy

71.8%Counter-strafing

11.2°Preaim

624msReaction time

39.3%T opening success

54.9%CT opening success

0.67Enemies flashed / flash

4.9%Flash assists

12.33HE damage / grenade

15.05Flashes / 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.

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 39.3132% — below the 40% mark we flag

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.

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–7	-0.03	19%	21 Aug →
nuke	13–11	0.04	18%	21 Aug →
ancient	11–13	-0.03	14%	16 Aug →
dust2	2–13	-0.04	24%	13 Aug →
vertigo	25–21	-0.01	33%	10 Aug →
ancient	10–13	-0.05	21%	6 Aug →
ancient	9–13	-0.04	21%	31 Jul →
dust2	16–12	0.01	12%	30 Jul →
anubis	13–8	-0.03	18%	30 Jul →
ancient	13–1	0.06	18%	30 Jul →
dust2	9–13	-0.02	29%	30 Jul →
cache	13–6	0.03	17%	30 Jul →
inferno	4–0	0.13	33%	30 Jul →
dust2	5–13	-0.09	25%	29 Jul →
nuke	13–8	-0.01	9%	28 Jul →
mirage	16–14	0.00	14%	28 Jul →
dust2	10–13	0.00	14%	28 Jul →
cache	9–13	-0.05	16%	26 Jul →
cache	11–13	-0.00	26%	23 Jul →
ancient	13–4	0.06	12%	22 Jul →
cache	13–10	-0.00	21%	22 Jul →
mirage	13–3	0.09	29%	22 Jul →
dust2	11–13	0.07	19%	22 Jul →
inferno	11–13	0.02	32%	20 Jul →
inferno	7–13	-0.06	15%	19 Jul →
dust2	6–13	0.00	17%	19 Jul →
ancient	10–13	-0.02	28%	19 Jul →
inferno	8–13	-0.08	13%	17 Jul →
dust2	14–16	0.01	16%	17 Jul →
cache	13–3	0.04	30%	17 Jul →
dust2	13–11	0.00	19%	17 Jul →
nuke	13–6	-0.02	21%	17 Jul →
anubis	13–9	0.02	7%	17 Jul →
dust2	10–13	0.01	26%	17 Jul →
inferno	11–13	-0.01	21%	17 Jul →
nuke	13–11	0.02	18%	17 Jul →
cache	13–9	-0.01	15%	17 Jul →
anubis	16–13	-0.02	13%	17 Jul →
inferno	13–9	0.01	13%	17 Jul →
dust2	13–7	0.01	19%	17 Jul →
cache	13–7	0.03	30%	16 Jul →
dust2	9–13	-0.10	22%	15 Jul →
anubis	13–10	-0.03	16%	15 Jul →
ancient	13–5	0.02	28%	15 Jul →
mirage	16–12	-0.02	16%	14 Jul →
mirage	13–10	0.06	25%	14 Jul →
ancient	13–10	0.06	23%	14 Jul →
ancient	9–13	0.03	38%	14 Jul →
dust2	13–5	0.03	35%	12 Jul →
ancient	10–13	-0.05	24%	11 Jul →
cache	6–13	-0.08	36%	11 Jul →
ancient	13–6	-0.00	13%	9 Jul →
mirage	3–13	-0.10	20%	9 Jul →
cache	8–13	-0.06	31%	9 Jul →
cache	8–13	-0.06	25%	9 Jul →
overpass	11–13	-0.04	21%	6 Jul →
cache	12–12	0.01	34%	6 Jul →
cache	3–13	-0.03	27%	6 Jul →
nuke	8–13	0.01	30%	4 Jul →
nuke	13–16	-0.02	21%	4 Jul →
dust2	6–13	-0.06	25%	4 Jul →
nuke	10–13	-0.00	18%	4 Jul →
inferno	1–13	0.01	43%	3 Jul →
mirage	6–13	0.01	30%	3 Jul →
anubis	13–5	-0.04	21%	3 Jul →
dust2	9–13	0.07	21%	3 Jul →
nuke	13–9	-0.01	22%	3 Jul →
ancient	13–10	-0.00	12%	3 Jul →
dust2	11–7	0.01	23%	3 Jul →
ancient	10–13	-0.04	6%	2 Jul →
overpass	9–13	-0.06	28%	2 Jul →
dust2	13–2	-0.06	15%	2 Jul →
ancient	11–13	0.01	14%	2 Jul →
mirage	3–13	-0.06	8%	2 Jul →
nuke	11–13	0.09	18%	2 Jul →
dust2	13–2	-0.00	27%	2 Jul →
dust2	6–13	-0.03	12%	1 Jul →
ancient	13–5	0.02	23%	1 Jul →
overpass	13–4	0.03	22%	1 Jul →
nuke	4–13	0.01	15%	1 Jul →
ancient	15–15	-0.03	16%	1 Jul →
ancient	13–5	0.11	15%	1 Jul →
anubis	13–1	0.02	27%	1 Jul →
inferno	13–8	0.01	11%	29 Jun →
mirage	14–16	0.03	24%	29 Jun →
anubis	4–13	-0.07	8%	29 Jun →
dust2	16–13	-0.04	31%	29 Jun →
nuke	8–13	-0.01	14%	29 Jun →
ancient	13–10	-0.04	16%	29 Jun →
ancient	15–15	-0.04	25%	29 Jun →
anubis	16–12	-0.04	8%	28 Jun →
inferno	9–13	-0.02	29%	27 Jun →
mirage	13–5	0.08	19%	27 Jun →
mirage	13–11	-0.05	13%	27 Jun →
nuke	1–13	-0.04	19%	27 Jun →
anubis	13–16	-0.02	18%	26 Jun →
dust2	10–13	0.02	14%	26 Jun →
nuke	13–8	-0.02	20%	26 Jun →
ancient	8–13	-0.05	27%	26 Jun →
nuke	10–13	0.02	20%	25 Jun →