bork — CS2 Stats

76561198152511076[U:1:192245348]Steam profile ↗✓ No bans

2,437Tracked matches57%Win rate2020Tracked since

CSDB Rating5.4 Developing

Premier CS Rating16,853Purple band · top ~21% of ranked players (population est.)

CSDB Leaderboard#11342 of 19546 tracked

FaceitLevel 4 · 1,018 ELOTop 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim41

Positioning60

Utility51

0–100 skill scores via Leetify.

Recent form

HOT42–53–5Last 10042%Win rateLWLLWWWWWW

Last 10 vs previous 10: +40pp win rate · -0.03 avg rating

Player DNA

Aim4.1

Aggression7.6

Utility5.1

Positioning6.0

Opening Duels5.5

Clutch0.0

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 ropz 86% playstyle similarity

Most alike: positioning profile, 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

Reaction time. 680ms 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

Aim4.1

Positioning6.0

Utility5.1

Mechanics6.3

Opening Duels5.5

Win Impact7.2

Composite 5.4/10 (Developing), 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+0.03

first ⅓ avg -0.02 → last ⅓ avg 0.01

Reaction time687ms−13ms

first ⅓ avg 700ms → last ⅓ avg 687ms

Headshot accuracy14.7%−0.2%

first ⅓ avg 15.0% → last ⅓ avg 14.7%

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

0.11Best rating — inferno 6–13

13–0Biggest win — cache

6Longest win streak

6–7In matches decided by ≤2 rounds

6Overtime games

Map breakdown

cacheBest map · 67% over 15infernoWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	22	8–14	36%	-0.00
mirage	C	22	9–13	41%	-0.01
nuke	A	17	10–7	59%	-0.02
cache	S	15	10–5	67%	-0.00
anubis	D	8	2–6	25%	-0.05
inferno	D	6	1–5	17%	0.02
train	—	3	1–2	33%	-0.00
overpass	—	3	0–3	0%	-0.02
ancient	—	2	0–2	0%	0.00
shelter	—	1	0–1	0%	0.11
vertigo	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

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

Faceit stats

Combat

41Matches

56%Win rate

0.80Avg K/D

67.5ADR

43%Headshot %

Clutches & streaks

20%1v1 clutch win

10%1v2 clutch win

4Longest win streak

Recent Faceit resultsLWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	11	45%	0.61	10.2
Nuke	10	70%	1.02	15.9
Anubis	6	67%	0.74	11.0
Overpass	5	60%	0.81	13.2
Inferno	4	50%	0.83	12.0
Train	2	0%	0.62	10.0
Dust2	2	50%	0.76	10.5
Ancient	1	100%	1.25	15.0

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.

14.5%Headshot accuracy

35.6%Accuracy (enemy spotted)

38.9%Spray accuracy

78.1%Counter-strafing

14.9°Preaim

680msReaction time

48.7%T opening success

55.5%CT opening success

0.51Enemies flashed / flash

5.8%Flash assists

7.15HE damage / grenade

20.14Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 14.89° — above the 12° mark we flag
Aim Training →
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 14.5085% — below the 15% mark we flag
Aim Training →

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.

17% win rate across 6 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
dust2	9–13	0.00	14%	24 Aug →
mirage	13–9	-0.01	16%	24 Aug →
nuke	8–13	-0.03	11%	19 Aug →
mirage	10–13	-0.04	15%	13 Aug →
cache	13–10	-0.01	19%	13 Aug →
cache	13–2	0.05	18%	12 Aug →
mirage	13–9	-0.02	9%	11 Aug →
mirage	13–10	0.01	16%	8 Aug →
dust2	13–10	-0.00	17%	8 Aug →
nuke	13–11	0.03	10%	6 Aug →
cache	6–13	0.07	23%	5 Aug →
mirage	11–13	0.07	24%	5 Aug →
dust2	13–7	0.04	17%	5 Aug →
cache	4–13	-0.06	18%	3 Aug →
dust2	10–13	0.10	15%	3 Aug →
cache	16–13	0.02	18%	3 Aug →
mirage	13–6	0.05	8%	1 Aug →
nuke	11–13	0.08	18%	28 Jul →
mirage	3–13	-0.04	13%	27 Jul →
mirage	6–13	-0.03	15%	27 Jul →
nuke	13–5	-0.06	13%	27 Jul →
mirage	10–13	0.01	13%	25 Jul →
dust2	13–5	-0.01	17%	25 Jul →
nuke	13–2	0.06	12%	25 Jul →
mirage	13–11	-0.03	7%	25 Jul →
cache	13–6	-0.00	11%	25 Jul →
cache	13–5	-0.04	10%	25 Jul →
dust2	8–13	-0.02	11%	25 Jul →
anubis	1–13	-0.07	7%	25 Jul →
nuke	13–7	-0.00	15%	23 Jul →
dust2	3–13	0.01	19%	22 Jul →
inferno	6–13	0.11	17%	21 Jul →
cache	13–7	0.02	19%	20 Jul →
dust2	13–9	0.01	11%	20 Jul →
cache	10–13	-0.06	7%	19 Jul →
mirage	8–13	-0.02	16%	19 Jul →
nuke	0–9	-0.21	14%	19 Jul →
mirage	8–13	-0.04	6%	19 Jul →
mirage	13–9	0.00	8%	19 Jul →
dust2	13–2	0.01	9%	19 Jul →
mirage	15–15	-0.00	8%	18 Jul →
shelter	10–13	0.11	18%	18 Jul →
dust2	13–16	-0.02	17%	16 Jul →
inferno	9–13	-0.05	14%	16 Jul →
mirage	8–13	0.07	15%	16 Jul →
dust2	1–13	-0.04	15%	16 Jul →
nuke	5–13	-0.03	13%	16 Jul →
mirage	7–13	-0.00	12%	15 Jul →
anubis	13–6	0.03	9%	15 Jul →
dust2	10–13	-0.06	23%	14 Jul →
mirage	2–13	-0.05	8%	14 Jul →
cache	13–10	0.01	14%	14 Jul →
dust2	13–10	-0.04	12%	13 Jul →
dust2	13–11	0.02	23%	13 Jul →
mirage	6–13	-0.04	7%	12 Jul →
cache	13–0	0.05	10%	12 Jul →
anubis	13–16	-0.04	10%	12 Jul →
cache	3–8	-0.04	0%	12 Jul →
dust2	13–10	-0.05	28%	11 Jul →
dust2	8–13	0.03	22%	11 Jul →
nuke	5–13	-0.03	8%	11 Jul →
vertigo	13–7	0.01	10%	8 Jul →
train	12–12	0.07	16%	8 Jul →
cache	12–12	-0.01	16%	8 Jul →
cache	13–8	0.01	17%	7 Jul →
nuke	13–10	0.00	8%	6 Jul →
dust2	15–15	-0.05	13%	6 Jul →
anubis	5–13	-0.03	18%	6 Jul →
nuke	13–11	0.01	12%	6 Jul →
inferno	8–13	0.00	11%	6 Jul →
dust2	7–13	0.06	11%	5 Jul →
nuke	13–9	0.01	15%	5 Jul →
ancient	14–16	0.01	16%	5 Jul →
mirage	13–3	-0.02	13%	5 Jul →
mirage	13–9	-0.01	16%	3 Jul →
overpass	10–13	-0.00	20%	3 Jul →
inferno	10–13	0.06	11%	3 Jul →
dust2	11–13	0.02	19%	3 Jul →
overpass	7–13	-0.03	22%	18 Jun →
anubis	6–13	-0.12	9%	18 Jun →
anubis	11–13	-0.07	13%	18 Jun →
mirage	3–13	-0.08	19%	16 Jun →
cache	3–13	-0.06	4%	13 Jun →
anubis	13–4	0.03	16%	13 Jun →
nuke	6–13	-0.08	4%	13 Jun →
nuke	13–10	-0.02	28%	12 Jun →
anubis	4–13	-0.10	12%	12 Jun →
inferno	11–13	-0.04	13%	12 Jun →
dust2	11–13	-0.01	22%	12 Jun →
nuke	13–10	-0.02	16%	8 Jun →
inferno	13–11	0.01	17%	8 Jun →
dust2	7–13	-0.03	12%	8 Jun →
nuke	6–13	-0.01	17%	7 Jun →
overpass	4–13	-0.03	15%	7 Jun →
nuke	13–7	-0.06	21%	7 Jun →
dust2	8–13	-0.08	15%	7 Jun →
train	13–11	-0.03	15%	7 Jun →
train	12–12	-0.05	7%	2 Jun →
mirage	13–8	0.04	13%	2 Jun →
ancient	3–13	-0.01	21%	31 May →