bog — CS2 Stats

IE76561199008651841[U:1:1048386113]Steam profile ↗✓ No bans

1,674Tracked matches54%Win rate2020Tracked since

CSDB Rating6.0 SolidPassive Rifler

FaceitLevel 10 · 2,289 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim78

Positioning47

Utility50

0–100 skill scores via Leetify.

Recent form

STEADY56–42–2Last 10056%Win rateLWWLLWLTLW

Last 10 vs previous 10: -10pp win rate · -0.00 avg rating

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim7.8

Aggression4.2

Utility5.0

Positioning4.7

Opening Duels1.3

Clutch3.2

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.

Your pro match

Plays most like NiKo 89% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

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

Positioning. Positioning trails aim by 31 points — deaths here waste a strong aim profile.

Reaction time. 571ms 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

Aim7.8

Positioning4.7

Utility5.0

Mechanics8.0

Opening Duels1.6

Win Impact6.2

Composite 6.0/10 (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-0.00+0.01

first ⅓ avg -0.01 → last ⅓ avg -0.00

Reaction time574ms−24ms

first ⅓ avg 598ms → last ⅓ avg 574ms

Headshot accuracy23.9%−1.4%

first ⅓ avg 25.3% → last ⅓ avg 23.9%

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 — overpass 13–2

13–1Biggest win — anubis

8Longest win streak

11–10In matches decided by ≤2 rounds

15Overtime games

Map breakdown

anubisBest map · 86% over 7ancientWeakest map · 38% over 13

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	21	12–9	57%	0.01
inferno	C	16	7–9	44%	-0.01
ancient	C	13	5–8	38%	-0.00
mirage	S	12	8–4	67%	0.01
overpass	S	10	7–3	70%	-0.01
nuke	C	9	4–5	44%	0.01
anubis	S	7	6–1	86%	-0.01
train	S	6	4–2	67%	-0.01
cache	—	4	2–2	50%	0.02
vertigo	—	2	1–1	50%	-0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,139Matches

52%Win rate

1.04Avg K/D

73.9ADR

49%Headshot %

Clutches & streaks

36%1v1 clutch win

19%1v2 clutch win

11Longest win streak

Recent Faceit resultsLLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	152	49%	0.96	15.3
Mirage	151	53%	0.95	14.9
Ancient	147	50%	0.95	15.1
Anubis	117	57%	0.93	15.3
Inferno	98	47%	0.92	14.3
Nuke	84	57%	0.96	14.6
Train	70	57%	1.02	16.4
Overpass	44	61%	0.94	14.4

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.

24.2%Headshot accuracy

32.7%Accuracy (enemy spotted)

35.4%Spray accuracy

86.0%Counter-strafing

10.1°Preaim

571msReaction time

28.3%T opening success

42.5%CT opening success

0.65Enemies flashed / flash

11.7%Flash assists

7.89HE damage / grenade

4.01Flashes / 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 28.2949% — below the 40% mark we flag

Spend your practice time on Ancient

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

38% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	10–13	-0.03	24%	18 Aug →
vertigo	13–9	-0.00	26%	17 Aug →
ancient	13–11	0.02	26%	14 Aug →
inferno	9–13	-0.07	14%	14 Aug →
dust2	9–13	-0.06	21%	12 Aug →
anubis	13–1	0.02	15%	11 Aug →
vertigo	14–16	-0.00	22%	5 Aug →
cache	15–15	0.02	32%	26 Jul →
ancient	7–13	0.05	35%	26 Jul →
mirage	13–7	0.12	22%	26 Jul →
inferno	10–13	-0.02	23%	25 Jul →
inferno	7–13	0.01	21%	25 Jul →
dust2	15–15	0.03	31%	25 Jul →
ancient	6–1	0.01	33%	25 Jul →
cache	13–9	0.01	20%	25 Jul →
cache	13–4	0.09	33%	25 Jul →
inferno	8–13	-0.04	33%	26 Jun →
inferno	13–9	0.03	19%	25 Jun →
dust2	11–13	0.02	26%	11 Jun →
anubis	13–10	-0.03	38%	11 Jun →
nuke	4–13	-0.08	29%	19 May →
cache	9–13	-0.06	19%	19 May →
overpass	13–7	-0.03	16%	17 May →
inferno	13–11	-0.02	20%	9 May →
dust2	10–13	-0.00	27%	29 Apr →
dust2	16–14	-0.02	18%	25 Apr →
overpass	13–7	-0.01	19%	20 Apr →
ancient	13–3	0.01	17%	20 Apr →
inferno	13–8	0.00	32%	20 Apr →
inferno	8–13	0.00	15%	16 Apr →
overpass	13–2	-0.02	29%	16 Apr →
ancient	9–13	0.00	19%	16 Apr →
mirage	13–5	0.01	14%	12 Apr →
overpass	13–11	-0.01	24%	12 Apr →
dust2	13–10	0.05	17%	12 Apr →
nuke	11–13	0.05	22%	12 Apr →
ancient	13–1	-0.04	33%	12 Apr →
inferno	13–10	-0.08	24%	12 Apr →
dust2	13–4	0.03	31%	12 Apr →
dust2	16–13	0.03	34%	11 Apr →
inferno	13–5	-0.01	25%	11 Apr →
dust2	13–8	0.04	30%	11 Apr →
ancient	13–9	-0.04	17%	11 Apr →
anubis	13–3	0.06	15%	11 Apr →
ancient	4–13	-0.01	20%	11 Apr →
inferno	13–8	0.05	29%	11 Apr →
inferno	3–13	-0.01	20%	11 Apr →
inferno	4–13	-0.03	32%	10 Apr →
nuke	9–13	0.01	22%	10 Apr →
dust2	13–11	0.03	22%	8 Apr →
overpass	13–10	0.08	31%	7 Apr →
anubis	11–13	-0.02	12%	7 Apr →
dust2	11–13	0.05	40%	6 Apr →
overpass	16–19	-0.03	23%	29 Oct →
inferno	13–5	0.10	23%	29 Oct →
nuke	13–9	0.03	15%	17 Oct →
dust2	8–13	-0.02	21%	5 Oct →
nuke	17–19	0.02	20%	28 Sept →
mirage	13–10	0.03	18%	22 Sept →
overpass	9–13	0.03	21%	28 Aug →
overpass	13–2	0.13	20%	25 Aug →
train	12–16	-0.06	6%	23 Aug →
nuke	6–13	-0.01	28%	20 Aug →
ancient	11–13	-0.04	25%	10 Aug →
mirage	6–13	0.04	26%	10 Aug →
nuke	13–10	0.05	29%	2 Aug →
nuke	19–15	0.04	45%	1 Aug →
mirage	14–16	-0.02	27%	30 Jul →
mirage	13–7	0.01	19%	30 Jul →
ancient	11–13	0.04	22%	30 Jul →
mirage	13–6	-0.01	44%	28 Jul →
overpass	0–13	-0.08	35%	28 Jul →
train	13–6	0.04	28%	27 Jul →
overpass	13–5	-0.09	9%	21 Jul →
train	16–14	0.00	23%	15 Jul →
dust2	12–16	0.10	23%	11 Jul →
nuke	13–10	0.00	29%	6 Jul →
anubis	13–11	-0.04	24%	6 Jul →
dust2	13–2	0.08	44%	28 Jun →
inferno	8–13	-0.00	28%	13 Jun →
mirage	8–13	-0.01	28%	7 Jun →
dust2	11–13	-0.07	23%	9 May →
anubis	13–8	-0.05	17%	9 May →
dust2	13–11	0.00	34%	9 May →
train	9–13	-0.01	12%	9 May →
dust2	13–11	-0.03	22%	9 May →
anubis	13–9	0.02	23%	7 May →
mirage	16–12	0.02	31%	2 May →
dust2	13–9	-0.03	26%	1 May →
dust2	13–9	-0.03	27%	1 May →
mirage	10–13	0.03	20%	1 May →
ancient	3–13	-0.02	14%	30 Apr →
ancient	9–13	0.00	25%	29 Apr →
mirage	13–9	-0.06	20%	29 Apr →
train	13–9	-0.01	34%	28 Apr →
dust2	8–13	-0.04	24%	27 Apr →
train	16–13	0.00	25%	27 Apr →
mirage	13–11	-0.02	26%	27 Apr →
ancient	12–16	-0.01	26%	27 Apr →
dust2	13–11	-0.03	23%	27 Apr →