MikB — CS2 Stats

76561198054842231[U:1:94576503]Steam profile ↗✓ No bans

577Tracked matches47%Win rate2023Tracked since

CSDB Rating5.3 DevelopingHybrid Rifler

Premier CS Rating18,811Purple band · top ~13.2% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim72

Positioning44

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY50–50Last 10050%Win rateLWLWWLWWLW

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating

Player DNA

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

Aim7.2

Aggression5.3

Utility5.6

Positioning4.4

Opening Duels1.1

Clutch4.0

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 NiKo 87% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

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. 610ms 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

Aim7.2

Positioning4.4

Utility5.6

Mechanics6.3

Opening Duels1.1

Win Impact3.9

Composite 5.3/10 (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 rating0.00+0.01

first ⅓ avg -0.01 → last ⅓ avg 0.00

Reaction time610ms−35ms

first ⅓ avg 645ms → last ⅓ avg 610ms

Headshot accuracy20.8%+3.5%

first ⅓ avg 17.3% → last ⅓ avg 20.8%

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 — ancient 13–4

13–0Biggest win — nuke

6Longest win streak

7–12In matches decided by ≤2 rounds

12Overtime games

Map breakdown

overpassBest map · 80% over 5infernoWeakest map · 48% over 25

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	30	15–15	50%	-0.00
inferno	B	25	12–13	48%	-0.00
ancient	B	23	11–12	48%	-0.01
overpass	S	5	4–1	80%	-0.02
nuke	—	4	2–2	50%	0.00
cache	—	4	1–3	25%	-0.01
anubis	—	3	2–1	67%	0.03
mirage	—	3	2–1	67%	0.01
train	—	3	1–2	33%	-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (48% over 25). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

553Matches

51%Win rate

1.13Avg K/D

77.2ADR

40%Headshot %

Clutches & streaks

40%1v1 clutch win

29%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	65	46%	1.09	16.5
Inferno	64	64%	1.27	16.9
Dust2	57	44%	1.02	15.3
Anubis	39	41%	0.96	16.2
Mirage	12	58%	1.07	15.3
Train	9	56%	0.85	12.7
Overpass	7	71%	1.50	16.0
Vertigo	4	50%	1.27	15.3

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.

21.6%Headshot accuracy

35.1%Accuracy (enemy spotted)

32.3%Spray accuracy

78.2%Counter-strafing

8.6°Preaim

610msReaction time

38.9%T opening success

29.5%CT opening success

0.46Enemies flashed / flash

3.8%Flash assists

13.02HE damage / grenade

10.24Flashes / 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.

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 0.459 — below the 0.5 mark we flag
Grenade Lineups →
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 38.8913% — 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.

48% win rate across 25 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
inferno	5–13	-0.08	22%	26 Aug →
ancient	13–4	0.11	30%	26 Aug →
inferno	9–13	-0.04	20%	26 Aug →
inferno	13–8	0.01	24%	15 Aug →
dust2	13–7	0.00	26%	3 Aug →
inferno	7–13	0.02	27%	3 Aug →
dust2	13–3	0.04	23%	3 Aug →
ancient	13–10	-0.00	14%	3 Aug →
nuke	14–16	0.03	15%	31 Jul →
ancient	13–11	0.03	28%	29 Jul →
anubis	13–8	0.05	18%	29 Jul →
dust2	2–13	-0.07	20%	29 Jul →
cache	13–10	0.05	15%	28 Jul →
dust2	11–13	0.02	22%	28 Jul →
anubis	12–16	-0.01	16%	26 Jul →
dust2	4–13	-0.04	10%	26 Jul →
inferno	8–13	-0.06	15%	20 Jul →
cache	1–13	-0.11	17%	20 Jul →
inferno	13–9	-0.00	15%	20 Jul →
anubis	13–7	0.04	21%	17 Jul →
ancient	14–16	0.01	33%	17 Jul →
ancient	13–6	0.02	33%	14 Jul →
dust2	8–13	-0.03	32%	14 Jul →
inferno	13–11	-0.00	36%	14 Jul →
inferno	9–13	0.03	20%	12 Jul →
ancient	7–13	-0.02	22%	12 Jul →
cache	5–13	0.02	15%	8 Jul →
ancient	13–6	0.05	8%	6 Jul →
dust2	13–5	-0.01	18%	6 Jul →
dust2	14–16	0.02	26%	4 Jul →
inferno	13–6	0.05	19%	24 Jun →
dust2	6–13	-0.04	16%	24 Jun →
inferno	6–13	-0.03	11%	24 Jun →
inferno	13–9	-0.02	16%	16 Jun →
overpass	13–7	0.04	5%	16 Jun →
cache	16–19	0.00	22%	6 Jun →
ancient	13–6	-0.00	20%	6 Jun →
mirage	3–13	-0.03	20%	3 Jun →
dust2	10–13	-0.09	18%	3 Jun →
ancient	5–13	-0.05	20%	3 Jun →
mirage	13–6	0.04	9%	30 May →
dust2	13–7	-0.00	17%	30 May →
dust2	13–9	0.01	22%	24 May →
ancient	13–10	-0.05	8%	24 May →
ancient	10–13	0.01	8%	23 May →
overpass	13–7	-0.07	18%	20 May →
nuke	13–2	-0.06	13%	20 May →
ancient	5–13	-0.05	20%	20 May →
ancient	9–13	-0.07	26%	18 May →
ancient	11–13	0.01	16%	18 May →
mirage	13–11	0.02	27%	13 May →
dust2	7–13	-0.02	13%	13 May →
nuke	13–0	0.07	15%	13 May →
inferno	11–13	-0.02	19%	13 May →
inferno	11–13	0.02	20%	9 May →
inferno	8–13	0.05	18%	9 May →
inferno	13–11	0.00	9%	5 May →
inferno	13–4	0.03	16%	29 Apr →
dust2	16–13	0.02	15%	29 Apr →
overpass	16–14	-0.07	15%	27 Apr →
inferno	13–5	-0.02	42%	27 Apr →
dust2	13–3	0.06	15%	18 Apr →
inferno	3–13	-0.05	38%	18 Apr →
train	6–13	-0.03	26%	6 Dec →
ancient	3–13	-0.05	6%	6 Dec →
ancient	13–8	-0.02	12%	6 Dec →
dust2	13–6	0.02	21%	1 Nov →
nuke	2–13	-0.02	8%	31 Oct →
inferno	4–13	-0.08	19%	28 Oct →
train	7–13	-0.04	44%	28 Oct →
dust2	13–9	0.03	16%	28 Oct →
ancient	11–13	-0.04	23%	28 Oct →
dust2	13–9	-0.01	14%	27 Oct →
inferno	13–9	0.05	21%	27 Oct →
dust2	16–13	-0.00	15%	26 Oct →
ancient	13–8	0.00	14%	26 Oct →
dust2	8–13	0.01	25%	24 Oct →
inferno	7–8	-0.06	18%	24 Oct →
ancient	8–13	-0.03	14%	22 Oct →
inferno	14–16	0.02	13%	22 Oct →
dust2	5–13	-0.00	10%	22 Oct →
inferno	13–5	0.02	13%	21 Oct →
overpass	13–11	0.04	13%	21 Oct →
dust2	5–13	0.00	23%	21 Oct →
ancient	3–13	-0.05	20%	21 Oct →
dust2	10–13	0.00	17%	20 Oct →
dust2	13–7	-0.02	11%	20 Oct →
ancient	12–16	-0.05	18%	20 Oct →
train	13–11	-0.05	10%	16 Oct →
dust2	11–13	0.00	16%	16 Oct →
dust2	8–13	-0.05	24%	15 Oct →
inferno	13–10	0.03	9%	15 Oct →
dust2	13–8	0.06	11%	15 Oct →
dust2	8–13	0.02	29%	13 Oct →
dust2	13–10	0.04	19%	12 Oct →
overpass	11–13	-0.02	21%	12 Oct →
inferno	13–6	0.01	13%	6 Oct →
ancient	16–13	-0.03	11%	6 Oct →
ancient	16–13	-0.02	15%	2 Oct →
dust2	13–7	0.03	19%	2 Oct →