Bairy Fitch — CS2 Stats

US76561198078365322[U:1:118099594]Steam profile ↗✓ No bans

781Tracked matches41%Win rate2020Tracked since

1,055Hours in CS

CSDB Rating3.7 Learning

FaceitLevel 2 · 721 ELOTop 97.9% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim55

Positioning36

Utility41

0–100 skill scores via Leetify.

Recent form

COLD50–44–6Last 10050%Win rateLLLWLLTLWW

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

Player DNA

Aim5.5

Aggression3.0

Utility4.1

Positioning3.6

Opening Duels0.0

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 NiKo 75% playstyle similarity

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

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. 697ms 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

Aim5.5

Positioning3.6

Utility4.1

Mechanics6.0

Opening Duels0.6

Win Impact2.1

Composite 3.7/10 (Learning), 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 rating-0.02−0.03

first ⅓ avg 0.01 → last ⅓ avg -0.02

Reaction time700ms+25ms

first ⅓ avg 675ms → last ⅓ avg 700ms

Headshot accuracy11.2%−0.9%

first ⅓ avg 12.1% → last ⅓ avg 11.2%

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 — ancient 13–4

13–0Biggest win — train

8Longest win streak

L3Current streak

7–8In matches decided by ≤2 rounds

8Overtime games

Map breakdown

trainBest map · 100% over 5mirageWeakest map · 25% over 12

Map	Grade	Played	Record	Win rate	Avg rating
inferno	A	19	11–8	58%	-0.03
ancient	A	15	9–6	60%	0.00
nuke	B	13	6–7	46%	-0.02
mirage	D	12	3–9	25%	-0.02
overpass	S	9	6–3	67%	-0.00
dust2	C	8	3–5	38%	-0.02
office	D	8	2–6	25%	0.00
anubis	D	6	2–4	33%	-0.03
train	S	5	5–0	100%	0.04
cache	—	4	2–2	50%	0.01
alpine	—	1	1–0	100%	-0.09

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (25% over 12). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

69,706Lifetime kills

1.07K/D · Top 50% of tracked players

3,559Matches

28.6%Match win rate

32.8%Headshot %

13.3%Shot accuracy · Top 50% of tracked players

4,899MVPs

1,055Hours (in match)

2,933Bombs planted

644Bombs defused

Most-used weapons

AK-4721,640

M4A4 / M4A1-S19,063

AWP3,778

P2000 / USP-S2,724

Glock-181,786

Desert Eagle1,583

Galil AR1,419

MAC-101,416

FAMAS1,359

UMP-451,293

Lifetime map wins

2,635inferno

2,445dust2

1,335nuke

800cbble

791vertigo

722train

165office

69ar_shoots

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

40Matches

38%Win rate

0.76Avg K/D

65.2ADR

34%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

2Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	9	22%	0.80	15.1
Overpass	7	14%	0.72	12.6
Anubis	6	33%	0.65	10.5
Vertigo	5	60%	0.82	11.6
Mirage	5	80%	1.01	12.8
Inferno	5	0%	0.58	10.2
Ancient	3	100%	0.76	11.3

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.

11.8%Headshot accuracy

37.9%Accuracy (enemy spotted)

42.3%Spray accuracy

77.1%Counter-strafing

10.9°Preaim

697msReaction time

22.1%T opening success

34.7%CT opening success

0.43Enemies flashed / flash

1.9%Flash assists

8.16HE damage / grenade

6.05Flashes / 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.

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 11.7516% — below the 15% mark we flag
Aim Training →
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 0.4288 — 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 22.0865% — below the 40% mark we flag

Spend your practice time on Mirage

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

25% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–16	-0.02	9%	3 Jul →
overpass	11–13	-0.00	9%	16 Jun →
cache	8–13	0.02	15%	6 Jun →
cache	13–6	-0.04	5%	6 Jun →
dust2	11–13	-0.04	15%	5 Jun →
anubis	4–13	-0.06	12%	27 May →
office	12–12	-0.04	9%	14 May →
cache	11–13	0.04	10%	8 May →
cache	13–9	0.01	21%	2 May →
inferno	13–10	-0.07	19%	22 Apr →
mirage	7–13	-0.07	22%	22 Apr →
mirage	9–13	0.00	18%	22 Apr →
mirage	2–9	-0.11	0%	16 Apr →
dust2	4–13	0.01	10%	8 Apr →
inferno	13–8	-0.00	9%	8 Apr →
mirage	5–11	-0.03	15%	31 Mar →
mirage	13–8	0.06	20%	28 Mar →
ancient	10–13	-0.03	12%	27 Mar →
inferno	5–13	-0.02	3%	27 Mar →
ancient	6–13	0.01	15%	25 Mar →
nuke	16–13	0.01	13%	23 Mar →
ancient	13–11	0.04	7%	20 Mar →
nuke	13–10	-0.01	19%	20 Mar →
inferno	10–13	-0.01	13%	16 Mar →
overpass	13–4	0.01	4%	15 Mar →
inferno	6–13	-0.09	8%	8 Mar →
mirage	8–13	-0.02	6%	8 Mar →
overpass	13–8	-0.03	11%	8 Mar →
dust2	13–2	-0.01	14%	8 Mar →
mirage	13–1	-0.03	0%	8 Mar →
nuke	8–13	-0.07	16%	2 Mar →
inferno	13–11	-0.04	9%	2 Mar →
alpine	13–6	-0.09	6%	1 Mar →
nuke	8–13	-0.05	14%	1 Mar →
anubis	16–14	-0.02	10%	1 Mar →
nuke	13–10	-0.04	21%	27 Feb →
inferno	13–7	-0.06	10%	27 Feb →
inferno	13–9	-0.03	9%	24 Feb →
inferno	13–10	-0.03	18%	24 Feb →
ancient	16–12	-0.01	15%	24 Feb →
inferno	13–9	-0.00	9%	24 Feb →
ancient	13–8	0.07	13%	23 Feb →
anubis	7–13	-0.01	9%	23 Feb →
anubis	7–13	-0.06	10%	22 Feb →
mirage	5–13	0.00	17%	22 Feb →
nuke	13–11	-0.01	14%	21 Feb →
ancient	13–9	-0.02	9%	21 Feb →
anubis	6–13	-0.04	15%	21 Feb →
inferno	8–13	-0.07	15%	6 Feb →
overpass	13–10	-0.05	13%	6 Feb →
nuke	5–13	-0.08	18%	6 Feb →
ancient	13–7	-0.01	4%	31 Jan →
train	13–6	0.02	11%	31 Jan →
nuke	3–13	0.00	12%	31 Jan →
mirage	9–13	-0.02	15%	30 Jan →
inferno	13–8	0.09	3%	30 Jan →
ancient	10–13	-0.07	8%	28 Jan →
nuke	13–11	-0.03	12%	28 Jan →
nuke	5–13	-0.07	13%	27 Jan →
inferno	13–8	-0.03	25%	27 Jan →
mirage	3–7	-0.02	27%	27 Jan →
ancient	11–13	-0.01	7%	27 Jan →
dust2	16–14	-0.01	10%	26 Jan →
mirage	15–15	-0.05	15%	26 Jan →
dust2	10–13	-0.05	21%	26 Jan →
inferno	13–8	0.05	13%	26 Jan →
overpass	11–13	-0.02	11%	26 Jan →
ancient	13–9	-0.07	5%	26 Jan →
dust2	13–8	0.02	11%	25 Jan →
inferno	11–13	0.00	9%	25 Jan →
office	10–13	0.02	19%	25 Jan →
inferno	13–11	-0.04	14%	25 Jan →
anubis	13–7	-0.02	9%	25 Jan →
dust2	12–12	-0.04	15%	24 Jan →
dust2	9–13	-0.01	19%	24 Jan →
mirage	13–9	0.06	8%	23 Jan →
ancient	13–5	-0.01	21%	23 Jan →
office	13–4	0.08	6%	23 Jan →
office	5–13	0.01	16%	22 Jan →
office	5–13	0.01	12%	22 Jan →
overpass	13–1	0.03	10%	17 Jan →
overpass	13–7	-0.00	14%	17 Jan →
nuke	15–15	0.06	13%	15 Jan →
inferno	13–16	0.00	8%	13 Jan →
train	10–3	0.04	4%	12 Jan →
ancient	13–4	0.13	13%	12 Jan →
ancient	11–13	0.01	6%	12 Jan →
ancient	12–12	0.00	6%	11 Jan →
overpass	13–7	0.10	11%	11 Jan →
office	12–12	-0.01	13%	11 Jan →
train	13–0	0.02	8%	11 Jan →
train	13–7	0.04	11%	10 Jan →
nuke	13–9	0.05	8%	10 Jan →
inferno	2–13	-0.03	24%	10 Jan →
office	2–13	0.03	21%	9 Jan →
train	13–7	0.09	16%	9 Jan →
ancient	13–8	0.02	9%	9 Jan →
inferno	5–9	-0.15	14%	8 Jan →
office	13–7	-0.07	16%	8 Jan →
overpass	11–13	-0.06	11%	8 Jan →