bagel — CS2 Stats

AU76561198009850070[U:1:49584342]Steam profile ↗✓ No bans

831Tracked matches50%Win rate2020Tracked since

CSDB Rating5.8 SolidHybrid Rifler

Premier CS Rating22,193Top 50% of 819 CSDB-tracked playersPink band · top ~6.1% of ranked players (population est.)

CSDB Leaderboard#6161 of 20219 tracked

Ladder ranks via Leetify

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Performance scores

Aim67

Positioning60

Utility61

0–100 skill scores via Leetify.

Recent form

HOT46–48–6Last 10046%Win rateWWWWLWWWLW

Last 10 vs previous 10: +60pp win rate · +0.03 avg rating

Player DNA

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

Aim6.7

Aggression9.2

Utility6.1

Positioning6.0

Opening Duels4.0

Clutch3.4

Strong CT-side openerEffective flashes

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 jL 92% playstyle similarity

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

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 37% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 560ms 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

Aim6.7

Positioning6.0

Utility6.1

Mechanics4.5

Opening Duels4.0

Win Impact5.0

Composite 5.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02−0.01

first ⅓ avg 0.03 → last ⅓ avg 0.02

Reaction time555ms−25ms

first ⅓ avg 579ms → last ⅓ avg 555ms

Headshot accuracy15.2%−3.1%

first ⅓ avg 18.3% → last ⅓ avg 15.2%

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

0.17Best rating — anubis 13–2

13–1Biggest win — mirage

4Longest win streak

W4Current streak

10–8In matches decided by ≤2 rounds

14Overtime games

Map breakdown

anubisBest map · 60% over 10ancientWeakest map · 13% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	30	16–14	53%	0.03
inferno	A	20	11–9	55%	0.02
overpass	D	15	4–11	27%	0.02
nuke	B	10	5–5	50%	0.02
anubis	A	10	6–4	60%	0.04
ancient	D	8	1–7	13%	0.02
cache	—	4	2–2	50%	0.03
dust2	—	2	1–1	50%	-0.01
vertigo	—	1	0–1	0%	0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

547Matches

53%Win rate

1.30Avg K/D

95.2ADR

36%Headshot %

Clutches & streaks

37%1v1 clutch win

30%1v2 clutch win

7Longest win streak

Recent Faceit resultsLWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	15	53%	1.25	18.3
Inferno	7	71%	1.39	22.7
Anubis	5	40%	1.42	25.4
Cache	4	75%	1.32	15.0
Overpass	3	100%	1.48	17.3
Ancient	3	33%	1.17	17.7
Dust2	2	50%	1.00	18.0
Nuke	2	50%	1.22	19.0

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.

14.8%Headshot accuracy

36.1%Accuracy (enemy spotted)

36.7%Spray accuracy

70.2%Counter-strafing

8.4°Preaim

560msReaction time

37.4%T opening success

54.8%CT opening success

0.73Enemies flashed / flash

12.8%Flash assists

12.98HE damage / grenade

7.95Flashes / 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 14.798% — below the 15% mark we flag
Aim Training →
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 37.4346% — 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.

13% win rate across 8 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	13–5	0.02	8%	8 Aug →
nuke	13–11	0.01	7%	15 Jul →
mirage	16–14	-0.01	12%	13 Jul →
mirage	13–10	0.04	15%	12 Jul →
anubis	10–13	0.05	9%	12 Jul →
overpass	13–7	-0.01	8%	11 Jul →
mirage	13–9	0.02	12%	11 Jul →
mirage	16–14	0.05	14%	4 Jul →
mirage	2–13	0.06	16%	18 Jun →
overpass	13–8	0.07	18%	17 Jun →
inferno	7–13	-0.09	9%	17 Jun →
overpass	6–13	0.00	38%	16 Jun →
mirage	4–13	-0.01	16%	16 Jun →
ancient	14–16	0.04	7%	15 Jun →
overpass	11–13	0.04	22%	15 Jun →
anubis	9–13	0.01	12%	11 Jun →
mirage	13–10	0.02	21%	11 Jun →
ancient	5–13	-0.01	16%	11 Jun →
mirage	13–10	0.04	25%	9 Jun →
ancient	5–13	-0.01	21%	9 Jun →
nuke	13–11	0.05	9%	9 Jun →
dust2	11–13	0.02	11%	9 Jun →
ancient	2–13	0.07	6%	9 Jun →
mirage	6–13	0.02	22%	9 Jun →
inferno	6–13	-0.05	13%	8 Jun →
mirage	13–4	0.00	12%	8 Jun →
anubis	16–13	0.03	10%	13 May →
mirage	12–12	0.07	19%	13 May →
mirage	12–12	0.03	23%	12 May →
cache	13–3	0.05	18%	12 May →
mirage	0–13	-0.07	17%	12 May →
dust2	13–7	-0.03	19%	11 May →
inferno	13–8	-0.01	15%	11 May →
cache	10–13	0.04	17%	29 Apr →
cache	13–5	-0.03	15%	29 Apr →
cache	8–13	0.06	19%	29 Apr →
overpass	10–13	-0.01	24%	28 Apr →
inferno	13–10	0.02	12%	28 Apr →
mirage	4–13	-0.04	19%	28 Apr →
inferno	3–13	0.05	9%	27 Apr →
anubis	13–2	0.17	30%	27 Apr →
nuke	6–13	-0.01	22%	27 Apr →
overpass	7–13	0.00	10%	27 Apr →
inferno	8–13	0.05	13%	23 Apr →
anubis	13–10	-0.05	15%	23 Apr →
mirage	11–13	-0.02	14%	22 Apr →
anubis	9–13	0.03	21%	22 Apr →
inferno	8–13	-0.00	16%	22 Apr →
mirage	13–6	0.06	26%	22 Apr →
overpass	11–13	0.03	19%	22 Apr →
mirage	15–15	0.07	16%	21 Apr →
mirage	16–13	-0.01	24%	20 Apr →
vertigo	7–13	0.03	51%	20 Apr →
overpass	8–13	0.00	23%	20 Apr →
ancient	8–13	0.00	20%	20 Apr →
ancient	13–11	0.07	16%	17 Apr →
mirage	16–13	0.06	14%	17 Apr →
inferno	13–8	0.06	16%	17 Apr →
mirage	12–16	0.03	16%	17 Apr →
inferno	8–13	-0.01	18%	17 Apr →
anubis	13–5	0.12	18%	17 Apr →
nuke	3–13	0.01	17%	17 Apr →
mirage	7–13	0.01	15%	17 Apr →
ancient	8–13	-0.01	16%	16 Apr →
anubis	13–10	0.12	17%	16 Apr →
inferno	13–4	0.04	41%	16 Apr →
mirage	15–15	-0.02	14%	16 Apr →
overpass	7–13	-0.04	27%	16 Apr →
nuke	11–13	0.03	20%	16 Apr →
inferno	13–8	-0.01	11%	16 Apr →
inferno	13–11	0.00	19%	15 Apr →
overpass	13–5	0.12	57%	15 Apr →
nuke	13–16	-0.03	11%	15 Apr →
overpass	2–13	-0.02	15%	15 Apr →
mirage	13–11	0.04	33%	14 Apr →
overpass	13–10	0.07	21%	14 Apr →
overpass	15–15	-0.02	17%	14 Apr →
inferno	9–13	0.11	21%	14 Apr →
nuke	13–9	0.10	16%	14 Apr →
mirage	13–3	0.11	13%	14 Apr →
inferno	13–8	0.04	15%	14 Apr →
overpass	11–13	0.00	28%	26 Mar →
nuke	13–9	-0.05	13%	26 Mar →
overpass	10–13	0.01	24%	26 Mar →
inferno	13–11	0.03	12%	26 Mar →
mirage	13–8	0.11	18%	26 Mar →
inferno	15–15	0.02	12%	24 Mar →
mirage	13–3	0.06	22%	24 Mar →
inferno	7–13	0.13	23%	20 Mar →
ancient	11–13	0.00	11%	20 Mar →
nuke	6–13	0.02	16%	19 Mar →
mirage	5–13	0.01	20%	19 Mar →
inferno	16–14	-0.07	7%	18 Mar →
anubis	13–10	0.01	18%	18 Mar →
mirage	16–13	0.01	10%	17 Mar →
anubis	8–13	-0.04	14%	16 Mar →
mirage	13–1	0.08	26%	16 Mar →
nuke	13–11	0.04	8%	16 Mar →
inferno	13–9	0.09	8%	16 Mar →
mirage	9–13	-0.02	18%	10 Mar →