Badger- — CS2 Stats

76561198283263090[U:1:322997362]✓ No bans

1,992Tracked matches60%Win rate2020Tracked since

CSDB Rating7.0 StrongAggressive Rifler

Premier CS Rating25,000Top 25% of 819 CSDB-tracked playersRed band · top ~3% of ranked players (population est.)

FaceitLevel 8 · 1,972 ELOTop 31.2% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim83

Positioning63

Utility43

0–100 skill scores via Leetify.

Recent form

STEADY53–44–3Last 10053%Win rateLLWLLWWLWW

Last 10 vs previous 10: -20pp win rate · -0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim8.3

Aggression10.0

Utility4.3

Positioning6.3

Opening Duels4.2

Clutch4.0

Strong CT-side openerLimited 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 device 92% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 56% on CT to 37% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim8.3

Positioning6.3

Utility4.3

Mechanics6.8

Opening Duels4.2

Win Impact8.3

Composite 7.0/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 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 time522ms+12ms

first ⅓ avg 510ms → last ⅓ avg 522ms

Headshot accuracy13.5%−0.5%

first ⅓ avg 14.0% → last ⅓ avg 13.5%

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 — inferno 13–4

13–0Biggest win — ancient

7Longest win streak

L2Current streak

10–11In matches decided by ≤2 rounds

15Overtime games

Map breakdown

anubisBest map · 82% over 11mirageWeakest map · 38% over 16

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	23	11–12	48%	0.04
dust2	B	18	9–9	50%	0.00
mirage	C	16	6–10	38%	0.02
cache	B	14	7–7	50%	0.01
ancient	A	14	8–6	57%	0.03
anubis	S	11	9–2	82%	0.04
nuke	—	4	3–1	75%	0.03

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (38% over 16). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

224Matches

57%Win rate

1.34Avg K/D

84.9ADR

31%Headshot %

Clutches & streaks

40%1v1 clutch win

26%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	52	52%	1.21	17.4
Inferno	30	70%	1.30	17.5
Dust2	26	69%	1.46	19.6
Ancient	23	52%	2.11	17.4
Nuke	22	64%	1.28	18.3
Anubis	13	69%	1.47	17.9
Train	5	20%	1.07	15.4
Overpass	5	60%	0.85	12.4

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.

13.2%Headshot accuracy

38.0%Accuracy (enemy spotted)

44.1%Spray accuracy

80.7%Counter-strafing

8.3°Preaim

514msReaction time

37.2%T opening success

56.4%CT opening success

0.53Enemies flashed / flash

3.1%Flash assists

8.23HE damage / grenade

4.72Flashes / 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 13.156% — 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 37.1593% — 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.

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