BigDrop — CS2 Stats

76561199668586266[U:1:1708320538]Steam profile ↗✓ No bans

2,018Tracked matches70%Win rate2024Tracked since

CSDB Rating6.7 SolidHybrid Rifler

FaceitLevel 7 · 1,798 ELOTop 42.3% of ranked FACEIT players

WingmanGold Nova II

Ladder ranks via Leetify

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Performance scores

Aim81

Positioning63

Utility51

0–100 skill scores via Leetify.

Recent form

HOT54–44–2Last 10054%Win rateWWWLLWWWWW

Last 10 vs previous 10: +0pp win rate · +0.00 avg rating

Player DNA

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

Aim8.1

Aggression5.6

Utility5.1

Positioning6.3

Opening Duels3.5

Clutch3.2

Strong CT-side opener

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 iM 92% playstyle similarity

Most alike: positioning profile, 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 52% on CT to 36% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 557ms 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

Aim8.1

Positioning6.3

Utility5.1

Mechanics8.3

Opening Duels3.5

Win Impact10.0

Composite 6.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.02

first ⅓ avg 0.03 → last ⅓ avg 0.01

Reaction time566ms−42ms

first ⅓ avg 608ms → last ⅓ avg 566ms

Headshot accuracy16.4%−0.1%

first ⅓ avg 16.5% → last ⅓ avg 16.4%

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

0.26Best rating — anubis 13–2

13–1Biggest win — anubis

8Longest win streak

W3Current streak

11–4In matches decided by ≤2 rounds

13Overtime games

Map breakdown

cacheBest map · 69% over 13infernoWeakest map · 40% over 10

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	17	9–8	53%	0.02
mirage	A	16	10–6	63%	0.02
dust2	C	16	7–9	44%	-0.00
anubis	B	15	8–7	53%	0.03
cache	S	13	9–4	69%	0.02
nuke	B	11	5–6	45%	0.01
inferno	C	10	4–6	40%	-0.01
overpass	—	2	2–0	100%	0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

753Matches

49%Win rate

1.13Avg K/D

81.9ADR

42%Headshot %

Clutches & streaks

36%1v1 clutch win

23%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	201	48%	1.09	15.6
Dust2	141	47%	1.06	16.1
Ancient	110	48%	1.19	17.6
Inferno	94	54%	1.17	16.6
Nuke	87	52%	1.28	17.2
Anubis	47	36%	1.04	15.6
Cache	33	61%	1.13	15.8
Train	20	50%	1.22	16.4

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.

15.2%Headshot accuracy

38.4%Accuracy (enemy spotted)

38.0%Spray accuracy

87.5%Counter-strafing

9.3°Preaim

557msReaction time

35.9%T opening success

51.7%CT opening success

0.54Enemies flashed / flash

5.4%Flash assists

10.16HE damage / grenade

10.44Flashes / 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 35.943% — 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.

40% win rate across 10 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
cache	13–7	-0.04	14%	28 Aug →
mirage	13–7	0.13	16%	27 Aug →
mirage	13–11	0.02	20%	26 Aug →
cache	9–13	-0.00	26%	25 Aug →
cache	10–13	-0.02	16%	22 Aug →
ancient	13–7	-0.05	21%	21 Aug →
cache	13–6	0.10	8%	17 Aug →
dust2	19–17	-0.06	14%	17 Aug →
cache	13–9	-0.02	19%	16 Aug →
anubis	13–4	0.04	18%	13 Aug →
mirage	22–19	-0.01	12%	12 Aug →
ancient	13–9	0.02	15%	12 Aug →
mirage	13–5	0.00	17%	11 Aug →
anubis	9–13	0.05	11%	11 Aug →
ancient	19–16	-0.01	8%	8 Aug →
anubis	13–9	0.00	11%	8 Aug →
mirage	0–13	-0.06	18%	6 Aug →
dust2	16–13	0.03	11%	5 Aug →
cache	13–11	0.03	7%	4 Aug →
ancient	13–7	0.03	18%	3 Aug →
ancient	13–4	0.00	10%	2 Aug →
nuke	16–14	0.03	12%	2 Aug →
mirage	12–16	0.01	18%	1 Aug →
dust2	10–13	-0.04	20%	1 Aug →
anubis	13–11	0.04	22%	1 Aug →
mirage	13–8	-0.03	11%	30 Jul →
nuke	7–13	-0.02	9%	29 Jul →
ancient	7–13	0.05	22%	29 Jul →
dust2	13–11	0.02	17%	28 Jul →
ancient	4–13	-0.03	27%	28 Jul →
anubis	4–12	-0.05	18%	28 Jul →
ancient	9–13	0.02	29%	26 Jul →
cache	13–9	-0.00	26%	26 Jul →
cache	13–6	0.03	14%	26 Jul →
inferno	16–13	0.00	15%	25 Jul →
nuke	6–13	0.06	11%	23 Jul →
inferno	6–13	-0.03	21%	23 Jul →
inferno	10–13	0.00	11%	23 Jul →
cache	13–6	0.09	10%	22 Jul →
inferno	3–13	0.02	37%	21 Jul →
inferno	8–13	-0.01	17%	20 Jul →
nuke	13–10	-0.05	24%	20 Jul →
dust2	8–13	-0.01	16%	19 Jul →
inferno	13–11	-0.02	23%	18 Jul →
mirage	13–4	0.04	11%	18 Jul →
ancient	11–13	0.04	19%	18 Jul →
ancient	5–3	0.10	11%	18 Jul →
cache	9–13	0.03	22%	17 Jul →
anubis	10–13	-0.03	12%	17 Jul →
ancient	9–13	0.03	14%	17 Jul →
mirage	13–2	0.10	17%	16 Jul →
dust2	16–13	-0.03	10%	16 Jul →
mirage	5–13	-0.03	9%	16 Jul →
anubis	0–13	-0.07	8%	16 Jul →
nuke	13–6	0.09	16%	14 Jul →
anubis	0–13	-0.07	17%	14 Jul →
dust2	8–13	-0.03	7%	11 Jul →
inferno	9–13	-0.02	9%	11 Jul →
nuke	5–13	-0.06	16%	9 Jul →
mirage	4–13	0.04	24%	8 Jul →
inferno	13–10	0.02	14%	8 Jul →
anubis	5–13	-0.01	19%	7 Jul →
anubis	19–17	0.02	13%	7 Jul →
dust2	10–13	0.08	34%	6 Jul →
inferno	13–9	-0.01	21%	29 Jun →
dust2	8–13	0.04	26%	27 Jun →
overpass	13–6	0.03	22%	27 Jun →
mirage	13–16	-0.04	9%	25 Jun →
mirage	13–7	-0.03	12%	22 Jun →
ancient	7–13	0.00	26%	19 Jun →
anubis	13–11	-0.03	9%	18 Jun →
dust2	3–11	-0.08	16%	9 Jun →
dust2	9–13	-0.01	12%	7 Jun →
nuke	13–8	0.07	18%	7 Jun →
ancient	13–9	0.04	9%	6 Jun →
anubis	7–13	-0.01	8%	6 Jun →
cache	13–10	0.11	8%	6 Jun →
anubis	13–2	0.26	18%	5 Jun →
dust2	13–10	-0.06	19%	4 Jun →
dust2	16–14	0.06	20%	4 Jun →
ancient	13–7	0.06	16%	31 May →
ancient	5–13	0.02	16%	31 May →
dust2	13–5	-0.02	18%	30 May →
dust2	11–13	-0.00	19%	28 May →
inferno	6–13	-0.04	23%	24 May →
dust2	12–12	0.08	18%	24 May →
anubis	13–7	0.11	14%	24 May →
nuke	11–13	0.03	16%	19 May →
ancient	13–8	-0.03	15%	17 May →
nuke	13–10	-0.00	20%	17 May →
overpass	13–10	0.06	11%	17 May →
nuke	15–15	-0.03	13%	17 May →
anubis	13–1	0.18	28%	17 May →
mirage	13–7	0.11	15%	17 May →
ancient	11–13	0.08	31%	17 May →
mirage	16–12	0.05	22%	16 May →
nuke	6–13	-0.02	29%	11 May →
mirage	6–13	-0.01	15%	9 May →
cache	13–9	-0.00	10%	8 May →
cache	8–13	0.01	10%	8 May →