Don Corleone — CS2 Stats

GR76561198131111061[U:1:170845333]Steam profile ↗✓ No bans

2,616Tracked matches43%Win rate2020Tracked since

CSDB Rating4.5 DevelopingSupport

Premier CS Rating12,765Blue band · top ~40.2% of ranked players (population est.)

CSDB Leaderboard#38039 of 57201 tracked

FaceitLevel 4Top 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim48

Positioning50

Utility74

0–100 skill scores via Leetify.

Recent form

STEADY48–47–5Last 10048%Win rateWWWLWLLLWL

Last 10 vs previous 10: +20pp win rate · +0.04 avg rating

Player DNA

Primary style: Support — Utility contribution leads the profile while opening activity stays low.

Aim4.8

Aggression4.8

Utility7.4

Positioning5.0

Opening Duels0.4

Clutch3.0

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 Twistzz 82% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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 43% on CT to 20% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 648ms 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

Aim4.8

Positioning5.0

Utility7.4

Mechanics5.4

Opening Duels1.6

Win Impact2.6

Composite 4.5/10 (Developing), 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 rating0.01−0.01

first ⅓ avg 0.03 → last ⅓ avg 0.01

Reaction time646ms−60ms

first ⅓ avg 706ms → last ⅓ avg 646ms

Headshot accuracy18.9%−4.9%

first ⅓ avg 23.8% → last ⅓ avg 18.9%

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

0.16Best rating — dust2 13–2

13–0Biggest win — dust2

6Longest win streak

W3Current streak

10–2In matches decided by ≤2 rounds

13Overtime games

Map breakdown

dust2Best map · 61% over 36anubisWeakest map · 36% over 14

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	36	22–14	61%	0.03
inferno	B	20	9–11	45%	0.01
anubis	C	14	5–9	36%	0.01
ancient	C	13	5–8	38%	0.01
mirage	B	11	5–6	45%	-0.00
cache	—	4	2–2	50%	-0.01
nuke	—	1	0–1	0%	0.04
shelter	—	1	0–1	0%	0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (36% over 14). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

120Matches

44%Win rate

1.28Avg K/D

82.8ADR

36%Headshot %

Clutches & streaks

35%1v1 clutch win

25%1v2 clutch win

4Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	43	56%	1.52	17.8
Mirage	21	29%	0.99	13.9
Inferno	20	40%	1.13	16.1
Anubis	17	41%	1.35	17.9
Ancient	11	55%	1.37	17.8
Nuke	4	25%	1.06	15.5
Cache	2	0%	0.68	9.5
Overpass	1	100%	0.92	11.0

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.

18.5%Headshot accuracy

30.0%Accuracy (enemy spotted)

28.0%Spray accuracy

74.5%Counter-strafing

9.2°Preaim

648msReaction time

20.3%T opening success

42.6%CT opening success

0.69Enemies flashed / flash

10.4%Flash assists

13.66HE damage / grenade

11.63Flashes / 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 20.3262% — below the 40% mark we flag

Spend your practice time on Anubis

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

36% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	13–10	0.10	24%	31 Aug →
mirage	13–3	0.06	27%	31 Aug →
dust2	16–14	0.05	16%	30 Aug →
dust2	10–13	-0.01	19%	30 Aug →
dust2	13–11	-0.04	15%	30 Aug →
ancient	7–13	0.07	28%	30 Aug →
nuke	9–13	0.04	11%	30 Aug →
anubis	10–13	-0.01	15%	29 Aug →
dust2	13–6	0.03	14%	29 Aug →
inferno	10–13	-0.02	7%	28 Aug →
anubis	9–13	-0.00	19%	27 Aug →
inferno	1–13	-0.06	36%	27 Aug →
mirage	6–13	-0.08	25%	27 Aug →
dust2	15–15	0.03	9%	27 Aug →
inferno	13–11	-0.01	14%	27 Aug →
inferno	13–8	0.04	14%	25 Aug →
dust2	11–13	-0.01	17%	25 Aug →
dust2	13–6	0.03	28%	25 Aug →
ancient	13–16	-0.06	19%	24 Aug →
ancient	3–13	-0.04	23%	24 Aug →
dust2	13–16	0.01	20%	24 Aug →
anubis	13–10	0.06	27%	23 Aug →
dust2	10–13	0.01	33%	23 Aug →
ancient	9–13	0.06	15%	23 Aug →
inferno	8–13	0.02	16%	23 Aug →
inferno	15–15	0.03	18%	23 Aug →
cache	8–13	-0.05	21%	20 Aug →
dust2	13–0	0.06	9%	20 Aug →
ancient	13–5	0.03	14%	20 Aug →
dust2	13–10	0.06	15%	20 Aug →
ancient	9–13	0.02	21%	20 Aug →
dust2	13–10	0.05	13%	20 Aug →
mirage	13–11	0.01	22%	20 Aug →
inferno	7–13	-0.09	13%	19 Aug →
anubis	6–1	0.03	17%	19 Aug →
dust2	13–10	0.05	16%	19 Aug →
dust2	13–11	0.07	32%	19 Aug →
mirage	8–13	-0.01	24%	18 Aug →
dust2	9–1	0.11	12%	18 Aug →
inferno	13–11	0.01	16%	18 Aug →
dust2	7–13	-0.07	12%	17 Aug →
mirage	13–2	0.09	14%	17 Aug →
dust2	10–13	0.01	17%	17 Aug →
inferno	11–13	-0.01	21%	17 Aug →
dust2	9–13	-0.01	20%	17 Aug →
dust2	13–9	0.05	16%	17 Aug →
ancient	13–9	0.04	17%	17 Aug →
dust2	9–13	-0.04	15%	17 Aug →
anubis	13–11	-0.01	15%	16 Aug →
anubis	15–15	0.03	22%	16 Aug →
inferno	13–5	0.05	15%	16 Aug →
mirage	9–13	-0.06	18%	16 Aug →
dust2	15–15	-0.04	15%	16 Aug →
ancient	13–5	0.00	21%	16 Aug →
inferno	16–13	0.03	17%	16 Aug →
anubis	1–13	-0.04	20%	15 Aug →
inferno	3–13	-0.03	21%	15 Aug →
mirage	7–13	0.05	20%	15 Aug →
dust2	16–13	0.00	15%	12 Aug →
mirage	3–13	-0.07	45%	12 Aug →
inferno	13–1	0.13	25%	12 Aug →
dust2	6–13	0.01	23%	12 Aug →
inferno	10–13	-0.07	10%	12 Aug →
ancient	5–13	0.03	25%	11 Aug →
cache	13–10	-0.03	16%	11 Aug →
anubis	10–13	-0.07	23%	11 Aug →
dust2	13–8	0.02	38%	10 Aug →
dust2	13–5	0.08	41%	10 Aug →
mirage	13–4	0.05	20%	10 Aug →
inferno	6–4	0.01	20%	10 Aug →
dust2	13–10	0.01	16%	9 Aug →
ancient	13–1	0.06	30%	9 Aug →
inferno	9–13	-0.03	22%	9 Aug →
anubis	8–13	0.03	17%	9 Aug →
inferno	13–6	0.14	20%	8 Aug →
dust2	13–8	0.05	30%	8 Aug →
mirage	16–13	-0.01	20%	8 Aug →
anubis	9–13	-0.05	15%	7 Aug →
dust2	13–10	0.06	23%	6 Aug →
mirage	1–13	-0.04	6%	6 Aug →
dust2	9–13	0.01	19%	6 Aug →
ancient	5–13	-0.07	30%	3 Aug →
inferno	3–13	-0.05	24%	2 Aug →
dust2	8–13	-0.04	9%	2 Aug →
dust2	13–0	0.03	43%	27 Jul →
dust2	13–8	0.04	31%	27 Jul →
dust2	13–6	0.05	27%	27 Jul →
dust2	13–2	0.16	19%	27 Jul →
anubis	13–10	0.06	15%	27 Jul →
dust2	10–13	0.09	28%	26 Jul →
inferno	6–13	0.08	18%	26 Jul →
inferno	16–12	0.04	19%	25 Jul →
anubis	13–11	0.04	25%	25 Jul →
shelter	8–13	0.02	23%	25 Jul →
ancient	15–15	-0.00	18%	24 Jul →
cache	4–13	-0.01	21%	24 Jul →
anubis	3–13	0.05	48%	24 Jul →
anubis	12–16	-0.04	32%	24 Jul →
cache	13–11	0.05	38%	22 Jul →
ancient	13–2	-0.01	18%	22 Jul →