pywin32 STATIC = BAD — CS2 Stats

76561198834721462[U:1:874455734]

248Tracked matches48%Win rate2022Tracked since

CSDB Rating6.5 SolidAggressive Rifler

Premier CS Rating21,384Pink band · top ~7% of ranked players (population est.)

CSDB Leaderboard#6957 of 19514 tracked

FaceitLevel 5Top 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim82

Positioning55

Utility46

0–100 skill scores via Leetify.

Recent form

COLD49–49–2Last 10049%Win rateLLWLTLLLWW

Last 10 vs previous 10: -30pp win rate · -0.01 avg rating

Player DNA

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

Aim8.2

Aggression7.4

Utility4.6

Positioning5.5

Opening Duels4.1

Clutch9.4

Excellent counter-strafingStrong CT-side openerEffective flashesReliable in 1v1s

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 ropz 93% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

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

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 54% on CT to 38% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 607ms 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

Aim8.2

Positioning5.5

Utility4.6

Mechanics8.8

Opening Duels4.1

Win Impact4.4

Composite 6.5/10 (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 rating0.01−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.01

Reaction time600ms−21ms

first ⅓ avg 621ms → last ⅓ avg 600ms

Headshot accuracy18.3%+1.9%

first ⅓ avg 16.4% → last ⅓ avg 18.3%

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

0.18Best rating — dust2 13–5

12–0Biggest win — inferno

5Longest win streak

L2Current streak

4–8In matches decided by ≤2 rounds

12Overtime games

Map breakdown

cacheBest map · 80% over 5ancientWeakest map · 33% over 15

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	26	13–13	50%	0.00
dust2	B	20	9–11	45%	0.02
ancient	D	15	5–10	33%	0.01
overpass	C	12	5–7	42%	0.03
nuke	B	10	5–5	50%	0.02
inferno	S	9	7–2	78%	0.02
cache	S	5	4–1	80%	0.02
anubis	—	2	1–1	50%	-0.02
train	—	1	0–1	0%	-0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

45Matches

40%Win rate

1.25Avg K/D

99.3ADR

46%Headshot %

Clutches & streaks

67%1v1 clutch win

33%1v2 clutch win

4Longest win streak

Recent Faceit resultsLWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	5	60%	1.27	22.8
Ancient	3	33%	1.35	21.7
Inferno	2	100%	1.00	17.5
Overpass	1	100%	1.22	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.

17.7%Headshot accuracy

38.7%Accuracy (enemy spotted)

42.0%Spray accuracy

89.6%Counter-strafing

9.7°Preaim

607msReaction time

38.1%T opening success

54.5%CT opening success

0.72Enemies flashed / flash

4.7%Flash assists

6.31HE damage / grenade

5.77Flashes / 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 38.1204% — 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.

33% win rate across 15 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
ancient	6–13	-0.05	17%	2 Aug →
dust2	10–13	-0.00	22%	2 Aug →
mirage	13–11	0.16	24%	2 Aug →
dust2	4–13	-0.01	18%	26 Jul →
nuke	15–15	0.03	9%	26 Jul →
ancient	11–13	-0.01	10%	26 Jul →
mirage	10–13	-0.06	21%	26 Jul →
mirage	6–13	-0.02	20%	26 Jul →
inferno	13–10	0.02	21%	25 Jul →
ancient	13–10	0.04	13%	25 Jul →
mirage	13–8	0.05	12%	25 Jul →
mirage	11–13	-0.04	14%	25 Jul →
inferno	13–3	0.06	20%	25 Jul →
mirage	13–3	0.12	24%	21 Jul →
inferno	12–16	-0.04	10%	21 Jul →
dust2	12–16	-0.02	15%	21 Jul →
dust2	13–10	0.10	19%	20 Jul →
mirage	13–7	-0.03	14%	20 Jul →
ancient	4–13	-0.01	18%	20 Jul →
mirage	13–2	0.04	27%	20 Jul →
anubis	6–13	-0.02	19%	20 Jul →
cache	16–13	0.02	21%	18 Jul →
anubis	9–3	-0.02	16%	18 Jul →
cache	11–13	0.07	15%	18 Jul →
nuke	10–13	-0.03	25%	18 Jul →
dust2	13–6	0.03	19%	18 Jul →
dust2	11–13	0.01	25%	18 Jul →
cache	13–9	0.03	16%	18 Jul →
mirage	8–13	0.04	20%	18 Jul →
cache	13–9	0.00	17%	17 Jul →
inferno	16–12	0.02	22%	17 Jul →
ancient	8–13	0.02	28%	16 Jul →
mirage	16–12	-0.00	13%	16 Jul →
nuke	5–13	-0.02	18%	16 Jul →
mirage	7–13	-0.09	18%	16 Jul →
dust2	10–13	-0.03	37%	15 Jul →
ancient	13–5	0.00	18%	15 Jul →
cache	13–2	-0.05	21%	15 Jul →
dust2	9–13	-0.06	6%	16 Aug →
ancient	11–13	-0.04	11%	16 Aug →
inferno	6–13	0.01	17%	16 Aug →
overpass	13–4	0.07	21%	16 Aug →
dust2	13–6	0.17	27%	16 Aug →
overpass	11–13	0.03	17%	16 Aug →
ancient	5–13	0.06	11%	16 Aug →
mirage	5–13	-0.04	13%	16 Aug →
nuke	13–6	0.00	15%	15 Aug →
dust2	13–9	0.02	20%	15 Aug →
overpass	13–16	-0.00	17%	14 Aug →
nuke	13–10	0.11	10%	14 Aug →
overpass	9–13	0.03	17%	14 Aug →
nuke	13–6	-0.03	24%	14 Aug →
mirage	8–13	-0.06	10%	13 Aug →
dust2	6–13	0.01	18%	13 Aug →
ancient	4–13	0.02	18%	13 Aug →
overpass	13–5	-0.00	15%	13 Aug →
mirage	13–7	0.02	14%	13 Aug →
nuke	7–13	0.03	13%	10 Aug →
ancient	7–13	-0.03	13%	10 Aug →
mirage	10–13	-0.02	15%	10 Aug →
dust2	13–8	-0.01	17%	10 Aug →
mirage	13–8	0.05	18%	10 Aug →
overpass	13–4	0.08	15%	10 Aug →
mirage	13–7	-0.00	15%	7 Aug →
overpass	15–15	-0.01	18%	7 Aug →
inferno	16–14	0.06	20%	7 Aug →
dust2	11–13	-0.02	12%	7 Aug →
mirage	13–8	0.04	27%	7 Aug →
inferno	16–14	0.04	15%	2 Aug →
ancient	13–7	0.02	38%	2 Aug →
dust2	9–13	0.03	21%	2 Aug →
mirage	13–10	0.02	13%	30 Jul →
train	5–13	-0.00	13%	30 Jul →
mirage	13–10	-0.02	5%	30 Jul →
dust2	13–7	0.03	36%	30 Jul →
overpass	13–10	0.10	15%	30 Jul →
overpass	8–13	0.05	7%	28 Jul →
inferno	13–8	-0.03	18%	28 Jul →
mirage	16–19	0.13	19%	28 Jul →
mirage	5–13	-0.09	13%	28 Jul →
mirage	9–13	-0.04	15%	27 Jul →
ancient	13–10	0.06	17%	27 Jul →
overpass	13–5	0.05	18%	27 Jul →
mirage	3–13	-0.00	13%	27 Jul →
nuke	5–13	-0.00	7%	26 Jul →
overpass	10–13	-0.05	17%	26 Jul →
ancient	13–7	0.07	15%	26 Jul →
dust2	13–10	0.04	14%	26 Jul →
dust2	13–5	0.18	18%	26 Jul →
nuke	13–11	0.02	15%	26 Jul →
inferno	12–0	0.02	17%	25 Jul →
ancient	12–16	0.05	18%	25 Jul →
nuke	13–10	0.07	13%	24 Jul →
mirage	5–13	-0.05	24%	23 Jul →
dust2	3–13	-0.04	23%	23 Jul →
overpass	9–13	0.05	18%	23 Jul →
dust2	5–13	0.03	11%	22 Jul →
ancient	11–13	-0.04	8%	22 Jul →
mirage	13–6	-0.00	13%	21 Jul →
dust2	13–10	-0.02	7%	21 Jul →