Professor Finnessor — CS2 Stats

76561198200673046[U:1:240407318]

683Tracked matches34%Win rate2023Tracked since

CSDB Rating4.6 DevelopingHybrid Rifler

WingmanMaster Guardian I

Ladder ranks via Leetify

Performance scores

Aim66

Positioning61

Utility38

0–100 skill scores via Leetify.

Recent form

STEADY39–56–5Last 10039%Win rateLWWWLLWWLW

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

Player DNA

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

Aim6.6

Aggression5.9

Utility3.8

Positioning6.1

Opening Duels2.3

Clutch1.2

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 NiKo 86% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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 49% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 587ms 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

Aim6.6

Positioning6.1

Utility3.8

Mechanics7.4

Opening Duels2.4

Win Impact0.0

Composite 4.6/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00+0.02

first ⅓ avg -0.02 → last ⅓ avg -0.00

Reaction time592ms−46ms

first ⅓ avg 639ms → last ⅓ avg 592ms

Headshot accuracy12.0%+0.2%

first ⅓ avg 11.9% → last ⅓ avg 12.0%

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 — ancient 13–6

13–4Biggest win — mirage

4Longest win streak

6–9In matches decided by ≤2 rounds

14Overtime games

Map breakdown

ancientBest map · 64% over 14dust2Weakest map · 11% over 9

Map	Grade	Played	Record	Win rate	Avg rating
nuke	C	18	7–11	39%	-0.01
overpass	C	18	7–11	39%	-0.02
inferno	D	17	5–12	29%	-0.01
ancient	A	14	9–5	64%	0.00
mirage	B	13	6–7	46%	-0.01
dust2	D	9	1–8	11%	-0.01
cache	C	5	2–3	40%	-0.01
train	—	3	1–2	33%	-0.00
anubis	—	2	1–1	50%	0.02
vertigo	—	1	0–1	0%	-0.04

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (11% over 9). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

257Matches

49%Win rate

1.04Avg K/D

79.3ADR

33%Headshot %

Clutches & streaks

26%1v1 clutch win

22%1v2 clutch win

4Longest win streak

Recent Faceit resultsWLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	68	49%	1.08	15.3
Nuke	39	56%	1.12	15.2
Inferno	38	42%	0.95	14.7
Dust2	37	49%	0.94	14.7
Ancient	29	52%	1.02	14.3
Overpass	23	52%	1.18	14.4
Vertigo	13	38%	0.95	13.2
Anubis	9	56%	1.14	17.9

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.

11.7%Headshot accuracy

36.6%Accuracy (enemy spotted)

36.5%Spray accuracy

83.3%Counter-strafing

10.0°Preaim

587msReaction time

29.5%T opening success

48.8%CT opening success

0.49Enemies flashed / flash

5.9%Flash assists

6.59HE damage / grenade

4.20Flashes / 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 11.7308% — below the 15% mark we flag
Aim Training →
Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4851 — below the 0.5 mark we flag
Grenade Lineups →
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 29.5006% — below the 40% mark we flag

Spend your practice time on Dust 2

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

11% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	10–13	-0.02	15%	29 Aug →
nuke	13–11	-0.05	13%	29 Aug →
anubis	13–9	0.01	12%	29 Aug →
cache	13–10	0.10	4%	29 Aug →
inferno	5–13	-0.05	22%	29 Aug →
cache	3–13	-0.05	12%	28 Aug →
mirage	13–8	-0.03	14%	28 Aug →
ancient	13–6	0.13	12%	25 Aug →
dust2	11–13	-0.01	9%	23 Aug →
ancient	12–4	0.06	9%	23 Aug →
dust2	5–13	-0.04	14%	23 Aug →
cache	13–9	-0.02	13%	23 Aug →
cache	6–13	-0.04	10%	25 Apr →
nuke	15–15	0.07	13%	5 Apr →
mirage	13–10	0.09	11%	5 Apr →
inferno	13–8	0.02	12%	4 Apr →
overpass	11–13	0.04	17%	29 Mar →
nuke	14–16	0.05	16%	29 Mar →
mirage	9–13	0.00	11%	28 Mar →
ancient	4–13	-0.01	6%	17 Mar →
ancient	10–13	-0.08	3%	11 Mar →
anubis	16–19	0.03	10%	10 Mar →
dust2	9–13	0.05	5%	9 Mar →
mirage	11–13	-0.05	11%	1 Mar →
dust2	4–13	-0.09	27%	25 Feb →
dust2	6–13	-0.02	10%	24 Feb →
nuke	13–9	0.05	12%	22 Feb →
mirage	10–13	-0.01	7%	21 Feb →
inferno	7–13	-0.02	16%	19 Feb →
nuke	11–13	-0.09	8%	16 Feb →
dust2	16–14	0.05	18%	14 Feb →
inferno	6–13	-0.06	8%	8 Feb →
ancient	13–9	-0.06	16%	8 Feb →
dust2	9–13	0.04	12%	23 Jan →
nuke	6–13	-0.03	15%	22 Jan →
overpass	6–13	-0.05	8%	18 Jan →
inferno	10–13	-0.01	10%	15 Jan →
ancient	13–10	-0.02	8%	15 Jan →
ancient	13–11	-0.01	14%	14 Jan →
overpass	13–7	-0.04	18%	14 Jan →
mirage	16–13	-0.03	16%	13 Jan →
mirage	10–13	0.02	13%	12 Jan →
inferno	7–13	-0.05	14%	12 Jan →
dust2	3–13	-0.08	17%	11 Jan →
nuke	4–13	-0.08	17%	11 Jan →
overpass	4–13	0.00	10%	8 Jan →
ancient	13–8	0.05	12%	8 Jan →
overpass	13–9	-0.00	12%	8 Jan →
inferno	14–16	0.02	12%	7 Jan →
inferno	13–9	0.01	5%	6 Jan →
ancient	16–13	0.01	16%	6 Jan →
mirage	5–13	-0.09	19%	6 Jan →
mirage	13–4	0.02	16%	4 Jan →
nuke	13–5	0.05	10%	4 Jan →
nuke	13–6	-0.01	9%	4 Jan →
inferno	10–13	-0.02	20%	4 Jan →
mirage	13–10	-0.02	13%	2 Jan →
inferno	9–13	-0.08	8%	2 Jan →
nuke	10–1	0.03	13%	2 Jan →
overpass	11–13	-0.04	9%	1 Jan →
mirage	13–5	0.05	11%	25 Dec →
overpass	13–6	0.03	9%	25 Dec →
nuke	7–13	0.00	17%	25 Dec →
overpass	7–13	-0.01	18%	22 Dec →
overpass	7–13	-0.03	16%	20 Dec →
inferno	13–9	0.06	11%	20 Dec →
inferno	10–13	0.03	9%	19 Dec →
overpass	15–15	-0.01	19%	19 Dec →
inferno	7–13	-0.04	12%	17 Dec →
train	13–8	0.03	19%	14 Dec →
inferno	15–15	-0.01	13%	14 Dec →
ancient	13–10	0.09	14%	13 Dec →
overpass	10–13	-0.05	7%	13 Dec →
nuke	3–13	0.02	11%	13 Dec →
train	10–13	-0.05	5%	7 Sept →
inferno	9–0	0.12	15%	31 Aug →
overpass	11–13	0.02	23%	31 Aug →
inferno	9–13	-0.05	5%	30 Aug →
vertigo	4–13	-0.04	5%	30 Aug →
overpass	13–11	-0.03	13%	30 Aug →
inferno	16–14	-0.02	10%	24 Aug →
ancient	6–13	-0.06	8%	24 Aug →
nuke	6–13	-0.02	16%	24 Aug →
overpass	13–4	-0.04	18%	24 Aug →
overpass	5–13	-0.06	11%	23 Aug →
nuke	13–5	0.02	7%	23 Aug →
overpass	13–10	-0.05	10%	22 Aug →
mirage	9–13	0.01	11%	22 Aug →
overpass	8–13	-0.04	14%	17 Aug →
nuke	15–15	-0.02	7%	17 Aug →
nuke	13–7	-0.01	12%	14 Aug →
ancient	15–15	-0.03	11%	13 Aug →
train	6–13	0.01	16%	13 Aug →
overpass	13–8	-0.06	15%	13 Aug →
ancient	6–13	-0.02	17%	12 Aug →
dust2	6–13	-0.03	9%	10 Aug →
nuke	8–13	-0.06	10%	9 Aug →
nuke	6–13	-0.04	8%	9 Aug →
ancient	16–14	-0.01	15%	9 Aug →
mirage	14–16	-0.06	8%	9 Aug →