sapienza — CS2 Stats

IT76561198122917975[U:1:162652247]Steam profile ↗✓ No bans

5,111Tracked matches33%Win rate2020Tracked since

CSDB Rating4.0 DevelopingSupport

FaceitLevel 10 · 2,302 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim48

Positioning43

Utility77

0–100 skill scores via Leetify.

Recent form

COLD44–56Last 10044%Win rateLWLLWLLLLL

Last 10 vs previous 10: -30pp win rate · -0.04 avg rating

Player DNA

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

Aim4.8

Aggression2.0

Utility7.7

Positioning4.3

Opening Duels0.0

Clutch3.2

Effective flashesHigh utility contribution

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 75% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-fight frequency; 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

Strengths

Utility. Utility score of 77 — grenade impact well above the norm.

Areas to improve

Reaction time. 600ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 65% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Positioning4.3

Utility7.7

Mechanics3.3

Opening Duels0.6

Win Impact0.0

Composite 4.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00+0.03

first ⅓ avg -0.02 → last ⅓ avg 0.00

Reaction time599ms+2ms

first ⅓ avg 597ms → last ⅓ avg 599ms

Headshot accuracy20.0%+1.4%

first ⅓ avg 18.6% → last ⅓ avg 20.0%

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

0.14Best rating — mirage 13–7

13–3Biggest win — inferno

4Longest win streak

7–13In matches decided by ≤2 rounds

14Overtime games

Map breakdown

infernoBest map · 58% over 24mirageWeakest map · 35% over 17

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	26	10–16	38%	-0.01
inferno	A	24	14–10	58%	-0.01
mirage	C	17	6–11	35%	0.01
nuke	B	13	6–7	46%	0.00
overpass	B	10	5–5	50%	-0.02
ancient	—	4	2–2	50%	-0.04
anubis	—	3	1–2	33%	-0.02
cache	—	2	0–2	0%	-0.02
train	—	1	0–1	0%	-0.07

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (35% over 17). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

5,804Matches

51%Win rate

0.94Avg K/D

71.0ADR

49%Headshot %

Clutches & streaks

36%1v1 clutch win

17%1v2 clutch win

16Longest win streak

Recent Faceit resultsWLLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	807	48%	0.94	13.7
Inferno	610	57%	0.97	13.9
Dust2	608	48%	0.92	13.5
Anubis	520	50%	0.91	14.0
Nuke	491	57%	1.00	13.9
Ancient	242	51%	0.91	13.3
Overpass	137	44%	0.89	13.0
Vertigo	56	59%	0.93	13.6

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.

20.2%Headshot accuracy

32.3%Accuracy (enemy spotted)

34.2%Spray accuracy

64.9%Counter-strafing

11.6°Preaim

600msReaction time

20.4%T opening success

35.1%CT opening success

0.72Enemies flashed / flash

10.6%Flash assists

10.07HE damage / grenade

14.84Flashes / 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 20.4177% — 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.

35% win rate across 17 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
cache	11–13	0.01	15%	12 Aug →
inferno	13–6	0.03	14%	10 Aug →
dust2	11–13	-0.03	21%	10 Aug →
dust2	11–13	0.00	21%	4 Aug →
nuke	13–10	-0.01	25%	3 Aug →
dust2	8–13	-0.07	14%	3 Aug →
dust2	3–13	-0.10	21%	2 Aug →
anubis	4–13	-0.04	18%	1 Aug →
dust2	13–16	0.02	25%	1 Aug →
nuke	10–13	0.06	29%	1 Aug →
mirage	14–16	0.00	24%	1 Aug →
anubis	11–13	-0.04	21%	29 Jul →
mirage	13–7	0.14	23%	10 Jun →
dust2	13–4	0.04	23%	10 Jun →
inferno	13–5	0.03	20%	8 Jun →
mirage	12–16	-0.01	20%	7 Jun →
mirage	10–13	0.01	19%	7 Jun →
overpass	13–9	0.00	16%	6 Jun →
mirage	8–13	0.02	26%	5 Jun →
inferno	13–5	0.02	11%	21 May →
dust2	8–13	-0.05	20%	21 May →
nuke	11–13	-0.02	23%	15 May →
nuke	8–13	0.02	22%	15 May →
mirage	3–13	-0.02	29%	14 May →
inferno	13–8	0.02	11%	12 May →
mirage	9–13	-0.01	11%	12 May →
inferno	13–6	-0.01	25%	12 May →
dust2	13–7	0.05	23%	12 May →
mirage	7–13	0.06	23%	11 May →
cache	8–13	-0.04	14%	11 May →
nuke	14–16	0.01	13%	10 May →
overpass	13–9	-0.02	15%	5 May →
dust2	13–10	0.04	28%	5 May →
nuke	13–11	-0.00	24%	4 May →
inferno	13–10	-0.03	24%	2 May →
dust2	11–13	0.08	26%	2 May →
nuke	13–7	0.05	22%	1 May →
mirage	13–5	0.08	16%	19 Apr →
dust2	13–9	0.02	21%	19 Apr →
inferno	9–13	-0.04	13%	17 Apr →
dust2	13–10	-0.02	18%	16 Apr →
overpass	13–10	0.02	17%	13 Apr →
dust2	13–11	-0.02	22%	9 Apr →
overpass	12–16	-0.05	19%	30 Mar →
inferno	13–5	-0.01	16%	30 Mar →
dust2	7–13	-0.08	28%	30 Mar →
inferno	13–10	-0.02	19%	30 Mar →
inferno	2–13	-0.08	24%	18 Mar →
inferno	19–22	0.02	18%	17 Mar →
inferno	13–3	0.05	19%	11 Mar →
inferno	8–13	-0.02	30%	10 Mar →
inferno	9–13	-0.02	20%	8 Mar →
dust2	14–16	-0.05	10%	8 Mar →
inferno	13–7	0.01	19%	7 Mar →
anubis	13–6	0.02	16%	5 Mar →
inferno	8–13	-0.02	36%	5 Mar →
mirage	6–13	-0.05	15%	1 Mar →
dust2	14–16	0.04	19%	1 Mar →
nuke	7–13	-0.06	16%	1 Mar →
dust2	12–16	-0.01	13%	24 Feb →
dust2	6–13	-0.04	10%	23 Feb →
ancient	13–11	-0.06	12%	23 Feb →
nuke	16–14	0.06	14%	14 Feb →
overpass	13–11	-0.03	15%	14 Feb →
nuke	11–13	0.05	16%	14 Feb →
overpass	7–13	-0.02	13%	12 Feb →
mirage	13–8	0.01	22%	11 Feb →
inferno	8–13	-0.05	22%	9 Feb →
mirage	10–13	-0.01	20%	9 Feb →
ancient	4–13	-0.01	10%	2 Feb →
nuke	12–16	-0.06	21%	31 Jan →
inferno	13–8	0.01	21%	30 Jan →
dust2	6–13	-0.07	19%	29 Jan →
inferno	4–13	0.03	24%	29 Dec →
mirage	13–10	-0.02	24%	22 Dec →
inferno	13–8	0.03	17%	22 Dec →
overpass	6–13	-0.04	18%	21 Dec →
inferno	13–11	-0.09	8%	18 Dec →
overpass	7–12	-0.05	14%	15 Dec →
mirage	13–5	-0.06	17%	10 Dec →
dust2	13–5	-0.03	17%	10 Dec →
nuke	13–8	-0.02	21%	7 Dec →
dust2	13–11	-0.01	23%	5 Dec →
ancient	8–13	-0.09	11%	27 Nov →
ancient	11–3	0.01	22%	15 Nov →
dust2	13–6	-0.01	18%	15 Nov →
nuke	19–15	-0.02	23%	15 Nov →
mirage	6–13	0.00	21%	15 Nov →
mirage	13–5	0.04	23%	15 Nov →
inferno	7–13	-0.01	27%	15 Nov →
dust2	13–8	0.02	26%	14 Nov →
mirage	7–13	-0.01	18%	14 Nov →
inferno	14–16	-0.01	22%	14 Nov →
dust2	2–13	-0.07	8%	14 Nov →
inferno	13–5	-0.03	24%	13 Nov →
train	8–13	-0.07	19%	25 Oct →
overpass	6–13	-0.05	18%	1 Oct →
dust2	14–16	0.01	19%	28 Sept →
overpass	13–10	-0.01	10%	21 Aug →
dust2	9–13	-0.04	6%	19 Aug →