Sippo.P — CS2 Stats

76561198996173199[U:1:1035907471]Steam profile ↗✓ No bans

1,013Tracked matches39%Win rate2020Tracked since

CSDB Rating4.2 Developing

FaceitLevel 3Top 90.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim56

Positioning34

Utility51

0–100 skill scores via Leetify.

Recent form

STEADY47–49–4Last 10047%Win rateLLWLWWWLLL

Last 10 vs previous 10: +0pp win rate · +0.04 avg rating

Player DNA

Aim5.6

Aggression1.4

Utility5.1

Positioning3.4

Opening Duels0.0

Clutch4.0

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 70% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower aim profile; lower opening-fight frequency.

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

Reaction time. 604ms 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

Aim5.6

Positioning3.4

Utility5.1

Mechanics6.5

Opening Duels0.0

Win Impact1.4

Composite 4.2/10 (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 rating-0.03−0.00

first ⅓ avg -0.03 → last ⅓ avg -0.03

Reaction time623ms−30ms

first ⅓ avg 653ms → last ⅓ avg 623ms

Headshot accuracy15.3%+4.0%

first ⅓ avg 11.3% → last ⅓ avg 15.3%

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

0.13Best rating — inferno 1–2

13–0Biggest win — nuke

5Longest win streak

L2Current streak

8–9In matches decided by ≤2 rounds

5Overtime games

Map breakdown

trainBest map · 83% over 6ancientWeakest map · 30% over 10

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	26	15–11	58%	-0.02
inferno	B	23	11–12	48%	-0.03
anubis	B	11	5–6	45%	-0.04
ancient	D	10	3–7	30%	-0.04
dust2	C	10	4–6	40%	-0.03
overpass	C	9	4–5	44%	-0.05
train	S	6	5–1	83%	-0.02
mirage	—	2	0–2	0%	-0.03
cache	—	2	0–2	0%	-0.04
office	—	1	0–1	0%	-0.08

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

484Matches

49%Win rate

0.80Avg K/D

69.1ADR

38%Headshot %

Clutches & streaks

40%1v1 clutch win

21%1v2 clutch win

8Longest win streak

Recent Faceit resultsLWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	59	54%	0.94	12.8
Anubis	56	41%	0.86	12.0
Nuke	33	55%	0.98	11.9
Dust2	21	38%	0.73	10.1
Overpass	20	50%	0.65	10.2
Ancient	16	25%	0.76	12.6
Mirage	15	47%	0.65	11.3
Cache	6	33%	1.10	19.5

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.

15.3%Headshot accuracy

32.4%Accuracy (enemy spotted)

37.2%Spray accuracy

79.1%Counter-strafing

11.3°Preaim

604msReaction time

23.3%T opening success

26.5%CT opening success

0.54Enemies flashed / flash

4.3%Flash assists

8.88HE damage / grenade

3.53Flashes / 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.

Grenades & Utility
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.5302 — below the 4 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 23.2751% — 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.

30% win rate across 10 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	4–13	-0.01	7%	26 Aug →
dust2	10–13	-0.06	28%	26 Aug →
nuke	13–8	0.05	13%	25 Aug →
inferno	1–2	0.13	30%	25 Aug →
nuke	13–5	-0.02	9%	16 Aug →
inferno	13–6	0.00	10%	14 Aug →
nuke	13–6	0.01	15%	14 Aug →
ancient	11–13	-0.07	6%	14 Aug →
mirage	10–13	0.00	8%	14 Aug →
nuke	7–13	-0.01	12%	14 Aug →
inferno	11–13	-0.05	3%	14 Aug →
cache	10–13	-0.04	10%	13 Aug →
anubis	13–10	-0.07	6%	13 Aug →
nuke	3–13	-0.05	19%	31 Jul →
anubis	6–13	-0.07	36%	31 Jul →
dust2	14–16	-0.04	30%	31 Jul →
inferno	13–10	-0.02	24%	31 Jul →
anubis	13–6	0.00	27%	23 May →
ancient	13–11	-0.03	16%	15 May →
cache	11–13	-0.03	6%	15 May →
nuke	2–13	-0.07	33%	30 Apr →
inferno	6–13	-0.02	19%	27 Apr →
nuke	15–15	-0.06	17%	20 Apr →
ancient	9–13	-0.04	18%	20 Apr →
inferno	15–15	-0.04	9%	20 Apr →
overpass	5–13	-0.11	18%	20 Apr →
anubis	13–4	-0.04	19%	17 Apr →
dust2	13–10	-0.03	18%	17 Apr →
anubis	10–13	0.00	7%	17 Apr →
inferno	13–8	-0.01	7%	17 Apr →
dust2	7–13	-0.06	8%	5 Apr →
inferno	1–13	-0.09	13%	5 Apr →
overpass	10–13	-0.07	4%	3 Apr →
overpass	10–13	-0.06	13%	3 Apr →
nuke	13–11	0.01	9%	11 Mar →
inferno	9–13	-0.09	3%	8 Mar →
nuke	8–13	0.01	26%	8 Mar →
nuke	3–13	-0.04	19%	8 Mar →
overpass	9–13	-0.07	9%	28 Feb →
anubis	11–13	-0.07	6%	22 Feb →
nuke	13–10	-0.01	13%	22 Feb →
nuke	13–2	0.09	15%	21 Feb →
dust2	13–11	-0.04	24%	21 Feb →
inferno	13–4	-0.03	9%	21 Feb →
nuke	11–13	-0.04	6%	30 Jan →
nuke	13–10	-0.06	7%	30 Jan →
ancient	15–15	-0.01	12%	21 Dec →
nuke	7–13	-0.02	10%	13 Dec →
overpass	13–6	0.02	11%	13 Dec →
dust2	13–11	0.01	21%	13 Dec →
inferno	7–13	-0.09	7%	19 Nov →
overpass	8–13	-0.02	8%	19 Nov →
inferno	6–13	-0.08	14%	17 Nov →
overpass	13–7	-0.06	8%	16 Nov →
dust2	10–13	-0.03	25%	16 Nov →
inferno	11–13	-0.02	25%	16 Nov →
inferno	13–6	-0.02	9%	15 Nov →
ancient	13–8	-0.06	13%	15 Nov →
inferno	13–8	-0.03	14%	19 Oct →
train	13–11	-0.01	11%	19 Oct →
overpass	13–7	-0.07	24%	12 Oct →
inferno	6–13	-0.08	2%	11 Oct →
train	13–9	-0.05	7%	9 Oct →
nuke	13–11	-0.01	8%	9 Oct →
nuke	13–11	-0.04	17%	13 Sept →
anubis	9–13	0.00	12%	29 Aug →
office	7–13	-0.08	40%	29 Aug →
nuke	11–13	-0.01	12%	29 Aug →
overpass	13–6	-0.01	18%	29 Aug →
nuke	8–13	-0.02	14%	27 Aug →
inferno	13–11	-0.02	13%	27 Aug →
nuke	13–0	-0.04	10%	24 Aug →
inferno	13–5	-0.05	6%	24 Aug →
dust2	9–1	0.01	13%	24 Aug →
mirage	2–13	-0.06	25%	2 Aug →
nuke	5–13	-0.06	22%	19 Jun →
anubis	5–13	-0.05	6%	29 May →
train	13–8	-0.05	8%	11 May →
anubis	13–8	-0.09	6%	11 May →
inferno	6–13	-0.02	8%	10 May →
ancient	13–3	-0.01	13%	10 May →
nuke	13–9	-0.04	12%	7 May →
ancient	2–13	-0.10	4%	4 May →
inferno	5–13	-0.07	15%	4 May →
ancient	4–13	-0.06	10%	2 May →
dust2	5–13	0.02	15%	2 May →
nuke	13–5	-0.01	21%	2 May →
inferno	13–4	0.06	8%	2 May →
train	13–5	-0.01	11%	2 May →
inferno	13–7	-0.01	2%	2 May →
nuke	13–9	-0.05	9%	2 May →
ancient	8–13	-0.04	9%	2 May →
anubis	5–13	-0.05	8%	2 May →
nuke	13–9	-0.04	9%	22 Apr →
inferno	13–6	-0.01	13%	22 Apr →
train	13–9	-0.00	16%	21 Apr →
anubis	13–8	-0.04	7%	21 Apr →
dust2	15–15	-0.05	12%	13 Apr →
train	10–13	0.00	8%	13 Apr →
nuke	13–4	0.01	11%	12 Apr →