apolo — CS2 Stats

BR76561198821353091[U:1:861087363]Steam profile ↗✓ No bans

2,279Tracked matches57%Win rate2022Tracked since

CSDB Rating6.2 SolidHybrid Rifler

Ladder ranks via Leetify

Performance scores

Aim61

Positioning71

Utility66

0–100 skill scores via Leetify.

Recent form

STEADY52–48Last 10052%Win rateLLLWWWLWLW

Last 10 vs previous 10: -20pp win rate · -0.01 avg rating

Player DNA

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

Aim6.1

Aggression7.7

Utility6.6

Positioning7.1

Opening Duels3.6

Clutch3.2

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 donk 88% playstyle similarity

Most alike: positioning profile, 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

T-side openings. Opening success drops from 57% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 616ms 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

Aim6.1

Positioning7.1

Utility6.6

Mechanics5.8

Opening Duels3.6

Win Impact7.2

Composite 6.2/10 (Solid), 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 rating0.03+0.02

first ⅓ avg 0.00 → last ⅓ avg 0.03

Reaction time619ms−15ms

first ⅓ avg 634ms → last ⅓ avg 619ms

Headshot accuracy16.3%−1.4%

first ⅓ avg 17.7% → last ⅓ avg 16.3%

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

0.11Best rating — mirage 4–13

13–2Biggest win — mirage

4Longest win streak

L3Current streak

9–7In matches decided by ≤2 rounds

12Overtime games

Map breakdown

mirageBest map · 68% over 25ancientWeakest map · 33% over 30

Map	Grade	Played	Record	Win rate	Avg rating
ancient	D	30	10–20	33%	0.00
mirage	S	25	17–8	68%	0.02
dust2	A	23	13–10	57%	0.01
anubis	A	16	9–7	56%	0.00
inferno	—	3	0–3	0%	-0.05
vertigo	—	1	1–0	100%	-0.00
overpass	—	1	1–0	100%	-0.03
train	—	1	1–0	100%	0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 30). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,450Matches

51%Win rate

1.16Avg K/D

80.0ADR

47%Headshot %

Clutches & streaks

36%1v1 clutch win

24%1v2 clutch win

11Longest win streak

Recent Faceit resultsLWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	562	53%	1.18	17.4
Mirage	550	51%	1.08	16.1
Anubis	468	52%	1.23	17.4
Dust2	392	54%	1.11	16.2
Vertigo	102	57%	1.27	17.3
Nuke	80	39%	0.99	14.9
Inferno	40	50%	1.22	16.7
Overpass	36	56%	1.25	16.0

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.

15.9%Headshot accuracy

34.5%Accuracy (enemy spotted)

37.6%Spray accuracy

76.0%Counter-strafing

10.1°Preaim

616msReaction time

31.8%T opening success

57.2%CT opening success

0.64Enemies flashed / flash

9.2%Flash assists

7.95HE damage / grenade

7.51Flashes / 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 31.7854% — 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 30 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
mirage	4–13	0.11	25%	27 Aug →
mirage	1–13	0.08	35%	27 Aug →
ancient	13–16	-0.01	16%	6 Aug →
dust2	4–3	0.10	38%	29 Jul →
mirage	13–9	0.02	13%	28 Jul →
dust2	13–8	0.00	8%	26 Apr →
mirage	5–13	-0.08	21%	25 Apr →
vertigo	13–4	-0.00	10%	16 Apr →
mirage	7–13	-0.03	10%	16 Apr →
anubis	13–5	0.05	31%	12 Apr →
dust2	13–3	0.08	17%	12 Apr →
ancient	13–5	0.07	7%	2 Apr →
mirage	9–13	-0.01	9%	2 Apr →
ancient	13–7	0.10	15%	2 Apr →
ancient	11–13	0.00	14%	1 Apr →
mirage	10–13	-0.01	16%	1 Apr →
ancient	13–8	0.00	20%	24 Mar →
ancient	13–11	0.04	19%	24 Mar →
mirage	13–2	0.10	20%	24 Mar →
mirage	13–10	0.00	10%	24 Mar →
ancient	8–13	0.02	19%	20 Mar →
anubis	13–11	0.09	10%	20 Mar →
mirage	13–5	0.03	17%	20 Mar →
anubis	7–13	-0.02	13%	20 Mar →
mirage	13–10	0.03	11%	19 Mar →
anubis	13–6	-0.03	18%	19 Mar →
anubis	11–13	-0.01	10%	18 Mar →
ancient	9–13	0.06	24%	18 Mar →
ancient	7–13	0.01	16%	18 Mar →
dust2	13–8	-0.02	11%	18 Mar →
mirage	13–6	0.09	10%	18 Mar →
anubis	5–13	-0.01	10%	18 Mar →
ancient	8–13	-0.06	13%	18 Mar →
mirage	13–7	0.03	13%	17 Mar →
dust2	13–10	0.01	12%	16 Mar →
mirage	14–16	0.02	19%	16 Mar →
dust2	6–13	-0.01	32%	16 Mar →
ancient	9–13	0.04	16%	16 Mar →
ancient	13–16	-0.04	11%	16 Mar →
ancient	13–9	0.06	20%	16 Mar →
dust2	4–13	-0.03	7%	16 Mar →
dust2	8–13	-0.09	14%	13 Mar →
mirage	13–10	0.08	9%	13 Mar →
anubis	13–9	0.03	18%	13 Mar →
mirage	13–10	-0.00	15%	13 Mar →
dust2	13–10	-0.00	18%	13 Mar →
ancient	14–16	-0.05	19%	12 Mar →
mirage	3–13	-0.04	25%	12 Mar →
dust2	16–19	-0.04	19%	12 Mar →
mirage	13–7	0.02	18%	12 Mar →
dust2	14–16	0.00	17%	12 Mar →
ancient	6–13	-0.02	18%	12 Mar →
mirage	13–8	0.02	10%	12 Mar →
anubis	13–5	0.01	22%	11 Mar →
ancient	11–13	-0.02	12%	11 Mar →
dust2	13–10	-0.00	13%	11 Mar →
ancient	6–13	-0.02	10%	11 Mar →
mirage	13–9	-0.00	20%	11 Mar →
dust2	13–11	-0.00	12%	11 Mar →
ancient	10–13	-0.03	25%	11 Mar →
ancient	10–13	-0.02	10%	10 Mar →
overpass	16–14	-0.03	21%	10 Mar →
inferno	7–13	-0.01	18%	10 Mar →
ancient	8–13	-0.04	13%	10 Mar →
anubis	8–13	-0.03	26%	9 Mar →
dust2	5–13	-0.01	5%	9 Mar →
train	13–6	0.03	30%	9 Mar →
dust2	13–8	0.06	27%	9 Mar →
anubis	13–4	0.03	23%	9 Mar →
dust2	13–4	0.07	26%	8 Mar →
ancient	13–16	0.01	22%	8 Mar →
anubis	13–9	-0.02	22%	8 Mar →
ancient	13–9	0.01	13%	8 Mar →
ancient	13–3	0.00	20%	8 Mar →
dust2	23–25	0.04	27%	8 Mar →
mirage	13–10	0.07	22%	7 Mar →
anubis	10–13	0.04	24%	7 Mar →
dust2	8–13	-0.01	16%	7 Mar →
mirage	13–11	-0.01	14%	7 Mar →
ancient	13–6	0.04	23%	7 Mar →
inferno	12–16	-0.04	15%	7 Mar →
ancient	13–8	0.02	13%	6 Mar →
dust2	7–13	-0.05	26%	6 Mar →
anubis	13–9	0.01	17%	5 Mar →
anubis	8–13	-0.06	17%	5 Mar →
ancient	4–13	-0.01	21%	5 Mar →
mirage	13–10	0.04	15%	4 Mar →
ancient	7–13	-0.04	9%	4 Mar →
anubis	8–13	-0.02	16%	3 Mar →
anubis	13–11	-0.03	12%	28 Feb →
ancient	13–6	0.06	9%	28 Feb →
dust2	8–13	0.02	14%	27 Feb →
mirage	16–12	0.01	16%	27 Feb →
inferno	8–13	-0.09	28%	26 Feb →
ancient	9–13	0.04	15%	25 Feb →
dust2	16–13	-0.03	5%	24 Feb →
dust2	13–11	-0.01	16%	21 Feb →
mirage	13–10	-0.04	19%	21 Feb →
ancient	2–13	-0.11	10%	20 Feb →
dust2	13–11	0.05	10%	20 Feb →