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apollo — CS2 Stats

76561198881211048[U:1:920945320]✓ No bans

2,192Tracked matches57%Win rate2021Tracked since
CSDB Rating4.8 Developing
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGapolloFACEITLevel 4STANDINGTop 81.0% of rankedcsdb.gg/stats

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Performance scores

Aim37
Positioning50
Utility65

0–100 skill scores via Leetify.

Recent form

STEADY51–48–1Last 10051%Win rateWLLWWLWLWW

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

Player DNA

Aim3.7
Aggression5.1
Utility6.5
Positioning5.0
Opening Duels0.2
Clutch3.4

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

NiKo

Plays most like NiKo 80% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower opening-duel success; 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

CT openings. Opening success drops from 42% on T to 20% on CT — first contacts on the defending side are being lost.

Reaction time. 602ms 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

Aim3.7
Positioning5.0
Utility6.5
Mechanics5.8
Opening Duels1.4
Win Impact7.2

Composite 4.8/10 (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 rating0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg 0.00
Reaction time586ms−6ms
first ⅓ avg 592ms → last ⅓ avg 586ms
Headshot accuracy11.5%−1.4%
first ⅓ avg 12.8% → last ⅓ avg 11.5%

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

0.17Best rating — dust2 13–6
13–1Biggest win — dust2
5Longest win streak
9–9In matches decided by ≤2 rounds
13Overtime games

Map breakdown

infernoBest map · 58% over 12nukeWeakest map · 43% over 14
MapGradePlayedRecordWin rateAvg rating
mirageA2514–1156%0.00
dust2B168–850%-0.00
nukeC146–843%0.01
anubisC146–843%0.01
infernoA127–558%0.01
trainB105–550%0.00
ancientA95–456%0.01

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (43% over 14). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,273Matches
49%Win rate
1.02Avg K/D
78.6ADR
41%Headshot %

Clutches & streaks

37%1v1 clutch win
23%1v2 clutch win
10Longest win streak

Recent Faceit resultsLWLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage40652%1.0114.1
Dust216853%1.0014.5
Inferno15847%1.0714.9
Anubis14649%1.0315.4
Nuke10946%1.0515.2
Ancient10350%1.0714.5
Vertigo9437%0.8913.3
Train4045%0.9414.9

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.

12.1%Headshot accuracy
30.8%Accuracy (enemy spotted)
33.1%Spray accuracy
76.3%Counter-strafing
13.2°Preaim
602msReaction time
41.5%T opening success
20.3%CT opening success
0.53Enemies flashed / flash
4.0%Flash assists
10.12HE damage / grenade
11.64Flashes / 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.

  1. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 13.2163° — above the 12° mark we flag

    Aim Training →
  2. 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 12.0621% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Nuke

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

43% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–60.0213%27 Jul →
mirage2–70.000%11 Jul →
mirage8–13-0.0010%11 Jul →
nuke13–9-0.029%11 Jul →
nuke13–10-0.0016%11 Jul →
nuke0–110.000%11 Jul →
dust213–5-0.0313%11 Jul →
dust22–6-0.010%11 Jul →
anubis13–90.0114%11 Jul →
mirage13–7-0.0911%2 Apr →
inferno13–9-0.0112%1 Apr →
mirage10–13-0.005%1 Apr →
anubis10–13-0.0316%30 Mar →
mirage13–80.039%30 Mar →
dust213–4-0.0218%30 Mar →
mirage13–110.0812%30 Mar →
mirage13–30.0720%29 Mar →
dust27–13-0.0712%28 Mar →
ancient9–13-0.0514%28 Mar →
train8–130.0020%28 Mar →
nuke13–20.0513%28 Mar →
anubis11–13-0.0111%28 Mar →
anubis22–180.067%27 Mar →
anubis7–130.047%21 Mar →
dust211–13-0.0411%21 Mar →
mirage16–140.0118%21 Mar →
mirage13–70.048%21 Mar →
inferno16–120.0711%21 Mar →
dust26–13-0.0113%20 Mar →
anubis13–11-0.0112%20 Mar →
dust21–13-0.0518%20 Mar →
train13–60.0110%20 Mar →
mirage10–13-0.0116%19 Mar →
anubis16–140.0517%19 Mar →
mirage10–13-0.0213%7 Mar →
inferno8–13-0.0714%2 Mar →
nuke1–13-0.0417%2 Mar →
anubis19–160.0119%1 Mar →
train10–130.067%1 Mar →
mirage13–9-0.0410%1 Mar →
mirage13–11-0.0415%1 Mar →
ancient8–130.066%1 Mar →
dust28–13-0.120%20 Feb →
ancient5–13-0.016%19 Feb →
anubis11–130.079%19 Feb →
nuke2–13-0.093%19 Feb →
train13–90.0415%19 Feb →
train5–13-0.026%19 Feb →
inferno13–8-0.029%19 Feb →
dust213–80.046%18 Feb →
dust213–10.0214%18 Feb →
inferno5–13-0.017%18 Feb →
ancient11–130.0812%18 Feb →
ancient13–8-0.0511%18 Feb →
train13–7-0.0019%18 Feb →
ancient8–20.0315%18 Feb →
train11–13-0.018%18 Feb →
dust21–7-0.0224%18 Feb →
ancient13–40.038%18 Feb →
inferno8–13-0.0412%18 Feb →
mirage13–20.059%17 Feb →
mirage16–130.0016%17 Feb →
inferno13–30.0716%17 Feb →
nuke14–16-0.035%17 Feb →
train13–4-0.0012%17 Feb →
dust213–100.0513%17 Feb →
mirage9–130.0414%17 Feb →
inferno6–13-0.096%17 Feb →
mirage9–130.0311%17 Feb →
nuke8–130.048%17 Feb →
anubis13–50.0713%17 Feb →
nuke6–13-0.0612%17 Feb →
nuke13–9-0.0010%16 Feb →
inferno13–90.0516%16 Feb →
mirage11–13-0.0517%16 Feb →
mirage9–130.0518%16 Feb →
mirage16–14-0.0013%16 Feb →
dust213–90.0219%16 Feb →
dust25–13-0.028%16 Feb →
mirage5–13-0.1111%16 Feb →
anubis13–160.0111%16 Feb →
dust213–60.1719%16 Feb →
train6–13-0.0711%16 Feb →
mirage13–50.0315%16 Feb →
nuke10–130.0514%16 Feb →
mirage15–15-0.0412%15 Feb →
ancient16–140.0212%15 Feb →
anubis6–130.0111%15 Feb →
mirage13–90.0514%15 Feb →
nuke14–16-0.0322%15 Feb →
inferno13–60.1216%15 Feb →
inferno13–10-0.0411%15 Feb →
dust216–140.0016%15 Feb →
nuke13–10.1012%15 Feb →
train13–100.0213%15 Feb →
anubis11–13-0.018%15 Feb →
ancient13–11-0.037%15 Feb →
anubis4–13-0.0515%15 Feb →
inferno10–130.059%15 Feb →
nuke13–90.1013%15 Feb →

Match data via Leetify.

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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