BOXEL

BOXEL — CS2 Stats

76561198810543867[U:1:850278139]Steam profile ↗✓ No bans

1,816Tracked matches57%Win rate2020Tracked since
3,496Hours in CS19Hrs last 2 wks
CSDB Rating6.6 SolidAggressive Rifler
FaceitLevel 10 · 2,441 ELOTop 12.4% of ranked FACEIT players
WingmanSupreme Master First Class
Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=218), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 10 median
Headshot rate58.6%52.8%
Shot accuracy9.7%13.7%
Kill/death ratio1.411.08
Match win rate59.0%49.2%

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CSDB.GGBOXELFACEITLevel 10 · 2,441 ELOSTANDINGTop 12.4% of rankedcsdb.gg/stats

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Performance scores

Aim80
Positioning58
Utility69

0–100 skill scores via Leetify.

Recent form

STEADY59347Last 10059%Win rateWWLLLLWWWW

Last 10 vs previous 10: +0pp win rate · -0.06 avg rating

Player DNA

Primary style: Aggressive RiflerTakes opening fights often, backed by a strong aim profile.

Aim8.0
Aggression7.8
Utility6.9
Positioning5.8
Opening Duels4.1
Clutch3.8

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

b1t

Plays most like b1t 92% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

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 36% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim8.0
Positioning5.8
Utility6.9
Mechanics6.0
Opening Duels4.1
Win Impact7.4

Composite 6.6/10 (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 rating0.02−0.02
first ⅓ avg 0.04 → last ⅓ avg 0.02
Reaction time523ms+9ms
first ⅓ avg 514ms → last ⅓ avg 523ms
Headshot accuracy20.2%−2.3%
first ⅓ avg 22.5% → last ⅓ avg 20.2%

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

0.15Best rating — inferno 13–4
130Biggest win — mirage
6Longest win streak
W2Current streak
73In matches decided by ≤2 rounds
4Overtime games

Map breakdown

nukeBest map · 80% over 5infernoWeakest map · 47% over 15
MapGradePlayedRecordWin rateAvg rating
dust2A25151060%0.03
infernoB157847%0.04
ancientB137654%0.04
cacheB126650%0.02
anubisA117464%0.02
mirageS118373%-0.00
overpassS64267%0.05
nukeS54180%0.07
train21150%0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (47% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

89,110Lifetime kills
1.41K/D · Top 10% of Level 10 players
3,590Matches
59.0%Match win rate · Top 5% of Level 10 players
58.6%Headshot % · Top 50% of Level 10 players
9.7%Shot accuracy
11,592MVPs
1,930Hours (in match)
3,693Bombs planted
1,034Bombs defused

Most-used weapons

AK-4736,573
AWP5,336
SSG 083,234
MP92,337
P2501,526

Lifetime map wins

6,112inferno
5,679dust2
2,603train
1,685vertigo
1,436nuke
921cbble
117office
36lake

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

553Matches
59%Win rate
1.26Avg K/D
82.5ADR
48%Headshot %

Clutches & streaks

39%1v1 clutch win
26%1v2 clutch win
10Longest win streak

Recent Faceit resultsWWWLW

MapMatchesWin rateAvg K/DAvg kills
Dust29063%1.3215.5
Ancient7868%1.2915.9
Mirage5143%1.0716.3
Anubis4360%1.1117.1
Inferno3866%1.3116.7
Train1776%1.3417.7
Nuke1656%1.4617.6
Overpass1540%1.5120.1

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.

20.5%Headshot accuracy
34.9%Accuracy (enemy spotted)
42.6%Spray accuracy
76.8%Counter-strafing
9.6°Preaim
515msReaction time
36.2%T opening success
56.8%CT opening success
0.64Enemies flashed / flash
8.2%Flash assists
8.85HE damage / grenade
13.15Flashes / 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

    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 36.2025% — below the 40% mark we flag

Spend your practice time on Inferno

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

47% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
cache13–5-0.0014%26 Aug
anubis13–100.0020%26 Aug
dust211–13-0.0120%23 Aug
ancient10–13-0.0433%23 Aug
dust29–13-0.0313%14 Aug
dust216–19-0.0412%14 Aug
mirage13–3-0.0116%10 Aug
cache13–80.0123%10 Aug
nuke13–9-0.0427%10 Aug
anubis13–50.0813%9 Aug
nuke13–60.0720%8 Aug
ancient13–50.1119%4 Aug
cache12–120.0213%2 Aug
ancient9–130.0818%2 Aug
nuke9–130.0823%1 Aug
ancient7–13-0.0320%1 Aug
nuke13–60.1124%28 Jul
cache13–11-0.0130%28 Jul
mirage13–60.0119%22 Jul
nuke13–40.1318%21 Jul
cache13–80.0925%20 Jul
cache6–13-0.0523%18 Jul
mirage13–40.0824%18 Jul
cache2–13-0.0613%18 Jul
ancient13–20.1022%18 Jul
anubis13–80.0327%16 Jul
ancient8–13-0.0119%16 Jul
inferno12–120.0124%16 Jul
ancient7–130.0722%16 Jul
mirage4–13-0.0317%16 Jul
dust213–11-0.0023%15 Jul
mirage13–7-0.0116%9 Jul
ancient13–30.0115%9 Jul
dust26–130.0120%6 Jul
mirage13–9-0.0112%6 Jul
overpass13–40.0919%5 Jul
inferno4–13-0.0812%4 Jul
cache9–130.0116%4 Jul
anubis13–60.0224%3 Jul
anubis13–70.0417%3 Jul
inferno13–110.0228%2 Jul
inferno13–11-0.0420%1 Jul
dust215–150.0622%30 Jun
ancient14–160.0517%30 Jun
dust28–13-0.0818%30 Jun
mirage13–00.000%30 Jun
ancient13–70.0126%30 Jun
dust213–70.038%29 Jun
anubis13–2-0.0216%28 Jun
dust28–13-0.0224%28 Jun
dust213–110.0017%28 Jun
dust213–100.0113%28 Jun
inferno13–90.0312%28 Jun
ancient13–50.0823%28 Jun
anubis8–130.0010%28 Jun
dust210–130.0720%27 Jun
mirage7–13-0.0511%27 Jun
inferno12–120.0819%20 Jun
inferno13–40.1530%17 Jun
inferno13–50.0520%13 Jun
cache3–13-0.0328%13 Jun
inferno10–130.0915%13 Jun
dust213–60.0711%10 Jun
dust213–40.0728%9 Jun
dust213–70.0128%8 Jun
ancient13–2-0.0124%8 Jun
overpass13–20.0015%7 Jun
dust213–20.0422%7 Jun
inferno12–12-0.0125%4 Jun
dust210–130.0427%3 Jun
mirage13–4-0.0139%3 Jun
inferno9–13-0.0118%2 Jun
dust213–110.0518%2 Jun
anubis10–130.0017%18 May
dust210–130.0524%18 May
dust213–90.0723%18 May
overpass13–20.1213%17 May
cache13–10.0610%14 May
inferno7–130.0419%14 May
ancient13–80.0422%14 May
cache12–120.0835%11 May
cache13–70.1029%9 May
anubis13–8-0.0221%29 Apr
inferno8–130.0825%28 Apr
anubis6–130.0116%15 Apr
overpass13–80.0228%11 Apr
mirage2–90.0323%11 Apr
inferno13–50.1125%22 Mar
overpass12–120.0516%19 Feb
dust213–40.0528%15 Feb
dust213–30.1023%6 Feb
dust216–140.0220%22 Jan
anubis8–130.1125%22 Jan
dust213–80.1230%17 Jan
mirage13–5-0.0224%14 Jan
train9–13-0.0027%9 Jan
overpass11–130.0215%9 Jan
inferno13–50.0611%9 Jan
dust213–6-0.0221%3 Jan
train13–70.1023%2 Jan

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 102K ELO1,000 Matches
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