Sorry I'm Horrible

Sorry I'm Horrible — CS2 Stats

US76561198422251731[U:1:461986003]Steam profile ↗✓ No bans

740Tracked matches45%Win rate2020Tracked since
CSDB Rating5.1 DevelopingHybrid Rifler
Ladder ranks via Leetify

Performance scores

Aim63
Positioning53
Utility47

0–100 skill scores via Leetify.

Recent form

STEADY52444Last 10052%Win rateLLLWWWLWLL

Last 10 vs previous 10: +0pp win rate · +0.02 avg rating

Player DNA

Primary style: Hybrid RiflerAim-led profile without a single dominant tendency.

Aim6.3
Aggression5.8
Utility4.7
Positioning5.3
Opening Duels1.6

Strong CT-side openerEffective flashes

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 85% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower utility contribution; 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 44% on CT to 29% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 579ms 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

Aim6.3
Positioning5.3
Utility4.7
Mechanics6.2
Opening Duels1.8
Win Impact3.3

Composite 5.1/10 (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-0.02−0.05
first ⅓ avg 0.03 → last ⅓ avg -0.02
Reaction time578ms−13ms
first ⅓ avg 591ms → last ⅓ avg 578ms
Headshot accuracy21.2%−4.2%
first ⅓ avg 25.5% → last ⅓ avg 21.2%

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

0.17Best rating — train 13–5
130Biggest win — vertigo
4Longest win streak
L3Current streak
126In matches decided by ≤2 rounds
5Overtime games

Map breakdown

trainBest map · 73% over 11nukeWeakest map · 33% over 9
MapGradePlayedRecordWin rateAvg rating
mirageB25131252%-0.01
infernoA1610663%0.01
trainS118373%0.03
nukeD93633%0.01
ancientS96367%0.03
dust2C94544%-0.03
anubisD62433%-0.01
overpassC52340%-0.03
vertigo42250%0.07
edin32167%0.02
office2020%-0.06
cache1010%-0.06

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

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
30.9%Accuracy (enemy spotted)
31.7%Spray accuracy
77.9%Counter-strafing
9.6°Preaim
579msReaction time
28.6%T opening success
44.2%CT opening success
0.74Enemies flashed / flash
3.0%Flash assists
11.87HE damage / grenade
7.17Flashes / 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 28.5848% — below the 40% mark we flag

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.

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategyNuke grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke4–13-0.0630%14 Aug
cache3–13-0.0615%13 Aug
mirage5–13-0.0122%13 Aug
mirage13–110.0314%9 Aug
ancient13–80.0725%9 Aug
mirage16–130.0123%9 Aug
mirage11–13-0.0344%6 Aug
inferno13–1-0.0920%6 Aug
dust212–16-0.0615%5 Aug
anubis9–130.0526%5 Aug
mirage9–13-0.0723%5 Aug
inferno8–13-0.0711%13 May
mirage8–130.0222%1 May
inferno16–130.0117%1 May
overpass5–13-0.079%18 Apr
ancient6–2-0.0312%18 Apr
anubis3–13-0.0720%18 Apr
ancient13–70.0111%18 Apr
mirage13–110.0120%18 Apr
overpass3–13-0.1125%3 Jan
inferno13–10-0.0317%3 Jan
mirage13–7-0.0223%1 Jan
overpass16–12-0.0521%1 Jan
dust211–13-0.0021%23 Oct
overpass10–130.0121%22 Oct
dust212–12-0.0317%19 Sept
dust213–5-0.0715%21 Aug
nuke13–60.0927%21 Aug
mirage9–13-0.0318%21 Aug
train7–13-0.0618%21 Aug
inferno13–100.0436%17 Aug
mirage13–7-0.078%17 Aug
ancient4–10.0556%17 Aug
train13–11-0.0421%9 Jul
train11–13-0.0624%9 Jul
office5–13-0.0632%8 Jul
mirage12–120.0319%7 Jul
nuke11–13-0.0319%6 Jul
train13–110.1524%6 Jul
train13–60.0117%6 Jul
mirage13–50.0316%2 Jun
inferno10–130.0119%2 Jun
mirage13–110.0324%2 Jun
inferno13–30.0232%2 Jun
anubis8–130.0324%16 May
nuke9–13-0.0625%16 May
nuke10–13-0.0130%16 May
inferno13–50.1418%16 May
mirage9–13-0.0520%23 Apr
inferno8–130.0319%16 Apr
vertigo9–130.1420%16 Apr
mirage13–110.0219%12 Apr
overpass13–50.0510%19 Mar
anubis13–9-0.0317%19 Mar
mirage16–140.0114%16 Mar
ancient3–13-0.0615%16 Mar
mirage11–13-0.0418%14 Mar
mirage5–13-0.1112%5 Mar
dust213–8-0.0533%22 Feb
inferno5–13-0.0126%18 Feb
inferno5–9-0.0833%18 Feb
mirage10–13-0.0017%16 Feb
train13–50.1723%16 Feb
train13–50.0121%16 Feb
office11–13-0.0725%15 Feb
mirage13–60.0417%31 Jan
nuke13–60.0430%31 Jan
ancient12–120.0017%21 Jan
mirage8–13-0.0540%20 Jan
train13–80.0029%9 Jan
vertigo13–00.0642%9 Jan
mirage13–11-0.0341%5 Jan
dust210–13-0.0613%5 Jan
dust213–100.0428%4 Jan
nuke13–90.1228%4 Jan
anubis13–11-0.0427%4 Jan
nuke8–130.0433%3 Jan
inferno13–80.0939%30 Dec
inferno13–60.0734%30 Dec
dust28–13-0.0127%24 Dec
mirage13–30.0816%24 Dec
inferno10–13-0.0318%17 Dec
edin3–13-0.0319%17 Dec
nuke10–13-0.0523%12 Dec
dust213–3-0.0423%12 Dec
vertigo4–130.0526%10 Dec
vertigo13–70.0531%10 Dec
inferno13–100.0227%10 Dec
ancient13–40.1026%5 Dec
mirage13–110.0120%5 Dec
ancient6–130.0313%26 Nov
anubis10–130.0227%26 Nov
inferno13–110.0720%26 Nov
train12–12-0.0623%24 Nov
ancient13–40.1318%24 Nov
train13–70.0516%23 Nov
edin13–80.0121%23 Nov
train13–60.1128%23 Nov
mirage9–130.0223%23 Nov
edin13–110.0923%23 Nov

Match data via Leetify.

Recent teammates

Milestones

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