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tomtom

tomtom — CS2 Stats

US76561197964091169[U:1:3825441]Steam profile ↗

710Tracked matches37%Win rate2020Tracked since
CSDB Rating3.9 Learning
FaceitLevel 7 · 1,649 ELOTop 42.3% of ranked FACEIT players
WingmanLegendary Eagle
Ladder ranks via Leetify

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CSDB.GGtomtomFACEITLevel 7 · 1,649 ELOSTANDINGTop 42.3% of rankedcsdb.gg/stats

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Performance scores

Aim56
Positioning41
Utility57

0–100 skill scores via Leetify.

Recent form

COLD44–54–2Last 10044%Win rateWLLWLLLLWL

Last 10 vs previous 10: +0pp win rate · -0.03 avg rating

Player DNA

Aim5.6
Aggression2.4
Utility5.7
Positioning4.1
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

NiKo

Plays most like NiKo 79% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower opening-fight frequency; 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 38% on CT to 21% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 561ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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
Positioning4.1
Utility5.7
Mechanics3.9
Opening Duels1.0
Win Impact0.6

Composite 3.9/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.01
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time567ms−0ms
first ⅓ avg 567ms → last ⅓ avg 567ms
Headshot accuracy14.3%−0.4%
first ⅓ avg 14.6% → last ⅓ avg 14.3%

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

0.12Best rating — mirage 13–7
13–3Biggest win — ancient
6Longest win streak
9–10In matches decided by ≤2 rounds
11Overtime games

Map breakdown

ancientBest map · 75% over 8dust2Weakest map · 29% over 21
MapGradePlayedRecordWin rateAvg rating
mirageD268–1831%-0.00
dust2D216–1529%-0.01
anubisS1510–567%-0.00
infernoB137–654%0.00
ancientS86–275%-0.02
nukeC83–538%-0.00
cacheC52–340%-0.01
overpass—20–20%-0.06
train—22–0100%0.00

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (29% over 21). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

878Matches
50%Win rate
1.00Avg K/D
71.4ADR
39%Headshot %

Clutches & streaks

40%1v1 clutch win
19%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Dust28442%0.8013.6
Mirage7743%0.9013.7
Inferno4846%0.8813.4
Anubis3850%0.9015.0
Nuke2241%0.8914.4
Ancient1547%0.7513.0
Cache743%0.6510.9
Vertigo3100%1.0917.7

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.

14.2%Headshot accuracy
36.9%Accuracy (enemy spotted)
40.6%Spray accuracy
67.5%Counter-strafing
12.2°Preaim
561msReaction time
20.9%T opening success
38.0%CT opening success
0.58Enemies flashed / flash
4.7%Flash assists
9.46HE damage / grenade
13.79Flashes / 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 12.1921° — 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 14.1555% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Dust 2

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

29% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–7-0.0112%28 Aug →
anubis16–19-0.0522%25 Aug →
mirage5–13-0.0327%21 Aug →
cache13–110.0519%19 Aug →
mirage7–13-0.0514%17 Aug →
mirage9–13-0.1010%14 Aug →
dust27–13-0.0512%12 Aug →
mirage4–130.027%12 Aug →
dust213–100.0512%7 Aug →
inferno1–13-0.0614%7 Aug →
cache9–13-0.0112%7 Aug →
inferno13–110.0510%5 Aug →
dust211–13-0.0616%15 Jul →
cache13–100.0011%8 Jul →
dust210–13-0.0410%8 Jul →
dust213–80.019%6 Jul →
dust24–130.0414%9 Jun →
dust28–130.0620%3 Jun →
inferno4–130.0220%3 Jun →
mirage20–22-0.0413%22 May →
inferno16–120.0312%6 May →
cache10–13-0.0512%1 May →
cache5–13-0.0610%29 Apr →
dust210–13-0.0716%17 Apr →
anubis14–160.0312%24 Mar →
inferno13–60.0925%18 Mar →
dust213–90.0115%13 Mar →
mirage13–10-0.0419%18 Feb →
nuke6–130.0012%11 Feb →
nuke13–90.0410%4 Feb →
dust215–150.0713%4 Feb →
dust25–13-0.0412%3 Feb →
nuke11–13-0.0322%2 Feb →
dust213–8-0.0114%30 Jan →
inferno5–13-0.0111%20 Jan →
dust213–90.0026%12 Dec →
mirage4–130.0118%12 Dec →
dust28–13-0.0411%4 Dec →
overpass11–13-0.0910%1 Dec →
nuke16–19-0.0323%26 Nov →
nuke16–19-0.0323%26 Nov →
dust27–13-0.0313%19 Nov →
dust26–13-0.0226%11 Nov →
inferno13–5-0.0216%9 Nov →
mirage5–130.0013%7 Nov →
mirage11–13-0.0315%5 Nov →
mirage11–130.0417%31 Oct →
overpass6–13-0.0321%14 Oct →
inferno8–13-0.057%26 Sept →
dust212–120.0519%22 Aug →
mirage13–8-0.0212%29 Mar →
mirage10–13-0.0112%12 Mar →
ancient13–90.0518%11 Feb →
mirage6–13-0.0117%4 Feb →
ancient9–13-0.0614%3 Feb →
anubis13–100.0218%30 Jan →
mirage3–13-0.0725%30 Jan →
anubis13–6-0.0115%27 Jan →
ancient16–14-0.0320%25 Jan →
mirage4–13-0.0420%25 Jan →
mirage13–50.0622%23 Jan →
train13–7-0.0419%22 Jan →
mirage13–70.1228%22 Jan →
inferno13–90.0113%21 Jan →
mirage14–16-0.0615%19 Jan →
inferno10–13-0.0121%16 Jan →
anubis9–13-0.0218%16 Jan →
mirage9–13-0.0515%14 Jan →
mirage3–90.0211%11 Jan →
anubis13–11-0.0111%9 Jan →
anubis16–140.0116%8 Jan →
train13–50.0514%8 Jan →
nuke13–110.0228%7 Jan →
ancient13–110.005%6 Jan →
anubis13–40.0214%6 Jan →
anubis11–13-0.0116%6 Jan →
anubis13–90.0522%5 Jan →
inferno13–70.0412%5 Jan →
ancient13–3-0.0119%5 Jan →
mirage7–130.0417%5 Jan →
anubis13–16-0.0613%3 Jan →
anubis13–8-0.0316%2 Jan →
dust23–13-0.0311%2 Jan →
mirage13–6-0.0415%2 Jan →
dust213–100.0227%1 Jan →
anubis13–100.0011%31 Dec →
ancient7–13-0.0218%31 Dec →
mirage10–130.0312%31 Dec →
dust210–13-0.0410%31 Dec →
mirage13–100.0816%30 Dec →
ancient13–10-0.0513%30 Dec →
anubis13–110.0116%30 Dec →
mirage13–9-0.0210%29 Dec →
nuke8–130.0114%27 Dec →
dust27–13-0.0817%27 Dec →
anubis13–10-0.0111%24 Dec →
mirage13–110.0714%24 Dec →
inferno9–60.0013%24 Dec →
inferno6–8-0.0514%23 Dec →
nuke13–90.0111%23 Dec →

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 →

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