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  Clan Information

Statistics Summary
Clan: TAMBOFF-WOLF
Home Page: tamboff-wolf.ru
Activity: 77.51%
Members: 29 active members (74 total)
Avg. Member Points: 11,446
Total Kills: 359,450
Total Deaths: 292,807
Avg. Kills: 12,395
Kills per Death: 1.23
Kills per Minute: 0.65
Total Connection Time: 386d 19:24:09h
Avg. Connection Time: 13d 08:07:02h
Favorite Server:* ~TAMBOFF-WOLF [NIGHT VIP] PUBLIC NOSTEAM~
Favorite Map:* de_dust2
Favorite Weapon:* Kalashnikov AK-47
Player Locations

  Members

Rank Name Rank Points Activity Time Kills Clan Kills % Deaths sort-descending.gif Kpd
1  Russian federationKAZANTIP elorank 12,701 49d 21:12:27h 42,010 11.69% 38,583 1.09
2  Russian federation⋙-☭3,14✖@ЉI4-►㋛™ elorank 33,965 46d 18:15:30h 68,825 19.15% 31,321 2.20
3  Russian federationdoc76 elorank 18,822 38d 01:42:25h 24,921 6.93% 24,192 1.03
4  Russian federationLoony elorank 9,420 30d 07:20:54h 19,937 5.55% 22,106 0.90
5  KazakhstanRastaman 10KZ elorank 9,158 22d 06:38:27h 16,151 4.49% 18,072 0.89
6  Russian federation♛℟usłan¢ħiҟ♛ elorank 17,806 24d 07:33:46h 32,536 9.05% 16,883 1.93
7  Russian federationубивашка 62 elorank 10,447 22d 05:26:20h 23,507 6.54% 15,929 1.48
8  Russian federationAnapskiy elorank 11,935 19d 05:13:30h 17,550 4.88% 15,207 1.15
9  Ukrainerimuru elorank 10,538 14d 04:56:12h 13,863 3.86% 13,411 1.03
10  Russian federationDiM4iK elorank 14,639 16d 11:27:36h 19,248 5.35% 12,180 1.58
11  Kazakhstan₭Ø฿Ɽ₳ 10₭Ⱬ elorank 5,483 13d 19:17:20h 4,999 1.39% 11,872 0.42
12  Russian federationStanislav752 elorank 10,543 14d 18:35:29h 12,215 3.40% 11,623 1.05
13  Russian federationSTRELOK elorank 14,649 15d 08:36:59h 11,558 3.22% 10,412 1.11
14  Russian federationKenzO elorank 5,731 8d 18:32:44h 5,913 1.65% 7,910 0.75
15  Russian federationBISON elorank 9,135 7d 10:55:13h 4,917 1.37% 7,442 0.66
16  Russian federation⇜Ṧ†êrvå⇝ elorank 9,404 6d 09:26:00h 4,662 1.30% 6,056 0.77
17  Israel«★»GℛΣﮒℍ₦iK«★» elorank 19,346 7d 17:10:25h 10,776 3.00% 5,572 1.93
18  Russian federationavpvovan elorank 9,883 5d 20:26:21h 4,450 1.24% 5,021 0.89
19  Russian federationSlovoPetuxa!-KashtanomPoOsvaltu elorank 10,227 3d 09:51:28h 3,247 0.90% 3,410 0.95
20  Russian federationOrel57RUSVOVAN elorank 13,050 5d 02:04:46h 4,277 1.19% 3,263 1.31


Page: 1 2




  Player Actions *

Rank Action Achieved sort-descending.gif Points Bonus
1 Headshot 28,527 times 28,527
2 Pick up the Bomb 25,222 times 50,444
3 Round MVP 17,607 times 0
4 Drop the Bomb 13,715 times -27430
5 Double Kill (2 kills) 10,882 times 10,882
6 Plant the Bomb 5,639 times 56,390
7 Domination 3,448 times 17,240
8 Triple Kill (3 kills) 2,717 times 5,434
9 Revenge 1,723 times 5,169
10 Start Defusing the Bomb With a Defuse Kit 676 times 0
11 Domination (4 kills) 491 times 1,473
12 Defuse the Bomb 462 times 4,620
13 Start Defusing the Bomb Without a Defuse Kit 59 times 0
14 Rampage (5 kills) 52 times 208
15 Kill a Hostage 18 times -270
16 Touch a Hostage 4 times 0
17 Mega Kill (6 kills) 2 times 10
18 Rescue a Hostage 1 times 5




  Victims of Player-Player Actions *

Rank Action Times Victimized sort-descending.gif Points Bonus
1 Domination 2,787 times -13935
2 Revenge 2,042 times -6126




  Team Selection *

Rank Team Joined sort-descending.gif Percentage of Times %
1 Terrorist 3,329 times 28.72%
2 Counter-Terrorist 2,350 times 20.27%




  Weapon Usage *

Rank Weapon Points Modifier Kills sort-ascending.gif Percentage of Kills % Headshots Percentage of Headshots % Hpk
1 H&K G3/SG1 Sniper Rifle 0.80 1 0.00% 0 0.00% 0.00
2 Fusil Automatique 1.00 29 0.01% 12 0.01% 0.41
3 H&K UMP45 1.20 35 0.01% 16 0.01% 0.46
4 Steyr Tactical Machine Pistol 1.50 53 0.01% 30 0.02% 0.57
5 FN Five-Seven 1.50 57 0.02% 28 0.02% 0.49
6 Steyr Aug 1.00 73 0.02% 34 0.03% 0.47
7 Benelli/H&K M4 Super 90 XM1014 1.10 78 0.02% 28 0.02% 0.36
8 H&K MP5-Navy 1.20 100 0.03% 42 0.03% 0.42
9 Glock 18 Select Fire 1.40 113 0.03% 53 0.04% 0.47
10 Ingram MAC-10 1.50 122 0.03% 61 0.05% 0.50
11 Galil 1.10 124 0.03% 52 0.04% 0.42
12 H&K USP .45 Tactical 1.40 149 0.04% 74 0.06% 0.50
13 Dual Beretta 96G Elite 1.40 189 0.05% 90 0.07% 0.48
14 Benelli M3 Super 90 Combat 1.20 800 0.22% 319 0.24% 0.40
15 Sig Sauer SG-552 Commando 1.00 1,040 0.29% 465 0.35% 0.45
16 Sig Sauer P-228 1.50 1,256 0.35% 515 0.39% 0.41
17 FN P90 1.20 1,471 0.41% 652 0.49% 0.44
18 Bundeswehr Advanced Combat Knife 2.00 1,491 0.41% 2 0.00% 0.00
19 M249 PARA Light Machine Gun 1.20 2,033 0.57% 1,016 0.76% 0.50
20 High Explosive Grenade 1.80 2,394 0.67% 0 0.00% 0.00
21 Arctic Warfare Magnum (Police) 1.00 2,775 0.77% 436 0.33% 0.16
22 Desert Eagle .50AE 1.20 5,926 1.65% 3,105 2.33% 0.52
23 Steyr Scout 1.10 6,263 1.74% 3,693 2.78% 0.59
24 Colt M4A1 Carbine 1.00 11,274 3.14% 4,960 3.73% 0.44
25 Kalashnikov AK-47 1.00 21,933 6.10% 10,932 8.22% 0.50




  Weapon Stats *

Rank Weapon Shots Hits sort-ascending.gif Damage Headshots Kills Kills per Death Accuracy Damage per Hit Shots per Kill
1 Sig SG-550 Sniper 6 3 301 1 2 2.0000 50.0% 100.3 3.0
2 H&K G3/SG1 Sniper Rifle 30 10 1,742 6 7 7.0000 33.3% 174.2 4.3
3 Fusil Automatique 780 147 4,388 11 27 27.0000 18.8% 29.9 28.9
4 H&K UMP45 2,041 270 5,449 16 34 17.0000 13.2% 20.2 60.0
5 FN Five-Seven 1,341 371 9,929 37 69 34.5000 27.7% 26.8 19.4
6 Steyr Aug 2,777 378 11,399 34 73 14.6000 13.6% 30.2 38.0
7 Steyr Tactical Machine Pistol 3,391 452 8,135 30 53 53.0000 13.3% 18.0 64.0
8 Galil 3,693 530 17,452 52 124 62.0000 14.4% 32.9 29.8
9 H&K MP5-Navy 4,812 855 14,170 41 98 10.8889 17.8% 16.6 49.1
10 Ingram MAC-10 5,173 864 15,804 60 119 29.7500 16.7% 18.3 43.5
11 Dual Beretta 96G Elite 4,814 929 26,008 90 189 63.0000 19.3% 28.0 25.5
12 H&K USP .45 Tactical 5,365 980 20,566 73 148 7.7895 18.3% 21.0 36.3
13 Benelli/H&K M4 Super 90 XM1014 1,436 986 11,456 28 78 15.6000 68.7% 11.6 18.4
14 Glock 18 Select Fire 5,450 993 17,053 52 111 7.4000 18.2% 17.2 49.1
15 Bundeswehr Advanced Combat Knife 21,628 1,292 66,942 2 447 1.6137 6.0% 51.8 48.4
16 Arctic Warfare Magnum (Police) 11,608 3,974 529,836 443 2,783 5.4569 34.2% 133.3 4.2
17 Sig Sauer P-228 31,527 5,167 159,907 515 1,256 22.4286 16.4% 30.9 25.1
18 Sig Sauer SG-552 Commando 76,212 5,272 154,025 478 1,056 42.2400 6.9% 29.2 72.2
19 Benelli M3 Super 90 Combat 3,541 7,167 102,494 319 800 2.3599 202.4% 14.3 4.4
20 M249 PARA Light Machine Gun 106,753 8,019 308,131 1,130 2,182 13.8101 7.5% 38.4 48.9
21 FN P90 74,742 8,435 196,899 652 1,471 9.7417 11.3% 23.3 50.8
22 Steyr Scout 51,328 15,340 1,465,246 3,753 6,372 2.6451 29.9% 95.5 8.1
23 Desert Eagle .50AE 65,071 17,234 902,310 3,431 6,309 4.4150 26.5% 52.4 10.3
24 Colt M4A1 Carbine 414,378 50,407 1,583,219 4,968 11,285 10.7068 12.2% 31.4 36.7
25 Kalashnikov AK-47 647,303 81,045 3,253,246 12,252 23,601 9.9206 12.5% 40.1 27.4




  Weapon Targets *

Rank Weapon Hits sort-ascending.gif Left Middle Right
1 Sig SG-550 Sniper 3 0.0% 100.0% 0.0%
2 H&K G3/SG1 Sniper Rifle 10 20.0% 80.0% 0.0%
3 Bundeswehr Advanced Combat Knife 62 24.2% 71.0% 4.8%
4 Fusil Automatique 147 21.1% 61.9% 17.0%
5 H&K UMP45 270 24.8% 55.2% 20.0%
6 FN Five-Seven 371 20.5% 65.8% 13.7%
7 Steyr Aug 378 28.3% 55.8% 15.9%
8 Steyr Tactical Machine Pistol 452 26.8% 62.8% 10.4%
9 Galil 530 28.1% 55.5% 16.4%
10 H&K MP5-Navy 855 29.4% 56.3% 14.4%
11 Ingram MAC-10 864 26.7% 58.9% 14.4%
12 Dual Beretta 96G Elite 929 24.5% 61.5% 14.0%
13 H&K USP .45 Tactical 980 23.9% 62.8% 13.4%
14 Benelli/H&K M4 Super 90 XM1014 986 27.2% 56.3% 16.5%
15 Glock 18 Select Fire 993 26.2% 61.3% 12.5%
16 Arctic Warfare Magnum (Police) 3,974 32.6% 57.5% 9.9%
17 Sig Sauer P-228 5,167 29.1% 57.0% 13.9%
18 Sig Sauer SG-552 Commando 5,272 28.7% 56.1% 15.2%
19 Benelli M3 Super 90 Combat 7,167 29.1% 57.9% 13.1%
20 M249 PARA Light Machine Gun 8,019 28.0% 57.9% 14.0%
21 FN P90 8,435 28.1% 56.2% 15.7%
22 Steyr Scout 15,315 26.4% 64.9% 8.7%
23 Desert Eagle .50AE 17,234 25.9% 61.5% 12.6%
24 Colt M4A1 Carbine 50,407 28.0% 58.7% 13.3%
25 Kalashnikov AK-47 81,045 26.8% 59.7% 13.5%


Targets
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ERROR
Database Error

Server Address: localhost
Server Username: hlstatsxce

Error Diagnostic:
Bad query.

Server Error: (1052) Column 'map' in order clause is ambiguous

Last SQL Query:
		SELECT *, 
			IFNULL(kills/deaths, '-') AS kpd,
			IFNULL(headshots / kills, '-') AS hpk,
			ROUND(kills / 359450 * 100, 2) AS kpercent,
			ROUND(headshots / 132979 * 100, 2) AS hpercent
		FROM
			tmp_clan_kills, tmp_clan_deaths
		WHERE
			tmp_clan_kills.map = tmp_clan_deaths.map
		ORDER BY
			map asc,
			kills asc