Connexion

Thunder
GP: 82 | W: 12 | L: 61 | OTL: 9 | P: 33
GF: 234 | GA: 413 | PP%: 19.20% | PK%: 77.78%
DG: Jean-Francois Lemelin | Morale : 50 | Moyenne d’équipe : 51
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Centre de jeu
Thunder
12-61-9, 33pts
1
FINAL
7 Monsters
46-29-7, 99pts
Team Stats
L7StreakSOL1
4-34-3Home Record23-14-4
8-27-6Away Record23-15-3
0-8-2Last 10 Games5-4-1
2.85Goals Per Game3.90
5.04Goals Against Per Game3.60
19.20%Power Play Percentage22.82%
77.78%Penalty Kill Percentage79.21%
Thunder
12-61-9, 33pts
4
FINAL
7 Cougars
56-20-6, 118pts
Team Stats
L7StreakW1
4-34-3Home Record30-9-2
8-27-6Away Record26-11-4
0-8-2Last 10 Games8-1-1
2.85Goals Per Game4.00
5.04Goals Against Per Game3.10
19.20%Power Play Percentage20.94%
77.78%Penalty Kill Percentage82.63%
Meneurs d'équipe
Buts
Gabriel Fortier
9
Passes
Rasmus Sandin
31
Points
Rasmus Sandin
40
Plus/Moins
Gabriel Fortier
8
Victoires
Louis Domingue
9
Pourcentage d’arrêts
Louis Domingue
0.913

Statistiques d’équipe
Buts pour
234
2.85 GFG
Tirs pour
3230
39.39 Avg
Pourcentage en avantage numérique
19.2%
48 GF
Début de zone offensive
36.6%
Buts contre
413
5.04 GAA
Tirs contre
4535
55.30 Avg
Pourcentage en désavantage numérique
77.8%
36 GA
Début de la zone défensive
45.2%
Information d’équipe

Directeur généralJean-Francois Lemelin
DivisionEst
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,883
Billets de saison300


Information formation

Équipe Pro25
Équipe Mineure21
Limite contact 46 / 50
Espoirs20


Historique d'équipe

Saison actuelle12-61-9 (33PTS)
Historique12-61-7 (0.150%)
Apparitions séries éliminatoires
Historique séries éliminatoires (W-L)-


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire moyen
1Adam Beckman (R)X100.00786999686958585950506365604444050580193925,000$
2Garrett WilsonXX100.00778071608061635450564566435758050560291575,000$
3Jack Drury (R)XXX100.00474086706266815658544846505050050540204925,000$
4Thomas Di PauliXX100.00686781646753535470485561534444050540261715,000$
5Ethan Keppen (R)X100.00807690637650514850474463424444050530194560,000$
6Devante Smith-PellyXX100.008279906379505246504344644244440505202811,200,000$
7Tanner FritzX100.00746985566945445366475461514444050520293825,000$
8Nikita NesterovX100.00764384706968725725494770254747050610272700,000$
9Brendan GuhleX100.00727370757361635525504264405858050600231800,000$
10Cal Foote (R)X100.00764577728460785725454860254747050600211925,000$
11Sean DurziX100.00787585646868655828554666404444050590214809,167$
12Brett LernoutX100.00828085648051525025433967375555050580252750,000$
13Dylan Samberg (R)X100.00838186608155584725394064384444050560213925,000$
14Jett Woo (R)X100.00767481587465704625334361414444050550204860,833$
15Ryan O'Rourke (R)X100.00716975606963684725384058384444050540183886,667$
Rayé
1Samuel HenleyXX100.00443591647434273235303465443532050430271690,000$
2Artur Kayumov (R)XX100.00394545455336363945393945423230050400221825,000$
3Dante Salituro (R)X100.00394545455136363945393945423230050400231725,000$
4Adam GilmourXX100.00314040406629293140313140353230050350261715,000$
5Tony CameranesiX100.00303737374527273037303037323230050330271600,000$
6Michael PrapavessisX100.00747096647046484125303861374444050520241650,000$
7Filip Johansson (R)X100.00494391646761863925294145435050050510204895,000$
MOYENNE D’ÉQUIPE100.0065617760695255473942435841444405052
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
Rayé
1Samuel Ersson (R)100.0050827468425242484246465454050520
2Jake Kielly (R)100.0047516478444650534647304444050510
3Samu Perhonen100.0036434068353333333333323230050380
MOYENNE D’ÉQUIPE100.004459597140444245404236434305047
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Brendan GuhleThunder (Tam)D82174966-407210277134194741428.76%164139717.04891769110000055210.00%000010.9400200221
2Adam BeckmanThunder (Tam)LW82422062-2959151712244651353909.03%62126715.461121936000091144.44%10800020.9815201146
3Thomas Di PauliThunder (Tam)C/LW82292453-1960551802788018610.43%4384010.2630347000001052.12%125100011.2604000120
4Ethan KeppenThunder (Tam)LW82192948-19355124119226781598.41%518189.9800001000001246.30%5400001.1701010204
5Rasmus SandinTampa BayD4593140-2543514310612244827.38%11898921.99661271131011274010.00%000000.8100001121
6Gabriel FortierTampa BayC/LW359202986031106140301096.43%1354115.46112625000010055.16%81400001.0713000112
7Cal FooteThunder (Tam)D416162254401123851104211.76%4994423.0324612880001103100.00%000000.4700000001
8Devante Smith-PellyThunder (Tam)LW/RW6911920-31005779102289010.78%1373810.7100002000001025.93%5400000.5400000022
9Tanner FritzThunder (Tam)C156410-34019102961920.69%425917.29112420000001051.61%6200000.7700000021
10Joel ArmiaTampa BayRW8448-220171838122210.53%414818.50112926000001014.29%700001.0811000002
11Nikita NesterovThunder (Tam)D11178-6801714399172.56%2023621.460442234000026100.00%000000.6800000010
12Markus GranlundTampa BayC/LW/RW11077100336409220.00%622220.220224230000180038.64%26400000.6300000000
13Curtis McKenzieTampa BayLW825718038176111333.28%117521.931231127000010087.50%800000.8001000100
14Sean DurziThunder (Tam)D111673602622185115.56%1120418.62112727000024000.00%000000.6800000001
15Brett LernoutThunder (Tam)D11235-2001610104520.00%1914112.860002200000000.00%000000.7100000000
16Michael PrapavessisThunder (Tam)D15044-52015492130.00%61177.850110100004000.00%000000.6800000000
17Dylan SambergThunder (Tam)D11134-211527762716.67%1714913.5800000000012000.00%000000.5400100000
18Jack DruryThunder (Tam)C/LW/RW1411200011013647.69%2876.2500000000010045.19%10400000.4600000000
19Jett WooThunder (Tam)D14202320283131315.38%2024217.3200012000034100.00%000000.1600000010
20Samuel HenleyThunder (Tam)C/LW15011-20025143140.00%419412.9900000000000033.33%1500000.1000000000
21Ryan O'RourkeThunder (Tam)D5000-100713120.00%55811.640000100006000.00%000000.0000000000
Statistiques d’équipe totales ou en moyenne667162243405-1373184011861143187155013728.66%632977514.66253358241571011337511550.42%274100040.8331551291721
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du gardien Nom de l’équipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Louis DomingueTampa Bay5994260.9134.7032692025629290520.455115866643
Statistiques d’équipe totales ou en moyenne5994260.9134.7032692025629290520.455115866643


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Adam BeckmanThunder (Tam)LW192001-05-10Yes187 Lbs6 ft1NoNoNo3Pro & Farm925,000$92,500$0$No925,000$925,000$Lien
Adam GilmourThunder (Tam)C/RW261994-01-29No193 Lbs6 ft2NoNoNo1Pro & Farm715,000$71,500$0$NoLien
Artur KayumovThunder (Tam)LW/RW221998-02-14Yes176 Lbs5 ft11NoNoNo1Pro & Farm825,000$82,500$0$NoLien
Brendan GuhleThunder (Tam)D231997-07-29No197 Lbs6 ft2NoNoNo1Pro & Farm800,000$80,000$0$NoLien
Brett LernoutThunder (Tam)D251995-09-23No214 Lbs6 ft4NoNoNo2Pro & Farm750,000$75,000$0$No750,000$Lien
Cal FooteThunder (Tam)D211998-12-12Yes227 Lbs6 ft4NoNoNo1Pro & Farm925,000$92,500$0$NoLien
Dante SalituroThunder (Tam)C231996-11-15Yes175 Lbs5 ft9NoNoNo1Pro & Farm725,000$72,500$0$NoLien
Devante Smith-PellyThunder (Tam)LW/RW281992-06-14No223 Lbs6 ft0NoNoNo1Pro & Farm1,200,000$120,000$0$NoLien
Dylan SambergThunder (Tam)D211999-01-24Yes216 Lbs6 ft4NoNoNo3Pro & Farm925,000$92,500$0$No925,000$925,000$Lien
Ethan KeppenThunder (Tam)LW192001-03-20Yes209 Lbs6 ft2NoNoNo4Pro & Farm560,000$56,000$0$No560,000$560,000$560,000$Lien
Filip JohanssonThunder (Tam)D202000-03-23Yes181 Lbs6 ft1NoNoNo4Pro & Farm895,000$89,500$0$No895,000$895,000$895,000$Lien
Garrett WilsonThunder (Tam)LW/RW291991-03-16No218 Lbs6 ft3NoNoNo1Pro & Farm575,000$57,500$0$NoLien
Jack DruryThunder (Tam)C/LW/RW202000-02-03Yes174 Lbs5 ft11NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Lien
Jake KiellyThunder (Tam)G241996-09-10Yes201 Lbs6 ft2NoNoNo4Pro & Farm700,000$70,000$0$No700,000$700,000$700,000$Lien
Jett WooThunder (Tam)D202000-07-27Yes205 Lbs6 ft0NoNoNo4Pro & Farm860,833$86,083$0$No860,833$860,833$860,833$Lien
Michael PrapavessisThunder (Tam)D241996-01-07No185 Lbs6 ft2NoNoNo1Pro & Farm650,000$65,000$0$NoLien
Nikita NesterovThunder (Tam)D271993-03-28No191 Lbs5 ft11NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Ryan O'RourkeThunder (Tam)D182002-05-16Yes181 Lbs6 ft2NoNoNo3Pro & Farm886,667$88,667$0$No886,667$886,667$Lien
Samu PerhonenThunder (Tam)G271993-03-07No184 Lbs6 ft5NoNoNo3Pro & Farm700,000$70,000$0$No700,000$700,000$Lien
Samuel ErssonThunder (Tam)G201999-10-20Yes176 Lbs6 ft2NoNoNo4Pro & Farm859,167$85,917$0$No859,167$859,167$859,167$Lien
Samuel HenleyThunder (Tam)C/LW271993-07-25No210 Lbs6 ft4NoNoNo1Pro & Farm690,000$69,000$0$NoLien
Sean DurziThunder (Tam)D211998-10-21No185 Lbs6 ft0NoNoNo4Pro & Farm809,167$80,917$0$No809,167$809,167$809,167$Lien
Tanner FritzThunder (Tam)C291991-08-20No192 Lbs5 ft11NoNoNo3Pro & Farm750,000$82,500$0$No560,000$560,000$Lien
Thomas Di PauliThunder (Tam)C/LW261994-04-29No187 Lbs5 ft11NoNoNo1Pro & Farm715,000$71,500$0$NoLien
Tony CameranesiThunder (Tam)C271993-08-12No162 Lbs5 ft9NoNoNo1Pro & Farm600,000$60,000$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2523.44194 Lbs6 ft12.32786,633$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
140122
2Adam Beckman30122
3Ethan KeppenThomas Di Pauli20122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
140122
2Brendan Guhle30122
320122
410122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
160122
2Adam Beckman40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Brendan Guhle40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
160122
2Adam Beckman40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Brendan Guhle40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
16012260122
240122Brendan Guhle40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
160122
2Adam Beckman40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Brendan Guhle40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Thomas Di Pauli, Ethan Keppen, Thomas Di Pauli, Ethan Keppen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, , ,
Tirs de pénalité
, , , Adam Beckman,
Gardien
#1 : , #2 :


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
TotalDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Admirals20200000711-41010000046-21010000035-200.000713201090915237610631085106240127302479222.22%110.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
2Baby Hawks20100100412-81010000018-71000010034-110.25046100090915236510631085106240131444426116.67%20100.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
3Bears30300000918-91010000035-220200000613-700.000917260090915231121063108510624015735155411218.18%5180.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
4Bruins40300001817-920200000610-42010000127-510.12581220009091523127106310851062402096350861100.00%11281.82%01085284138.19%1269350336.23%532141237.68%158310812385611994444
5Cabaret Lady Mary Ann422000002020021100000910-1211000001110140.50020365600909152319710631085106240216683210222836.36%16568.75%01085284138.19%1269350336.23%532141237.68%158310812385611994444
6Caroline3110000113130110000007432010000169-330.5001323360090915231401063108510624013845145413646.15%7357.14%01085284138.19%1269350336.23%532141237.68%158310812385611994444
7Chiefs21000001752110000005231000000123-130.7507132000909152390106310851062401102983710110.00%30100.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
8Chill20100001811-31000000145-11010000046-210.250814220090915237210631085106240802911619111.11%3166.67%01085284138.19%1269350336.23%532141237.68%158310812385611994444
9Comets20200000812-41010000045-11010000047-300.000815230090915239310631085106240952982510220.00%30100.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
10Cougars413000001424-1020200000412-8211000001012-220.2501421350090915231531063108510624023769276310220.00%60100.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
11Crunch412001001113-22010010046-22110000077030.3751120310090915232081063108510624019754181349222.22%8187.50%01085284138.19%1269350336.23%532141237.68%158310812385611994444
12Heat2010100058-3100010004311010000015-420.5005813009091523781063108510624010035440400.00%20100.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
13Jayhawks20200000410-61010000025-31010000025-300.00048120090915239110631085106240119324388225.00%20100.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
14Las Vegas21100000910-11010000026-41100000074320.5009162500909152310610631085106240143330397228.57%000.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
15Manchots30300000713-620200000712-51010000001-100.000713200090915239210631085106240157511562400.00%5180.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
16Marlies40400000821-1320200000210-820200000611-500.0008142200909152315010631085106240224633211512216.67%15286.67%01085284138.19%1269350336.23%532141237.68%158310812385611994444
17Minnesota2010000158-31010000002-21000000156-110.25058130090915236810631085106240117326423266.67%30100.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
18Monarchs2110000069-31010000026-41100000043120.50061218009091523811063108510624010127451600.00%2150.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
19Monsters30300000621-151010000027-520200000414-1000.00061218009091523106106310851062401986512598112.50%6183.33%01085284138.19%1269350336.23%532141237.68%158310812385611994444
20Monsters2020000058-31010000024-21010000034-100.000581300909152354106310851062401093014508112.50%6183.33%01085284138.19%1269350336.23%532141237.68%158310812385611994444
21Oceanics20200000612-61010000045-11010000027-500.0006111700909152389106310851062401292815316116.67%50100.00%11085284138.19%1269350336.23%532141237.68%158310812385611994444
22Oil Kings20100001810-21010000034-11000000156-110.250816240090915238910631085106240111372475120.00%110.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
23Phantoms30300000621-1520200000315-121010000036-300.00061016009091523114106310851062401804210855120.00%5180.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
24Rocket41300000719-1220200000415-112110000034-120.25071118109091523150106310851062402015015861119.09%5180.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
25Senators413000001022-1220200000313-102110000079-220.250101828009091523147106310851062402436922709111.11%11372.73%01085284138.19%1269350336.23%532141237.68%158310812385611994444
26Sharks2020000029-71010000014-31010000015-400.000246009091523521063108510624011539837300.00%4175.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
27Sound Tigers30300000817-920200000712-51010000015-400.00081523009091523117106310851062401793816779222.22%8362.50%01085284138.19%1269350336.23%532141237.68%158310812385611994444
28Spiders30200100715-81000010056-12020000029-710.1677111800909152311710631085106240165396739111.11%30100.00%01085284138.19%1269350336.23%532141237.68%158310812385611994444
29Stars20200000512-71010000015-41010000047-300.000591400909152368106310851062401192414344125.00%7528.57%01085284138.19%1269350336.23%532141237.68%158310812385611994444
30Wolf Pack312000001112-120200000611-51100000051420.333112132009091523128106310851062401283714739222.22%7185.71%01085284138.19%1269350336.23%532141237.68%158310812385611994444
Total82116101306234413-1794133401201111218-1074182700105123195-72330.2012344156492090915233230106310851062404535126640218142504819.20%1623677.78%11085284138.19%1269350336.23%532141237.68%158310812385611994444
_Since Last GM Reset82116101306234413-1794133401201111218-1074182700105123195-72330.2012344156492090915233230106310851062404535126640218142504819.20%1623677.78%11085284138.19%1269350336.23%532141237.68%158310812385611994444
_Vs Conference4333700102109229-120220200010159127-68213170000150102-5290.10510919730610909152315801063108510624023926552329811201613.33%911979.12%11085284138.19%1269350336.23%532141237.68%158310812385611994444

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8233L7234415649323045351266402181420
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8211611306234413
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
413341201111218
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
418270105123195
Derniers 10 matchs
WLOTWOTL SOWSOL
080101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2504819.20%1623677.78%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
106310851062409091523
Mises en jeu
Gagnées en zone offensiveTotal en zone offensive% gagnées en zone offensive Gagnées en zone défensiveTotal en zone défensive% gagnées en zone défensiveGagnées en zone neutreTotal en zone neutre% gagnées en zone neutre
1085284138.19%1269350336.23%532141237.68%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
158310812385611994444


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
2 - 2021-10-135Cabaret Lady Mary Ann5Thunder2LSommaire du match
4 - 2021-10-1521Thunder4Cabaret Lady Mary Ann5LSommaire du match
5 - 2021-10-1631Thunder2Caroline4LSommaire du match
9 - 2021-10-2047Thunder1Marlies3LSommaire du match
11 - 2021-10-2262Thunder4Senators1WSommaire du match
14 - 2021-10-2586Thunder2Rocket1WSommaire du match
16 - 2021-10-2798Thunder2Bruins3LXXSommaire du match
18 - 2021-10-29117Monsters4Thunder2LSommaire du match
22 - 2021-11-02144Manchots5Thunder4LSommaire du match
25 - 2021-11-05164Chill5Thunder4LXXSommaire du match
28 - 2021-11-08181Thunder5Wolf Pack1WSommaire du match
29 - 2021-11-09188Thunder0Spiders4LSommaire du match
31 - 2021-11-11197Thunder1Sound Tigers5LSommaire du match
38 - 2021-11-18248Thunder3Crunch4LSommaire du match
39 - 2021-11-19253Crunch3Thunder2LSommaire du match
44 - 2021-11-24287Wolf Pack4Thunder3LSommaire du match
46 - 2021-11-26302Oceanics5Thunder4LSommaire du match
49 - 2021-11-29324Thunder2Chiefs3LXXSommaire du match
51 - 2021-12-01341Thunder3Baby Hawks4LXSommaire du match
53 - 2021-12-03355Admirals6Thunder4LSommaire du match
55 - 2021-12-05365Crunch3Thunder2LXSommaire du match
57 - 2021-12-07380Chiefs2Thunder5WSommaire du match
59 - 2021-12-09398Thunder5Bears7LSommaire du match
60 - 2021-12-10408Caroline4Thunder7WSommaire du match
63 - 2021-12-13430Thunder4Chill6LSommaire du match
65 - 2021-12-15440Minnesota2Thunder0LSommaire du match
67 - 2021-12-17457Sharks4Thunder1LSommaire du match
69 - 2021-12-19468Sound Tigers6Thunder3LSommaire du match
70 - 2021-12-20473Thunder7Cabaret Lady Mary Ann5WSommaire du match
72 - 2021-12-22488Bruins3Thunder2LSommaire du match
74 - 2021-12-24509Bears5Thunder3LSommaire du match
77 - 2021-12-27526Senators6Thunder2LSommaire du match
79 - 2021-12-29539Stars5Thunder1LSommaire du match
81 - 2021-12-31559Thunder1Bears6LSommaire du match
83 - 2022-01-02572Cabaret Lady Mary Ann5Thunder7WSommaire du match
88 - 2022-01-07595Rocket8Thunder2LSommaire du match
89 - 2022-01-08607Cougars5Thunder2LSommaire du match
91 - 2022-01-10617Thunder4Crunch3WSommaire du match
93 - 2022-01-12629Thunder1Rocket3LSommaire du match
95 - 2022-01-14648Thunder3Senators8LSommaire du match
96 - 2022-01-15655Thunder4Caroline5LXXSommaire du match
98 - 2022-01-17663Comets5Thunder4LSommaire du match
100 - 2022-01-19680Jayhawks5Thunder2LSommaire du match
102 - 2022-01-21695Thunder3Phantoms6LSommaire du match
103 - 2022-01-22708Thunder2Spiders5LSommaire du match
105 - 2022-01-24716Monarchs6Thunder2LSommaire du match
107 - 2022-01-26736Thunder5Minnesota6LXXSommaire du match
108 - 2022-01-27742Thunder2Oceanics7LSommaire du match
118 - 2022-02-06771Thunder4Stars7LSommaire du match
120 - 2022-02-08779Thunder4Monarchs3WSommaire du match
122 - 2022-02-10791Thunder3Admirals5LSommaire du match
123 - 2022-02-11805Thunder1Sharks5LSommaire du match
126 - 2022-02-14814Las Vegas6Thunder2LSommaire du match
128 - 2022-02-16829Manchots7Thunder3LSommaire du match
130 - 2022-02-18847Sound Tigers6Thunder4LSommaire du match
132 - 2022-02-20863Thunder3Monsters7LSommaire du match
133 - 2022-02-21870Thunder0Manchots1LSommaire du match
135 - 2022-02-23882Oil Kings4Thunder3LSommaire du match
137 - 2022-02-25897Phantoms8Thunder1LSommaire du match
139 - 2022-02-27919Thunder3Monsters4LSommaire du match
142 - 2022-03-02939Thunder7Las Vegas4WSommaire du match
144 - 2022-03-04954Thunder2Jayhawks5LSommaire du match
147 - 2022-03-07970Marlies3Thunder0LSommaire du match
149 - 2022-03-09986Baby Hawks8Thunder1LSommaire du match
151 - 2022-03-111001Heat3Thunder4WXSommaire du match
154 - 2022-03-141019Bruins7Thunder4LSommaire du match
156 - 2022-03-161034Rocket7Thunder2LSommaire du match
158 - 2022-03-181054Thunder0Bruins4LSommaire du match
159 - 2022-03-191060Thunder6Cougars5WSommaire du match
161 - 2022-03-211070Thunder5Marlies8LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
163 - 2022-03-231085Phantoms7Thunder2LSommaire du match
165 - 2022-03-251100Cougars7Thunder2LSommaire du match
166 - 2022-03-261114Spiders6Thunder5LXSommaire du match
169 - 2022-03-291134Thunder4Comets7LSommaire du match
171 - 2022-03-311150Thunder5Oil Kings6LXXSommaire du match
172 - 2022-04-011162Thunder1Heat5LSommaire du match
176 - 2022-04-051185Marlies7Thunder2LSommaire du match
178 - 2022-04-071199Monsters7Thunder2LSommaire du match
179 - 2022-04-081211Wolf Pack7Thunder3LSommaire du match
182 - 2022-04-111228Senators7Thunder1LSommaire du match
184 - 2022-04-131249Thunder1Monsters7LSommaire du match
186 - 2022-04-151264Thunder4Cougars7LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance78,82139,377
Assistance PCT96.12%96.04%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2883 - 96.10% 81,692$3,349,390$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,347,784$ 1,966,584$ 1,974,084$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,557$ 2,353,124$ 25 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 10,516$ 0$




TotalDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT