Connexion

Jayhawks
GP: 82 | W: 40 | L: 33 | OTL: 9 | P: 89
GF: 309 | GA: 313 | PP%: 25.86% | PK%: 77.61%
DG: Yves Létourneau | Morale : 50 | Moyenne d’équipe : 54
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Centre de jeu
Comets
42-31-9, 93pts
4
FINAL
5 Jayhawks
40-33-9, 89pts
Team Stats
W1StreakW2
22-16-3Home Record19-16-6
20-15-6Away Record21-17-3
4-2-4Last 10 Games5-4-1
3.60Goals Per Game3.77
3.50Goals Against Per Game3.82
20.75%Power Play Percentage25.86%
78.66%Penalty Kill Percentage77.61%
Oceanics
52-20-10, 114pts
2
FINAL
5 Jayhawks
40-33-9, 89pts
Team Stats
L1StreakW2
30-6-5Home Record19-16-6
22-14-5Away Record21-17-3
6-3-1Last 10 Games5-4-1
4.17Goals Per Game3.77
3.55Goals Against Per Game3.82
23.77%Power Play Percentage25.86%
75.38%Penalty Kill Percentage77.61%
Meneurs d'équipe
Buts
Matt Tennyson
6
Passes
Matt Tennyson
9
Points
Matt Tennyson
15
Plus/Moins
Greg Pateryn
2
Victoires
Connor Ingram
40
Pourcentage d’arrêts
Kirill Ustimenko
0.937

Statistiques d’équipe
Buts pour
309
3.77 GFG
Tirs pour
3514
42.85 Avg
Pourcentage en avantage numérique
25.9%
68 GF
Début de zone offensive
41.4%
Buts contre
313
3.82 GAA
Tirs contre
3371
41.11 Avg
Pourcentage en désavantage numérique
77.6%
60 GA
Début de la zone défensive
40.2%
Information d’équipe

Directeur généralYves Létourneau
DivisionWest
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,905
Billets de saison300


Information formation

Équipe Pro23
Équipe Mineure23
Limite contact 46 / 50
Espoirs26


Historique d'équipe

Saison actuelle40-33-9 (89PTS)
Historique40-33-8 (0.494%)
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
1James NealXX100.007344887479626672336370526281860506403314,000,000$
2Luke PhilpX100.00807299676570656784626869594444050620241850,000$
3Josh Dunne (R)X100.00808081788055546176467166674444050600214925,000$
4Jack Dugan (R)X100.00737080627062626550656264594444050590222525,000$
5Tanner Laczynski (R)XXX100.00747180597156546379566764644444050580232925,000$
6Justin KloosXX100.00686680596467675571555461534545050560261792,500$
7Ivan Morozov (R)X100.00534886677172955360484853505051050550204700,000$
8Matt Filipe (R)X100.00747375607351515150485061484444050530221700,000$
9Matthew Strome (R)X100.00787891547857594749434664454444050520212990,000$
10Matt IacopelliXX100.00334343436531313343333343383230050370261710,000$
11Julius Vahatalo (R)X100.00303737376727273037303037323230050340251560,000$
12Michal KempnyX100.006742847570707655255645732461630506403031,700,000$
13Chase PriskieX100.00837599656864596228485869504444050600241560,000$
14Alex Green (R)X100.00797392637354555025464063384444050560221560,000$
15Scott Perunovich (R)X100.00585050686158744725523354355858050550224925,000$
16Chad Krys (R)X100.00696785666753564525353959384444050530221825,000$
Rayé
MOYENNE D’ÉQUIPE100.0067627862705759544849516048474705055
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
1Connor Ingram100.0057507177575958635959304444050580
2Kirill Ustimenko (R)100.0056706570565556565455545454050570
Rayé
1Kyle Keyser (R)100.0053475869565454585554334844050540
2Adam Huska100.0049486787474952564950304444050530
3Dustin Wolf (R)100.0050556960485050554949304444050510
4Arvid Soderblom (R)100.004545454545454545454545454501440
5Erik Kallgren (R)100.003737373737373737373737373701370
MOYENNE D’ÉQUIPE100.005050596449505053505037454503651
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
1Michal KempnyJayhawks (KC )D6511597018540130118157611127.01%148150023.0851318741510113150100.00%000000.9300000214
2Chase PriskieJayhawks (KC )D7422466815551516983177489912.43%109146719.838917671300222139220.00%000010.9300111442
3Jack DuganJayhawks (KC )LW71293766213001161132686818010.82%26133418.80710174114621351313446.73%10700000.9901000525
4Tanner LaczynskiJayhawks (KC )C/LW/RW7631336415360105952647017611.74%23127816.8251318381450002455258.68%12100001.0011000433
5Luke PhilpJayhawks (KC )C4928285693410811522797617810.04%25101520.72549389122481332059.69%157300021.1036002622
6Josh DunneJayhawks (KC )C7722254710275120150245621848.98%2082110.6723517450002435257.22%92800121.1434001431
7James NealJayhawks (KC )LW/RW53182139161003258182521119.89%875614.2731415700002201147.27%5500011.0328000024
8Justin KloosJayhawks (KC )C/RW44101727-3160466811134799.01%871216.202461342000060253.66%12300000.7612000023
9Matt TennysonKansas CityD336915-816076477227498.33%4765019.701341858011055210.00%000000.4600000200
10Matt FilipeJayhawks (KC )LW443710-34030295714335.26%83568.091235200001430051.52%3300000.5600000010
11Scott PerunovichJayhawks (KC )D281910-10180612712498.33%2743215.4600003000021000.00%000000.4600000001
12Ivan MorozovJayhawks (KC )C40459-137522576522476.15%33929.8100000000000150.27%37600000.4601100000
13Greg PaterynKansas CityD1016722014911589.09%916016.030000000000000.00%000000.8700000000
14Alex GreenJayhawks (KC )D2013412204012248134.17%2935217.62011519000035000.00%000000.2300000001
15Matthew StromeJayhawks (KC )LW1204441558620670.00%416713.9500001000010050.00%1600000.4800001000
16Julius VahataloJayhawks (KC )LW28011-14601325040.00%235312.6100001000030038.10%2100000.0600000000
17Chad KrysJayhawks (KC )D12000-21001669030.00%2218815.740000000003000.00%000000.0000000000
18Matt IacopelliJayhawks (KC )LW/RW20000-180126220.00%21527.6400001000000042.86%700000.0000000000
Statistiques d’équipe totales ou en moyenne756187310497573704010801034196455912949.52%5201209316.003963102331928471125836211556.79%336000160.821023215272026
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
1Connor IngramJayhawks (KC )82403080.9083.69470560289313001020.61942820254
2Kirill UstimenkoJayhawks (KC )80310.9373.1828300152380110.5004082000
Statistiques d’équipe totales ou en moyenne90403390.9103.66498960304336801130.609468282254


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 HuskaJayhawks (KC )G231997-05-12No218 Lbs6 ft4NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Alex GreenJayhawks (KC )D221998-06-17Yes194 Lbs6 ft3YesNoNo1Pro & Farm560,000$56,000$0$NoLien
Arvid SoderblomJayhawks (KC )G211999-08-19 06:07:53Yes180 Lbs6 ft3NoNoNo4Pro & Farm883,750$88,375$0$No883,750$883,750$883,750$
Chad KrysJayhawks (KC )D221998-04-10Yes185 Lbs5 ft11NoNoNo1Pro & Farm825,000$82,500$0$NoLien
Chase PriskieJayhawks (KC )D241996-03-18No185 Lbs6 ft0YesNoNo1Pro & Farm560,000$56,000$0$NoLien
Connor IngramJayhawks (KC )G231997-03-30No196 Lbs6 ft2NoNoNo1Pro & Farm742,500$74,250$0$NoLien
Dustin WolfJayhawks (KC )G192001-04-16Yes168 Lbs6 ft0NoNoNo3Pro & Farm815,833$81,583$0$No815,833$815,833$Lien
Erik KallgrenJayhawks (KC )G231996-10-14 06:04:56Yes198 Lbs6 ft3NoNoNo4Pro & Farm750,000$75,000$0$No750,000$750,000$750,000$
Ivan MorozovJayhawks (KC )C202000-05-05Yes196 Lbs6 ft1NoNoNo4Pro & Farm700,000$70,000$0$No700,000$700,000$700,000$Lien
Jack DuganJayhawks (KC )LW221998-03-24Yes185 Lbs6 ft2NoNoNo2Pro & Farm525,000$52,500$0$No525,000$Lien
James NealJayhawks (KC )LW/RW331987-09-03No212 Lbs6 ft3NoNoNo1Pro & Farm4,000,000$400,000$0$NoLien
Josh DunneJayhawks (KC )C211998-12-08Yes210 Lbs6 ft4NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Lien
Julius VahataloJayhawks (KC )LW251995-05-23Yes191 Lbs6 ft5NoNoNo1Pro & Farm560,000$56,000$0$NoLien
Justin KloosJayhawks (KC )C/RW261993-11-30No180 Lbs5 ft9NoNoNo1Pro & Farm792,500$79,250$0$NoLien
Kirill UstimenkoJayhawks (KC )G211999-01-29Yes187 Lbs6 ft3NoNoNo2Pro & Farm825,833$82,583$0$No825,833$Lien
Kyle KeyserJayhawks (KC )G211999-03-08Yes178 Lbs6 ft2YesNoNo1Pro & Farm800,000$80,000$0$NoLien
Luke PhilpJayhawks (KC )C241995-11-05No181 Lbs5 ft10NoNoNo1Pro & Farm850,000$85,000$0$NoLien
Matt FilipeJayhawks (KC )LW221997-12-30Yes198 Lbs6 ft2NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Matt IacopelliJayhawks (KC )LW/RW261994-05-15No192 Lbs6 ft1NoNoNo1Pro & Farm710,000$71,000$0$NoLien
Matthew StromeJayhawks (KC )LW211999-01-05Yes206 Lbs6 ft4NoNoNo2Pro & Farm990,000$99,000$0$No990,000$Lien
Michal KempnyJayhawks (KC )D301990-09-08No194 Lbs6 ft0YesNoNo3Pro & Farm1,700,000$170,000$0$No1,700,000$1,700,000$Lien
Scott PerunovichJayhawks (KC )D221998-08-18Yes174 Lbs5 ft10NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Lien
Tanner LaczynskiJayhawks (KC )C/LW/RW231997-06-01Yes190 Lbs6 ft1NoNoNo2Pro & Farm925,000$92,500$0$No925,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2323.22191 Lbs6 ft22.00938,714$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jack DuganLuke PhilpJames Neal40122
2Matthew StromeJosh DunneTanner Laczynski30122
3Julius VahataloIvan MorozovJustin Kloos30122
4Matt FilipeJustin KloosMatt Iacopelli0122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michal Kempny40122
2Chase PriskieAlex Green30122
3Scott PerunovichChad Krys30122
4Michal Kempny0122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jack DuganLuke PhilpJames Neal60122
2Matt FilipeJosh DunneTanner Laczynski40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michal Kempny60122
2Chase PriskieAlex Green40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Luke PhilpJack Dugan60122
2Josh DunneMatt Filipe40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michal Kempny60122
2Chase PriskieAlex Green40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Luke Philp60122Michal Kempny60122
2Josh Dunne40122Chase PriskieAlex Green40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Luke PhilpJack Dugan60122
2Josh DunneMatt Filipe40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michal Kempny60122
2Chase PriskieAlex Green40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jack DuganLuke PhilpJames NealMichal Kempny
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jack DuganLuke PhilpJames NealMichal Kempny
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tanner Laczynski, Justin Kloos, Ivan MorozovTanner Laczynski, Justin KloosTanner Laczynski
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Alex Green, Scott Perunovich, Chad KrysAlex GreenAlex Green, Scott Perunovich
Tirs de pénalité
James Neal, Luke Philp, Josh Dunne, Jack Dugan, Tanner Laczynski
Gardien
#1 : Connor Ingram, #2 : Kirill Ustimenko


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
1Admirals42100100161152200000010372010010068-250.6251629450012383951816511831135115387157413511018422.22%8187.50%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
2Baby Hawks311000011316-320100001814-61100000052330.50013223500123839518152118311351153871494916698225.00%8362.50%11678324351.74%1535315048.73%754144152.32%1922131720046011066531
3Bears2020000058-31010000024-21010000034-100.00051015001238395188111831135115387922921426116.67%7271.43%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
4Bruins2020000049-51010000024-21010000025-300.0004711001238395187111831135115387852112579222.22%6266.67%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
5Cabaret Lady Mary Ann211000001192110000007341010000046-220.5001119300012383951810511831135115387783116387342.86%7185.71%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
6Caroline211000009901010000036-31100000063320.500917260012383951810011831135115387791814339333.33%7271.43%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
7Chiefs302000101013-31010000057-22010001056-120.3331014240012383951896118311351153871234220759222.22%10460.00%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
8Chill32100000862211000005411100000032140.66781523001238395181161183113511538710738296011218.18%12283.33%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
9Comets4120001016160201000108802110000088040.500162844001238395181561183113511538715865508711327.27%19668.42%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
10Cougars20100010660100000103211010000034-120.500681400123839518111118311351153878825653900.00%30100.00%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
11Crunch21000001990110000005411000000145-130.75091625001238395189911831135115387952216558225.00%8275.00%11678324351.74%1535315048.73%754144152.32%1922131720046011066531
12Heat402010011320-72010000136-3201010001014-430.375132134001238395181561183113511538714838259910220.00%8187.50%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
13Las Vegas5400100025141121001000752330000001899101.0002545700012383951826811831135115387199615412017635.29%14378.57%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
14Manchots20200000713-61010000048-41010000035-200.00071118101238395189711831135115387992510484125.00%5180.00%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
15Marlies2110000068-2110000005411010000014-320.50061016001238395187911831135115387841610417114.29%50100.00%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
16Minnesota321000001495211000008711100000062440.66714243800123839518134118311351153871033314827342.86%70100.00%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
17Monarchs413000001517-220200000710-32110000087120.2501524391012383951814611831135115387174563310212325.00%14564.29%21678324351.74%1535315048.73%754144152.32%1922131720046011066531
18Monsters200001109901000010045-11000001054130.75091423001238395188011831135115387802321386233.33%8187.50%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
19Monsters30200010915-61010000014-320100010811-320.33391625001238395181071183113511538712837166911327.27%8275.00%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
20Oceanics321000001192110000005232110000067-140.6671120310012383951895118311351153871393928717342.86%14192.86%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
21Oil Kings412000011117-62110000057-220100001610-430.37511193000123839518152118311351153871623633976350.00%12283.33%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
22Phantoms21100000810-2110000005411010000036-320.500816240012383951885118311351153871052935589444.44%9455.56%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
23Rocket200000117701000000123-11000001054130.7507101700123839518871183113511538781218598112.50%4175.00%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
24Senators2100010010821000010056-11100000052330.750101525001238395189111831135115387831918498112.50%9277.78%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
25Sharks413000001116-52020000059-42110000067-120.250111829101238395181681183113511538717239308513323.08%15473.33%11678324351.74%1535315048.73%754144152.32%1922131720046011066531
26Sound Tigers22000000963110000004311100000053241.00091322001238395187411831135115387871918464250.00%9188.89%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
27Spiders21100000770110000004221010000035-220.50079160012383951893118311351153877326143311327.27%6183.33%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
28Stars3200000114952100000110731100000042250.83314264000123839518130118311351153879428297212216.67%11463.64%11678324351.74%1535315048.73%754144152.32%1922131720046011066531
29Thunder220000001046110000005231100000052341.000101929001238395181191183113511538791251664200.00%8275.00%11678324351.74%1535315048.73%754144152.32%1922131720046011066531
30Wolf Pack22000000633110000002111100000042241.000611170012383951810111831135115387581114464125.00%70100.00%01678324351.74%1535315048.73%754144152.32%1922131720046011066531
Total82323302366309313-441161601224149154-5411617011421601591890.54330952683530123839518351411831135115387337196266119582636825.86%2686077.61%71678324351.74%1535315048.73%754144152.32%1922131720046011066531
_Since Last GM Reset82323302366309313-441161601224149154-5411617011421601591890.54330952683530123839518351411831135115387337196266119582636825.86%2686077.61%71678324351.74%1535315048.73%754144152.32%1922131720046011066531
_Vs Conference42141502056167169-22168010247583-821870103292866480.57116728545200123839518185311831135115387168550631710081323526.52%1263175.40%31678324351.74%1535315048.73%754144152.32%1922131720046011066531

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8289W230952683535143371962661195830
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8232332366309313
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4116161224149154
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4116171142160159
Derniers 10 matchs
WLOTWOTL SOWSOL
540001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2636825.86%2686077.61%7
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
11831135115387123839518
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
1678324351.74%1535315048.73%754144152.32%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1922131720046011066531


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 - 2021-10-1312Jayhawks1Admirals2LSommaire du match
4 - 2021-10-1526Bruins4Jayhawks2LSommaire du match
9 - 2021-10-2057Las Vegas3Jayhawks4WSommaire du match
11 - 2021-10-2272Jayhawks4Monsters3WXXSommaire du match
14 - 2021-10-2587Jayhawks3Oceanics2WSommaire du match
16 - 2021-10-27104Chill2Jayhawks4WSommaire du match
18 - 2021-10-29115Senators6Jayhawks5LXSommaire du match
21 - 2021-11-01136Jayhawks4Wolf Pack2WSommaire du match
23 - 2021-11-03146Jayhawks5Sound Tigers3WSommaire du match
24 - 2021-11-04157Jayhawks3Spiders5LSommaire du match
27 - 2021-11-07177Jayhawks4Crunch5LXXSommaire du match
29 - 2021-11-09191Rocket3Jayhawks2LXXSommaire du match
32 - 2021-11-12214Monsters4Jayhawks1LSommaire du match
34 - 2021-11-14223Jayhawks4Oil Kings5LXXSommaire du match
35 - 2021-11-15231Jayhawks6Heat5WXSommaire du match
37 - 2021-11-17246Monsters5Jayhawks4LXSommaire du match
39 - 2021-11-19259Minnesota2Jayhawks4WSommaire du match
41 - 2021-11-21270Jayhawks3Bears4LSommaire du match
42 - 2021-11-22275Jayhawks4Chiefs3WXXSommaire du match
44 - 2021-11-24289Jayhawks6Minnesota2WSommaire du match
46 - 2021-11-26301Heat3Jayhawks1LSommaire du match
48 - 2021-11-28317Monarchs6Jayhawks5LSommaire du match
51 - 2021-12-01343Marlies4Jayhawks5WSommaire du match
53 - 2021-12-03350Jayhawks5Monarchs3WSommaire du match
54 - 2021-12-04364Oil Kings5Jayhawks2LSommaire du match
57 - 2021-12-07386Admirals2Jayhawks5WSommaire du match
59 - 2021-12-09399Jayhawks4Las Vegas3WSommaire du match
60 - 2021-12-10411Sharks5Jayhawks3LSommaire du match
63 - 2021-12-13429Jayhawks5Monsters4WXXSommaire du match
65 - 2021-12-15442Jayhawks3Phantoms6LSommaire du match
66 - 2021-12-16449Jayhawks3Manchots5LSommaire du match
68 - 2021-12-18466Jayhawks5Baby Hawks2WSommaire du match
70 - 2021-12-20480Heat3Jayhawks2LXXSommaire du match
72 - 2021-12-22495Baby Hawks5Jayhawks4LXXSommaire du match
74 - 2021-12-24512Spiders2Jayhawks4WSommaire du match
77 - 2021-12-27534Jayhawks4Sharks3WSommaire du match
79 - 2021-12-29546Minnesota5Jayhawks4LSommaire du match
82 - 2022-01-01567Jayhawks3Cougars4LSommaire du match
83 - 2022-01-02576Jayhawks3Chill2WSommaire du match
88 - 2022-01-07600Jayhawks8Las Vegas4WSommaire du match
89 - 2022-01-08609Stars2Jayhawks6WSommaire du match
91 - 2022-01-10625Chiefs7Jayhawks5LSommaire du match
93 - 2022-01-12636Admirals1Jayhawks5WSommaire du match
95 - 2022-01-14650Phantoms4Jayhawks5WSommaire du match
98 - 2022-01-17664Jayhawks4Cabaret Lady Mary Ann6LSommaire du match
100 - 2022-01-19680Jayhawks5Thunder2WSommaire du match
101 - 2022-01-20690Jayhawks6Caroline3WSommaire du match
103 - 2022-01-22706Manchots8Jayhawks4LSommaire du match
105 - 2022-01-24724Sharks4Jayhawks2LSommaire du match
107 - 2022-01-26739Jayhawks3Comets6LSommaire du match
109 - 2022-01-28745Jayhawks2Oil Kings5LSommaire du match
120 - 2022-02-08778Jayhawks5Admirals6LXSommaire du match
121 - 2022-02-09784Monarchs4Jayhawks2LSommaire du match
123 - 2022-02-11800Baby Hawks9Jayhawks4LSommaire du match
126 - 2022-02-14824Oil Kings2Jayhawks3WSommaire du match
128 - 2022-02-16838Caroline6Jayhawks3LSommaire du match
130 - 2022-02-18844Jayhawks2Bruins5LSommaire du match
132 - 2022-02-20860Jayhawks5Rocket4WXXSommaire du match
133 - 2022-02-21867Jayhawks1Marlies4LSommaire du match
135 - 2022-02-23885Jayhawks5Senators2WSommaire du match
137 - 2022-02-25904Bears4Jayhawks2LSommaire du match
139 - 2022-02-27917Sound Tigers3Jayhawks4WSommaire du match
141 - 2022-03-01929Jayhawks4Stars2WSommaire du match
142 - 2022-03-02938Jayhawks1Chiefs3LSommaire du match
144 - 2022-03-04954Thunder2Jayhawks5WSommaire du match
147 - 2022-03-07979Cabaret Lady Mary Ann3Jayhawks7WSommaire du match
151 - 2022-03-111006Crunch4Jayhawks5WSommaire du match
155 - 2022-03-151032Jayhawks5Comets2WSommaire du match
157 - 2022-03-171046Jayhawks4Heat9LSommaire du match
160 - 2022-03-201067Jayhawks3Oceanics5LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
163 - 2022-03-231092Comets4Jayhawks3LSommaire du match
165 - 2022-03-251107Wolf Pack1Jayhawks2WSommaire du match
167 - 2022-03-271122Stars5Jayhawks4LXXSommaire du match
169 - 2022-03-291135Las Vegas2Jayhawks3WXSommaire du match
171 - 2022-03-311152Cougars2Jayhawks3WXXSommaire du match
173 - 2022-04-021169Jayhawks3Monarchs4LSommaire du match
176 - 2022-04-051190Jayhawks6Las Vegas2WSommaire du match
179 - 2022-04-081214Chill2Jayhawks1LSommaire du match
180 - 2022-04-091223Jayhawks2Sharks4LSommaire du match
182 - 2022-04-111235Jayhawks4Monsters8LSommaire du match
184 - 2022-04-131253Comets4Jayhawks5WXXSommaire du match
186 - 2022-04-151259Oceanics2Jayhawks5WSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5020
Assistance50,30427,785
Assistance PCT61.35%67.77%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 1905 - 63.49% 74,900$3,070,900$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,347,651$ 2,159,041$ 2,159,041$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
11,546$ 2,347,651$ 23 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 11,546$ 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