Connexion

Crunch
GP: 63 | W: 22 | L: 34 | OTL: 7 | P: 51
GF: 234 | GA: 300 | PP%: 21.88% | PK%: 72.47%
DG: Keven St-Amand | Morale : 20 | Moyenne d’équipe : 64
Prochains matchs #838 vs Reign
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Bears
32-28-4, 68pts
5
FINAL
3 Crunch
22-34-7, 51pts
Team Stats
W5StreakL5
16-14-2Home Record13-15-4
16-14-2Away Record9-19-3
6-4-0Last 10 Games3-7-0
4.30Buts par match 3.71
4.20Buts contre par match 4.76
19.70%Pourcentage en avantage numérique21.88%
75.47%Pourcentage en désavantage numérique72.47%
Crunch
22-34-7, 51pts
0
FINAL
3 Marlies
35-22-7, 77pts
Team Stats
L5StreakW2
13-15-4Home Record15-13-4
9-19-3Away Record20-9-3
3-7-0Last 10 Games8-2-0
3.71Buts par match 4.27
4.76Buts contre par match 3.95
21.88%Pourcentage en avantage numérique22.87%
72.47%Pourcentage en désavantage numérique78.37%
Reign
35-25-4, 74pts
2022-05-06
Crunch
22-34-7, 51pts
Statistiques d’équipe
W1SéquenceL5
18-12-2Fiche domicile13-15-4
17-13-2Fiche visiteur9-19-3
3-7-010 derniers matchs3-7-0
4.20Buts par match 3.71
3.88Buts contre par match 4.76
23.62%Pourcentage en avantage numérique21.88%
81.67%Pourcentage en désavantage numérique72.47%
Crunch
22-34-7, 51pts
2022-05-07
Icehogs
28-31-4, 60pts
Statistiques d’équipe
L5SéquenceSOW1
13-15-4Fiche domicile10-19-3
9-19-3Fiche visiteur18-12-1
3-7-010 derniers matchs6-3-1
3.71Buts par match 3.81
4.76Buts contre par match 4.06
21.88%Pourcentage en avantage numérique20.73%
72.47%Pourcentage en désavantage numérique76.52%
Comets
32-23-8, 72pts
2022-05-11
Crunch
22-34-7, 51pts
Statistiques d’équipe
OTL1SéquenceL5
15-11-6Fiche domicile13-15-4
17-12-2Fiche visiteur9-19-3
5-4-110 derniers matchs3-7-0
3.97Buts par match 3.71
3.84Buts contre par match 4.76
17.08%Pourcentage en avantage numérique21.88%
77.87%Pourcentage en désavantage numérique72.47%
Meneurs d'équipe
Buts
Teemu Hartikainen
41
Passes
Brock Boeser
54
Points
Brock Boeser
85
Plus/Moins
Jared Staal
0
Victoires
Kaapo Kahkonen
12
Pourcentage d’arrêts
Kaapo Kahkonen
0.871

Statistiques d’équipe
Buts pour
234
3.71 GFG
Tirs pour
1908
30.29 Avg
Pourcentage en avantage numérique
21.9%
56 GF
Début de zone offensive
35.8%
Buts contre
300
4.76 GAA
Tirs contre
2201
34.94 Avg
Pourcentage en désavantage numérique
72.5%
68 GA
Début de la zone défensive
35.5%
Informations de l'équipe

Directeur généralKeven St-Amand
EntraîneurDenis Savard
DivisionPaul-Loicq
ConférenceLouis-Magnus
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,784
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure23
Limite contact 48 / 250
Espoirs0


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
1Teemu Hartikainen (R)X100.007540787275627774636872706456483433690261900,000$
2Brock Boeser (R)X100.007247787173706569657174636444427634680191500,000$
3Jayson MegnaX100.007874616982588067696668656264623019680261500,000$
4Anthony Cirelli (R)X100.005833906671847258716661745645427716660191500,000$
5Christoffer Ehn (R)X100.005637836870776758746961736046436329660202650,000$
6Michael Ferland (R)X100.007264726580588270616567576547483826650241600,000$
7Dalton Smith (R)X100.006032646970656868666669626248483336640241500,000$
8Jared Staal (R)X100.007331756068647070586061656451512719640261500,000$
9Dylan Strome (R)X100.006028766454756968827765485244427526630191500,000$
10Max McCormick (R)X100.008068716279518759605759525755553517610241375,000$
11Connor Bunnaman (R)X100.005732836860775746575845705140407133590182500,000$
12Noah Hanifin (R)X100.006251807172676672537462656146427339670191500,000$
13Jordan Oesterle (R)X100.007053766074747276586862636254524932670243900,000$
14Matt Roy (R)X100.006049776871766073516664675346485722660211500,000$
15Charles-Olivier Roussel (R)X100.006331717562626367416756665547473116640251500,000$
16Jeremy Lauzon (R)X100.004736797852577072348162715245427323640191500,000$
17Sean Walker (R)X100.006336737267725755267146714945464222640221500,000$
18Jacob Larsson (R)X100.005923697057505770387356634641427236610191500,000$
Rayé
1Mitch Callahan (R)X92.837335706969557165576967586147472825640251450,000$
2Anatoli Golyshev (R)X87.865933707163657063767963485046475729630212500,000$
3Roman JosiX100.0073308674767679735368747364624936127102621,000,000$
4Michael Downing (R)X100.004835656855596268406846634143435017590211500,000$
5Kyle Capobianco (R)X100.005432736643515266346243524141415416550191500,000$
MOYENNE D’ÉQUIPE99.16644075696765686656686163564846512564
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 SPÂgeContratSalaire
1Kaapo Kahkonen98.00626364706866656362726045435635640202600,000$
2Josef Korenar (R)98.00664362626041535360526240406835550182500,000$
Rayé
MOYENNE D’ÉQUIPE98.0064536366645459586162614342623560
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Denis Savard60529576606555Can623500,000$


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
1Brock BoeserCrunch (T.B)RW63315485-185610106862247614013.84%34129520.56112031402153147723044.54%1195420021.31111011443
2Teemu HartikainenCrunch (T.B)LW63413778-17315121922365613217.37%37135221.46108183219622461702239.81%2166227011.15813010542
3Noah HanifinCrunch (T.B)D5573946-9415681069848477.14%64143726.13358122000113162200.00%03055000.6401001021
4Christoffer EhnCrunch (T.B)C58122537-24007812183264414.46%41104217.982810912902231252051.25%9171721000.7123000114
5Dylan StromeCrunch (T.B)C63152035-122208382122317312.30%1396915.39358101130111390056.49%6552414000.7200000301
6Jordan OesterleCrunch (T.B)D5682634-20611586979023358.89%70147326.3071118202080332160110.00%02941000.4613102001
7Anthony CirelliCrunch (T.B)RW45102030-10100418862223416.13%2286319.193101371140002652151.13%6651012000.6901000010
8Jayson MegnaCrunch (T.B)C35111930-5520616268273916.18%1259216.932467660001440049.22%6441411101.0135000111
9Michael FerlandCrunch (T.B)LW37141327-32207042103345613.59%863217.0943712880000151144.44%18177010.8511000201
10Mitch CallahanCrunch (T.B)RW63101626-21240935594364810.64%1569110.97044556000020050.00%282012000.7501000131
11Dalton SmithCrunch (T.B)LW63111425-8400786412823708.59%2281512.95000091122781143.14%512013000.6101000121
12Wiley ShermanLightningD5141620-30048977025365.71%67125224.56347111700004178110.00%02551000.3200000201
13Anatoli GolyshevCrunch (T.B)LW5911920-13180382192195011.96%85218.84000000000291056.52%23254000.7700000002
14Erik ChristensenLightningC1971219-14140343446144715.22%1337119.54371010660000251154.73%45595001.0202000010
15Jeremy LauzonCrunch (T.B)D6031114-1723526765429225.56%52103317.2210111081013104020.00%02331000.2701010002
16Matt RoyCrunch (T.B)D4311112-910018413016173.33%3071316.59011059000054000.00%01017000.3400000000
17Jared StaalCrunch (T.B)RW247310000322227151925.93%729412.2601106000010132.26%3185000.6800000010
18Charles-Olivier RousselCrunch (T.B)D28077-1100151414750.00%1931511.28011326011125000.00%028000.4400000000
19Max McCormickCrunch (T.B)RW46437-7602316196921.05%62796.0800004000000150.00%1814000.5000000011
20Jacob LarssonCrunch (T.B)D63145-72002935207115.00%2866010.49000025000047100.00%0413000.1500000100
21Connor BunnamanCrunch (T.B)C60145-14402935246184.17%194787.9700000000010043.08%19508000.2100000000
22Kyle CapobiancoCrunch (T.B)D22011-440332110.00%81004.5500001011010000.00%012000.2000000000
23Alex KillornLightningLW3000000000000.00%031.140000000002000.00%000000.0000000000
24Michael DowningCrunch (T.B)D24000-780376220.00%81265.290000800008000.00%004000.0000000000
25Roman JosiCrunch (T.B)D7000-500543040.00%89713.8900001000009000.00%026000.0000000000
26Sean WalkerCrunch (T.B)D46000-5220172612660.00%2949010.670000800009000.00%0116000.0000000000
Statistiques d’équipe totales ou en moyenne1156209364573-2534984012051326172755596512.10%6401790315.495292144179189671320351446181250.68%4035408407140.641643134212122
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
1Kaapo KahkonenCrunch (T.B)45122250.8714.452443201811404758200.645314023111
2Josef KorenarCrunch (T.B)28101220.8594.80139920112797504100.696232340000
Statistiques d’équipe totales ou en moyenne73223470.8674.5838434029322011262300.667546363111


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
Anatoli Golyshev (sur la masse salariale)Crunch (T.B)LW211995-01-01Yes187 Lbs5 ft8NoNoNo2Pro & Farm500,000$110,000$0$0$Yes500,000$
Anthony CirelliCrunch (T.B)RW191997-01-01Yes193 Lbs6 ft0NoNoNo1Pro & Farm500,000$110,000$0$0$No
Brock BoeserCrunch (T.B)RW191997-01-01Yes208 Lbs6 ft1NoNoNo1Pro & Farm500,000$110,000$0$0$No
Charles-Olivier RousselCrunch (T.B)D251991-01-01Yes201 Lbs6 ft1NoNoNo1Pro & Farm500,000$110,000$0$0$No
Christoffer EhnCrunch (T.B)C201996-01-01Yes181 Lbs6 ft3NoNoNo2Pro & Farm650,000$143,000$0$0$No750,000$
Connor BunnamanCrunch (T.B)C181998-01-01Yes214 Lbs6 ft3NoNoNo2Pro & Farm500,000$110,000$0$0$No500,000$
Dalton SmithCrunch (T.B)LW241992-01-01Yes206 Lbs6 ft2NoNoNo1Pro & Farm500,000$110,000$0$0$No
Dylan StromeCrunch (T.B)C191997-01-01Yes200 Lbs6 ft3NoNoNo1Pro & Farm500,000$110,000$0$0$No
Jacob LarssonCrunch (T.B)D191997-01-01Yes190 Lbs6 ft2NoNoNo1Pro & Farm500,000$110,000$0$0$No
Jared StaalCrunch (T.B)RW261990-01-01Yes210 Lbs6 ft4NoNoNo1Pro & Farm500,000$110,000$0$0$No
Jayson MegnaCrunch (T.B)C261990-01-01No195 Lbs6 ft1NoNoNo1Pro & Farm500,000$110,000$0$0$No
Jeremy LauzonCrunch (T.B)D191997-01-01Yes204 Lbs6 ft1NoNoNo1Pro & Farm500,000$110,000$0$0$No
Jordan OesterleCrunch (T.B)D241992-01-01Yes183 Lbs6 ft0NoNoNo3Pro & Farm900,000$198,000$0$0$No975,000$1,250,000$
Josef KorenarCrunch (T.B)G181998-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm500,000$110,000$0$0$No500,000$
Kaapo KahkonenCrunch (T.B)G201996-01-01No214 Lbs6 ft2NoNoNo2Pro & Farm600,000$132,000$0$0$No600,000$
Kyle CapobiancoCrunch (T.B)D191997-01-01Yes196 Lbs6 ft1NoNoNo1Pro & Farm500,000$110,000$0$0$No
Matt RoyCrunch (T.B)D211995-01-01Yes200 Lbs6 ft1NoNoNo1Pro & Farm500,000$110,000$0$0$No
Max McCormickCrunch (T.B)RW241992-01-01Yes188 Lbs5 ft11NoNoNo1Pro & Farm375,000$82,500$0$0$No
Michael DowningCrunch (T.B)D211995-01-01Yes185 Lbs6 ft3NoNoNo1Pro & Farm500,000$110,000$0$0$No
Michael FerlandCrunch (T.B)LW241992-01-01Yes215 Lbs6 ft2NoNoNo1Pro & Farm600,000$132,000$0$0$No
Mitch CallahanCrunch (T.B)RW251991-01-01Yes190 Lbs6 ft0NoNoNo1Pro & Farm450,000$99,000$0$0$No
Noah HanifinCrunch (T.B)D191997-01-01Yes215 Lbs6 ft3NoNoNo1Pro & Farm500,000$110,000$0$0$No
Roman JosiCrunch (T.B)D261990-01-01No198 Lbs6 ft2NoNoNo2Pro & Farm1,000,000$220,000$0$0$No1,000,000$
Sean WalkerCrunch (T.B)D221994-01-01Yes194 Lbs6 ft3NoNoNo1Pro & Farm500,000$110,000$0$0$No
Teemu HartikainenCrunch (T.B)LW261990-01-01Yes215 Lbs6 ft1NoNoNo1Pro & Farm900,000$198,000$0$0$No
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2521.76199 Lbs6 ft11.32559,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Teemu HartikainenJayson MegnaBrock Boeser40122
2Michael FerlandChristoffer EhnAnthony Cirelli30122
3Dalton SmithDylan StromeJared Staal20122
4Teemu HartikainenConnor BunnamanMax McCormick10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Noah HanifinJordan Oesterle40122
2Matt RoyCharles-Olivier Roussel30122
3Jeremy LauzonSean Walker20122
4Jacob LarssonNoah Hanifin10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Teemu HartikainenJayson MegnaBrock Boeser60122
2Michael FerlandChristoffer EhnAnthony Cirelli40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Noah HanifinJordan Oesterle60122
2Matt RoyCharles-Olivier Roussel40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jayson MegnaTeemu Hartikainen60122
2Christoffer EhnMichael Ferland40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Noah HanifinJordan Oesterle60122
2Matt RoyCharles-Olivier Roussel40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jayson Megna60122Noah HanifinJordan Oesterle60122
2Christoffer Ehn40122Matt RoyCharles-Olivier Roussel40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jayson MegnaTeemu Hartikainen60122
2Christoffer EhnMichael Ferland40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Noah HanifinJordan Oesterle60122
2Matt RoyCharles-Olivier Roussel40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Teemu HartikainenJayson MegnaBrock BoeserNoah HanifinJordan Oesterle
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Teemu HartikainenJayson MegnaBrock BoeserNoah HanifinJordan Oesterle
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Christoffer Ehn, Michael Ferland, Jared StaalChristoffer Ehn, Michael FerlandChristoffer Ehn
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jeremy Lauzon, Sean Walker, Jacob LarssonJeremy LauzonJeremy Lauzon, Sean Walker
Tirs de pénalité
Teemu Hartikainen, Brock Boeser, Jayson Megna, Anthony Cirelli, Christoffer Ehn
Gardien
#1 : Kaapo Kahkonen, #2 : Josef Korenar


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
1Admirals20100001811-31000000145-11010000046-210.2508142200558984195556669962671742618389222.22%9455.56%1677132950.94%681131751.71%519106548.73%130569013526091187597
2Barracuda30300000917-81010000034-120200000613-700.000914230055898419825666996267111839315113323.08%14285.71%0677132950.94%681131751.71%519106548.73%130569013526091187597
3Bears312000001316-31010000035-2211000001011-120.33313243700558984191055666996267112230136518422.22%40100.00%0677132950.94%681131751.71%519106548.73%130569013526091187597
4Comets2010001067-1000000000002010001067-120.5006713005589841963566699626716721144511218.18%7185.71%0677132950.94%681131751.71%519106548.73%130569013526091187597
5Condors2110000079-2110000004221010000037-420.5007142100558984195856669962671651811354250.00%30100.00%0677132950.94%681131751.71%519106548.73%130569013526091187597
6Devils1010000026-41010000026-40000000000000.00024600558984193156669962671305821100.00%4250.00%0677132950.94%681131751.71%519106548.73%130569013526091187597
7Eagles513000011928-920200000411-7311000011517-230.300193049005589841916556669962671166574011924416.67%20765.00%1677132950.94%681131751.71%519106548.73%130569013526091187597
8Griffins1010000024-2000000000001010000024-200.00023500558984192156669962671241168200.00%30100.00%0677132950.94%681131751.71%519106548.73%130569013526091187597
9Heat20200000811-31010000045-11010000046-200.000813210055898419665666996267169191639500.00%8362.50%0677132950.94%681131751.71%519106548.73%130569013526091187597
10Icehogs1010000026-41010000026-40000000000000.00023500558984192656669962671311512212150.00%6183.33%0677132950.94%681131751.71%519106548.73%130569013526091187597
11Little Stars31200000914-531200000914-50000000000020.33391726005589841994566699626711113422698112.50%11554.55%2677132950.94%681131751.71%519106548.73%130569013526091187597
12Marlies31200000911-2110000006332020000038-520.33391423005589841979566699626711072220537342.86%10460.00%0677132950.94%681131751.71%519106548.73%130569013526091187597
13Monsters210000011091110000005321000000156-130.75010192900558984197056669962671732518457228.57%9366.67%1677132950.94%681131751.71%519106548.73%130569013526091187597
14Moose20100010910-1100000106511010000035-220.5009122100558984194356669962671783320369222.22%10370.00%1677132950.94%681131751.71%519106548.73%130569013526091187597
15Penguins411000112022-2311000101718-11000000134-150.62520335300558984191325666996267113432509225728.00%20860.00%0677132950.94%681131751.71%519106548.73%130569013526091187597
16Phantoms2020000039-61010000024-21010000015-400.00034700558984196056669962671742616358112.50%8187.50%0677132950.94%681131751.71%519106548.73%130569013526091187597
17Punishers20100010911-2100000105411010000047-320.500915240055898419605666996267181261643800.00%8362.50%0677132950.94%681131751.71%519106548.73%130569013526091187597
18Rampage4300000115105320000019721100000063370.8751527420055898419126566699626711445034939222.22%17194.12%1677132950.94%681131751.71%519106548.73%130569013526091187597
19Reign1010000036-3000000000001010000036-300.00035800558984193056669962671331011225240.00%3166.67%0677132950.94%681131751.71%519106548.73%130569013526091187597
20Rocket20000011111101000000167-11000001054130.75011172800558984195656669962671721918387342.86%9455.56%1677132950.94%681131751.71%519106548.73%130569013526091187597
21Senators20100010910-11010000046-21000001054120.500912210055898419565666996267169162428300.00%12466.67%0677132950.94%681131751.71%519106548.73%130569013526091187597
22Sound Tigers321000001011-12110000079-21100000032140.667101424005589841910156669962671873118621400.00%9277.78%0677132950.94%681131751.71%519106548.73%130569013526091187597
23Thunderbirds20100001411-71000000123-11010000028-610.250481200558984197156669962671531717647114.29%6183.33%0677132950.94%681131751.71%519106548.73%130569013526091187597
24Wolfpack64200000302643210000017125321000001314-180.6673052820055898419182566699626712075461117391128.21%26580.77%0677132950.94%681131751.71%519106548.73%130569013526091187597
25Wolves30300000714-71010000013-220200000611-500.000712190055898419765666996267111227226411327.27%11372.73%0677132950.94%681131751.71%519106548.73%130569013526091187597
Total63163400067234300-6632101500034122142-203161900033112158-46510.4052343876210055898419190856669962671220166353613032565621.88%2476872.47%8677132950.94%681131751.71%519106548.73%130569013526091187597
_Since Last GM Reset63163400067234300-6632101500034122142-203161900033112158-46510.4052343876210055898419190856669962671220166353613032565621.88%2476872.47%8677132950.94%681131751.71%519106548.73%130569013526091187597
_Vs Conference38131800034144176-3221710000227692-161768000126884-16360.474144243387005589841912065666996267113143843158541753520.00%1433873.43%4677132950.94%681131751.71%519106548.73%130569013526091187597
_Vs Division1767000137387-14934000114044-4833000023343-10170.50073123196005589841955056669962671560160168392952324.21%722170.83%1677132950.94%681131751.71%519106548.73%130569013526091187597

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6351L523438762119082201663536130300
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6316340067234300
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3210150034122142
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
316190033112158
Derniers 10 matchs
WLOTWOTL SOWSOL
270010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2565621.88%2476872.47%8
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
5666996267155898419
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
677132950.94%681131751.71%519106548.73%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
130569013526091187597


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 - 2021-12-017Rampage3Crunch5BWSommaire du match
5 - 2021-12-0418Crunch5Wolfpack2AWR1Sommaire du match
8 - 2021-12-0734Crunch3Penguins4ALXXSommaire du match
10 - 2021-12-0944Wolfpack1Crunch6BWR1Sommaire du match
12 - 2021-12-1157Crunch6Eagles7ALXXSommaire du match
14 - 2021-12-1367Crunch6Bears3AWSommaire du match
16 - 2021-12-1574Little Stars3Crunch2BLSommaire du match
20 - 2021-12-1996Penguins7Crunch8BWXXR1Sommaire du match
23 - 2021-12-22112Crunch2Thunderbirds8ALR1Sommaire du match
25 - 2021-12-24119Thunderbirds3Crunch2BLXXSommaire du match
27 - 2021-12-26133Crunch4Punishers7ALSommaire du match
29 - 2021-12-28146Eagles4Crunch1BLR1Sommaire du match
33 - 2022-01-01166Rampage2Crunch1BLXXSommaire du match
36 - 2022-01-04184Icehogs6Crunch2BLSommaire du match
38 - 2022-01-06196Crunch5Comets4AWXXSommaire du match
40 - 2022-01-08206Crunch4Bears8ALSommaire du match
41 - 2022-01-09217Monsters3Crunch5BWSommaire du match
44 - 2022-01-12232Crunch3Moose5ALSommaire du match
46 - 2022-01-14241Crunch2Wolves5ALSommaire du match
47 - 2022-01-15252Rampage2Crunch3BWSommaire du match
50 - 2022-01-18265Crunch4Admirals6ALSommaire du match
52 - 2022-01-20275Phantoms4Crunch2BLSommaire du match
56 - 2022-01-24292Crunch5Senators4AWXXSommaire du match
58 - 2022-01-26302Penguins6Crunch2BLR1Sommaire du match
60 - 2022-01-28318Crunch3Eagles7ALSommaire du match
62 - 2022-01-30326Eagles7Crunch3BLR1Sommaire du match
66 - 2022-02-03348Moose5Crunch6BWXXSommaire du match
69 - 2022-02-06367Crunch2Barracuda8ALSommaire du match
71 - 2022-02-08376Condors2Crunch4BWSommaire du match
73 - 2022-02-10391Crunch3Condors7ALSommaire du match
75 - 2022-02-12398Crunch2Griffins4ALSommaire du match
77 - 2022-02-14407Senators6Crunch4BLSommaire du match
80 - 2022-02-17426Marlies3Crunch6BWSommaire du match
86 - 2022-02-23449Punishers4Crunch5BWXXSommaire du match
90 - 2022-02-27473Little Stars7Crunch1BLSommaire du match
94 - 2022-03-03494Crunch1Phantoms5ALSommaire du match
95 - 2022-03-04501Admirals5Crunch4BLXXSommaire du match
98 - 2022-03-07516Crunch3Wolfpack9ALR1Sommaire du match
100 - 2022-03-09525Sound Tigers3Crunch4BWSommaire du match
102 - 2022-03-11533Crunch3Reign6ALSommaire du match
106 - 2022-03-15552Rocket7Crunch6BLXXSommaire du match
108 - 2022-03-17564Crunch5Wolfpack3AWR1Sommaire du match
110 - 2022-03-19569Crunch3Sound Tigers2AWSommaire du match
111 - 2022-03-20580Wolfpack5Crunch6BWR1Sommaire du match
115 - 2022-03-24592Crunch4Heat6ALSommaire du match
117 - 2022-03-26605Heat5Crunch4BLSommaire du match
121 - 2022-03-30625Crunch4Barracuda5ALSommaire du match
123 - 2022-04-01632Wolfpack6Crunch5BLR1Sommaire du match
125 - 2022-04-03648Crunch6Rampage3AWSommaire du match
127 - 2022-04-05656Crunch1Comets3ALSommaire du match
128 - 2022-04-06662Penguins5Crunch7BWR1Sommaire du match
130 - 2022-04-08679Crunch5Monsters6ALXXSommaire du match
131 - 2022-04-09687Sound Tigers6Crunch3BLSommaire du match
135 - 2022-04-13707Crunch6Eagles3AWR1Sommaire du match
137 - 2022-04-15715Devils6Crunch2BLSommaire du match
140 - 2022-04-18734Little Stars4Crunch6BWSommaire du match
141 - 2022-04-19740Crunch3Marlies5ALSommaire du match
145 - 2022-04-23760Crunch5Rocket4AWXXSommaire du match
146 - 2022-04-24766Barracuda4Crunch3BLSommaire du match
149 - 2022-04-27786Wolves3Crunch1BLSommaire du match
151 - 2022-04-29795Crunch4Wolves6ALSommaire du match
154 - 2022-05-02812Bears5Crunch3BLSommaire du match
156 - 2022-05-04821Crunch0Marlies3ALSommaire du match
158 - 2022-05-06838Reign-Crunch-
159 - 2022-05-07844Crunch-Icehogs-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
163 - 2022-05-11863Comets-Crunch-
165 - 2022-05-13876Crunch-Little Stars-
167 - 2022-05-15888Crunch-Thunderbirds-
169 - 2022-05-17892Icehogs-Crunch-
173 - 2022-05-21914Crunch-Thunderbirds-
175 - 2022-05-23921Devils-Crunch-
178 - 2022-05-26936Crunch-Devils-
180 - 2022-05-28946Thunderbirds-Crunch-
182 - 2022-05-30959Crunch-Punishers-
184 - 2022-06-01973Thunderbirds-Crunch-
186 - 2022-06-03980Crunch-Bears-
188 - 2022-06-05988Crunch-Penguins-
191 - 2022-06-081003Eagles-Crunch-
192 - 2022-06-091009Crunch-Penguins-
198 - 2022-06-151031Griffins-Crunch-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance59,08530,009
Assistance PCT92.32%93.78%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
8 2784 - 92.81% 82,625$2,644,014$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,457,966$ 1,397,500$ 1,117,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
6,738$ 1,040,466$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
661,004$ 44 9,488$ 417,472$




Crunch Leaders statistiques (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Crunch Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Crunch Statistiques de l'Équipe de Carrière

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

Crunch Leaders statistiques (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Crunch Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA