Crunch

GP: 60 | W: 24 | L: 32 | OTL: 4 | P: 52
GF: 278 | GA: 332 | PP%: 43.60% | PK%: 54.44%
DG: Hugues Blais | Morale : 44 | Moyenne d'Équipe : 67
Prochain matchs #769 vs Senateurs
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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 SP
1Gabriel BourqueX100.008141817969767869565057746862584870680
2Anders BjorkXX100.006041827967766877655060626651515653640
3Michael AmadioX100.006042777175689071745058616751516453630
4Mark BarberioX100.006142837575807379305454786759574131700
5Brad HuntX100.005941888461796982306755696653523560690
6Sebastian D AhoX100.005542798358679077305054746351515759680
7Andrei MironovX100.005943765376536560305055735950506070620
Rayé
MOYENNE D'ÉQUIPE100.00624281756971767445535670655453525766
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
1Laurent Brossoit100.00758080847774777577737352644767730
2Zane McIntyre100.00747374837374777373716951634720700
Rayé
1Samuel Montembeault (R)100.00697172817171717070676750604418670
MOYENNE D'ÉQUIPE100.0073757583747375737370705162463570
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Scott Arniel62847578858679can5511,200,000$


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'ÉquipePOS GP 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
1Brad HuntCrunch (TB.)D60155368-119530432171091276.91%70110418.411314272452000254210.00%03074001.2300001874
2Anders BjorkCrunch (TB.)LW/RW19282149121202316114427724.56%736419.1810122217381015512263.16%573412042.6900000622
3Sebastian D AhoCrunch (TB.)D60103444-480223017893685.62%4274712.459918203502243920100.00%31660011.1800000467
4Gabriel BourqueCrunch (TB.)LW1914274110100302597286314.43%1136519.256152114370112503060.67%1782211002.2400000115
5Michael AmadioCrunch (TB.)C19728357260212539233117.95%1333417.61315186370113280168.50%692711002.0900000030
6Mark BarberioCrunch (TB.)D1952429610028239643525.21%3149726.19412161352000151110.00%21736001.1700000023
7Andrei MironovCrunch (TB.)D1941519316015107128335.63%2837019.4937101336000133100.00%1728001.0300000013
Stats d'équipe Total ou en Moyenne215832022852391516917281236645110.22%202378417.6048841321072901451830911566.56%933133232051.5100001192224
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
1Laurent BrossoitCrunch (TB.)98010.8993.545422032316168000.0000915000
2Jon GilliesLightning64200.9013.34359002020297000.000060101
Stats d'équipe Total ou en Moyenne1512210.9003.469022052518265000.00001515101


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Anders BjorkCrunch (TB.)LW/RW211996-08-05No186 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm925,000$0$0$NoLien
Andrei MironovCrunch (TB.)D231994-07-29No194 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Brad HuntCrunch (TB.)D291988-08-24No187 Lbs5 ft9NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Gabriel BourqueCrunch (TB.)LW271990-09-23No206 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm950,000$0$0$NoLien
Laurent BrossoitCrunch (TB.)G241993-03-23No204 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Mark BarberioCrunch (TB.)D271990-03-23No207 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm1,450,000$0$0$NoLien
Michael AmadioCrunch (TB.)C211996-05-13No204 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Samuel MontembeaultCrunch (TB.)G201996-10-30Yes192 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Sebastian D AhoCrunch (TB.)D211996-02-17No170 Lbs5 ft10NoNoNo2Contrat d'EntréePro & Farm770,000$0$0$NoLien
Zane McIntyreCrunch (TB.)G251992-08-20No206 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1023.80196 Lbs6 ft11.30859,500$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Gabriel BourqueMichael AmadioAnders Bjork40122
230122
320122
4Anders BjorkGabriel BourqueMichael Amadio10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark BarberioBrad Hunt40122
2Sebastian D AhoAndrei Mironov30122
320122
4Mark BarberioBrad Hunt10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Gabriel BourqueMichael AmadioAnders Bjork60122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark BarberioBrad Hunt60122
2Sebastian D AhoAndrei Mironov40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Gabriel BourqueAnders Bjork60122
2Michael Amadio40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark BarberioBrad Hunt60122
2Sebastian D AhoAndrei Mironov40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Gabriel Bourque60122Mark BarberioBrad Hunt60122
2Anders Bjork40122Sebastian D AhoAndrei Mironov40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Gabriel BourqueAnders Bjork60122
2Michael Amadio40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark BarberioBrad Hunt60122
2Sebastian D AhoAndrei Mironov40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Gabriel BourqueMichael AmadioAnders BjorkMark BarberioBrad Hunt
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Gabriel BourqueMichael AmadioAnders BjorkMark BarberioBrad Hunt
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Amadio, Gabriel Bourque, Anders BjorkMichael Amadio, Gabriel BourqueAnders Bjork
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Sebastian D Aho, Andrei Mironov, Mark BarberioSebastian D AhoAndrei Mironov, Mark Barberio
Tirs de Pénalité
Gabriel Bourque, Anders Bjork, Michael Amadio, ,
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
LigueDomicileVisiteur
# 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
1Admirals201010001016-61010000018-71000100098120.500101727003713210727548564461897023243510440.00%12741.67%0513104848.95%496105646.97%610128647.43%12667401360536984482
2Barracuda1010000026-41010000026-40000000000000.00024600371321072204856446189244695120.00%330.00%0513104848.95%496105646.97%610128647.43%12667401360536984482
3Bears53200000282262110000011101321000001712560.600285482003713210721234856446189117464862251248.00%24675.00%1513104848.95%496105646.97%610128647.43%12667401360536984482
4Blacknight22000000154111100000012391100000031241.0001526410037132107282485644618940151432131076.92%70100.00%0513104848.95%496105646.97%610128647.43%12667401360536984482
5Bruins522001002428-4320001001612420200000816-850.500244670003713210721104856446189133435269231460.87%261350.00%1513104848.95%496105646.97%610128647.43%12667401360536984482
6Condors20200000510-51010000026-41010000034-100.000591400371321072354856446189732020288112.50%10370.00%0513104848.95%496105646.97%610128647.43%12667401360536984482
7Devils20200000516-110000000000020200000516-1100.000591400371321072614856446189983126265360.00%13838.46%0513104848.95%496105646.97%610128647.43%12667401360536984482
8Gulls2100010012841000010067-11100000061530.750122335003713210726948564461895118103212758.33%5180.00%0513104848.95%496105646.97%610128647.43%12667401360536984482
9Icedogs3120000021192202000001116-511000000103720.3332138590037132107292485644618985302840161062.50%14564.29%0513104848.95%496105646.97%610128647.43%12667401360536984482
10Marlies404000001124-1320200000610-420200000514-900.00011223300371321072135485644618915458324514214.29%16943.75%0513104848.95%496105646.97%610128647.43%12667401360536984482
11Monsters2200000010642200000010640000000000041.00010192900371321072414856446189438122510330.00%6183.33%0513104848.95%496105646.97%610128647.43%12667401360536984482
12Moose20200000617-111010000038-51010000039-600.000611170037132107258485644618982242214500.00%11736.36%0513104848.95%496105646.97%610128647.43%12667401360536984482
13Penguins312000001317-421100000121111010000016-520.33313233600371321072103485644618910443274411327.27%11372.73%0513104848.95%496105646.97%610128647.43%12667401360536984482
14Phantoms211000001516-1211000001516-10000000000020.50015284310371321072764856446189832918449444.44%9544.44%1513104848.95%496105646.97%610128647.43%12667401360536984482
15Rampages1010000026-41010000026-40000000000000.0002460037132107217485644618953121414300.00%7357.14%0513104848.95%496105646.97%610128647.43%12667401360536984482
16Reigh211000008621010000034-11100000052320.5008142200371321072784856446189521812409555.56%60100.00%0513104848.95%496105646.97%610128647.43%12667401360536984482
17Rocket641010003525103300000020911311010001516-1100.8333565100003713210721514856446189168594880221150.00%24962.50%0513104848.95%496105646.97%610128647.43%12667401360536984482
18Senateurs40300100629-2310100000111-1030200100518-1310.125611170037132107210948564461891675534411417.14%171229.41%0513104848.95%496105646.97%610128647.43%12667401360536984482
19Sound Tigers42100100332112201001001416-2220000001951450.625336093003713210721594856446189185682664211466.67%13746.15%1513104848.95%496105646.97%610128647.43%12667401360536984482
20Stars20200000617-111010000038-51010000039-600.0006111700371321072664856446189943218324125.00%9722.22%1513104848.95%496105646.97%610128647.43%12667401360536984482
21Thunderbird20200000114-131010000013-210100000011-1100.0001230037132107235485644618982262925400.00%12741.67%0513104848.95%496105646.97%610128647.43%12667401360536984482
Total60223202400278332-5432121700300157178-2128101502100121154-33520.4332785157931037132107217564856446189201068152883025010943.60%25911854.44%5513104848.95%496105646.97%610128647.43%12667401360536984482
23Wolves220000001055110000006241100000043141.0001019290037132107261485644618952198297342.86%4250.00%0513104848.95%496105646.97%610128647.43%12667401360536984482
_Since Last GM Reset60223202400278332-5432121700300157178-2128101502100121154-33520.4332785157931037132107217564856446189201068152883025010943.60%25911854.44%5513104848.95%496105646.97%610128647.43%12667401360536984482
_Vs Conference39152001300181218-3720108002001061042195120110075114-39350.449181339520103713210721103485644618913344663525251586742.41%1718053.22%4513104848.95%496105646.97%610128647.43%12667401360536984482
_Vs Division216120120077120-431054001004445-11118011003375-42160.38177146223003713210725404856446189704241195260772836.36%955047.37%1513104848.95%496105646.97%610128647.43%12667401360536984482

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
6052L22785157931756201068152883010
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6022322400278332
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3212170300157178
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2810152100121154
Derniers 10 Matchs
WLOTWOTL SOWSOL
631000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
25010943.60%25911854.44%5
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
4856446189371321072
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
513104848.95%496105646.97%610128647.43%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12667401360536984482


Derniers Match 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
3 - 2018-10-118Crunch0Thunderbird11LSommaire du Match
6 - 2018-10-1421Bruins4Crunch7WSommaire du Match
10 - 2018-10-1834Senateurs11Crunch1LSommaire du Match
13 - 2018-10-2144Crunch3Marlies11LSommaire du Match
16 - 2018-10-2453Crunch4Bruins6LSommaire du Match
18 - 2018-10-2659Crunch7Bears5WSommaire du Match
19 - 2018-10-2767Marlies5Crunch3LSommaire du Match
22 - 2018-10-3084Crunch2Senateurs8LSommaire du Match
25 - 2018-11-0293Icedogs8Crunch5LSommaire du Match
28 - 2018-11-05111Rocket3Crunch10WSommaire du Match
30 - 2018-11-07120Crunch6Rocket5WXSommaire du Match
32 - 2018-11-09134Phantoms8Crunch6LSommaire du Match
36 - 2018-11-13153Thunderbird3Crunch1LSommaire du Match
38 - 2018-11-15162Crunch3Rocket7LSommaire du Match
41 - 2018-11-18175Rocket2Crunch5WSommaire du Match
47 - 2018-11-24195Monsters2Crunch4WSommaire du Match
52 - 2018-11-29218Condors6Crunch2LSommaire du Match
57 - 2018-12-04235Crunch1Devils9LSommaire du Match
60 - 2018-12-07243Penguins5Crunch2LSommaire du Match
63 - 2018-12-10256Crunch6Bears1WSommaire du Match
66 - 2018-12-13266Admirals8Crunch1LSommaire du Match
69 - 2018-12-16277Crunch4Wolves3WSommaire du Match
71 - 2018-12-18290Rocket4Crunch5WSommaire du Match
76 - 2018-12-23313Moose8Crunch3LSommaire du Match
80 - 2018-12-27330Crunch1Penguins6LSommaire du Match
81 - 2018-12-28335Bears4Crunch3LSommaire du Match
87 - 2019-01-03361Monsters4Crunch6WSommaire du Match
89 - 2019-01-05376Crunch3Condors4LSommaire du Match
90 - 2019-01-06382Gulls7Crunch6LXSommaire du Match
94 - 2019-01-10393Crunch4Bruins10LSommaire du Match
97 - 2019-01-13409Bears6Crunch8WSommaire du Match
103 - 2019-01-19433Bruins6Crunch5LXSommaire du Match
106 - 2019-01-22443Crunch3Stars9LSommaire du Match
109 - 2019-01-25457Marlies5Crunch3LSommaire du Match
111 - 2019-01-27470Crunch3Moose9LSommaire du Match
115 - 2019-01-31481Rampages6Crunch2LSommaire du Match
117 - 2019-02-02491Crunch2Senateurs3LXSommaire du Match
119 - 2019-02-04499Crunch4Bears6LSommaire du Match
120 - 2019-02-05505Icedogs8Crunch6LSommaire du Match
128 - 2019-02-13529Barracuda6Crunch2LSommaire du Match
131 - 2019-02-16550Stars8Crunch3LSommaire du Match
133 - 2019-02-18559Crunch2Marlies3LSommaire du Match
137 - 2019-02-22576Crunch4Devils7LSommaire du Match
138 - 2019-02-23580Blacknight3Crunch12WSommaire du Match
141 - 2019-02-26595Crunch3Blacknight1WSommaire du Match
143 - 2019-02-28601Bruins2Crunch4WSommaire du Match
146 - 2019-03-03616Crunch6Rocket4WSommaire du Match
148 - 2019-03-05625Sound Tigers5Crunch4LXSommaire du Match
150 - 2019-03-07636Crunch5Reigh2WSommaire du Match
152 - 2019-03-09649Wolves2Crunch6WSommaire du Match
154 - 2019-03-11658Crunch10Sound Tigers3WSommaire du Match
156 - 2019-03-13670Crunch10Icedogs3WSommaire du Match
157 - 2019-03-14673Penguins6Crunch10WSommaire du Match
160 - 2019-03-17681Crunch9Sound Tigers2WSommaire du Match
162 - 2019-03-19690Crunch6Gulls1WSommaire du Match
163 - 2019-03-20698Phantoms8Crunch9WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
168 - 2019-03-25720Sound Tigers11Crunch10LSommaire du Match
171 - 2019-03-28729Crunch9Admirals8WXSommaire du Match
173 - 2019-03-30739Crunch1Senateurs7LSommaire du Match
176 - 2019-04-02746Reigh4Crunch3LSommaire du Match
182 - 2019-04-08769Senateurs-Crunch-
186 - 2019-04-12784Crunch-Gulls-
188 - 2019-04-14794Heat-Crunch-
190 - 2019-04-16801Crunch-Heat-
192 - 2019-04-18812Crunch-Phantoms-
194 - 2019-04-20818Senateurs-Crunch-
197 - 2019-04-23830Crunch-Phantoms-
200 - 2019-04-26841Marlies-Crunch-
202 - 2019-04-28850Crunch-Bruins-
204 - 2019-04-30859Crunch-Penguins-
206 - 2019-05-02869Icedogs-Crunch-
213 - 2019-05-09891Thunderbird-Crunch-
214 - 2019-05-10901Crunch-Monsters-
218 - 2019-05-14914Crunch-Thunderbird-
219 - 2019-05-15920Devils-Crunch-
222 - 2019-05-18935Crunch-Rampages-
223 - 2019-05-19940Devils-Crunch-
225 - 2019-05-21945Crunch-Monsters-
226 - 2019-05-22951Crunch-Barracuda-
230 - 2019-05-26961Crunch-Thunderbird-
232 - 2019-05-28968Thunderbird-Crunch-
233 - 2019-05-29971Crunch-Marlies-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
9 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,402,895$ 859,500$ 859,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 491,555$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 57 8,690$ 495,330$




LigueDomicileVisiteur
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
260223202400278332-5432121700300157178-2128101502100121154-33522785157931037132107217564856446189201068152883025010943.60%25911854.44%5513104848.95%496105646.97%610128647.43%12667401360536984482
Total Saison Régulière60223202400278332-5432121700300157178-2128101502100121154-33522785157931037132107217564856446189201068152883025010943.60%25911854.44%5513104848.95%496105646.97%610128647.43%12667401360536984482