Crunch

GP: 4 | W: 1 | L: 3 | OTL: 0 | P: 2
GF: 6 | GA: 8 | PP%: 23.53% | PK%: 81.82%
DG: Stéphane Lacasse | Morale : 47 | Moyenne d'Équipe : 63
Prochain matchs #85 vs Comets
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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
1Byron FroeseX100.006238856378939161746059725875785748650
2Dmitrij JaskinX100.009036896684767264526358656271667848640
3Tyler GraovacX100.007437876291928961655960636171665948640
4Nicolas DeslauriersXX100.009645726582666164586163715975685348640
5Francis PerronX100.005237896268928960686257565965636448610
6Mario KempeX100.007938886071706759725658645979715048610
7Nathan BastianX100.007249816087836959525664585963627448610
8Matt PuempelX100.005836906278807060585961575871667748610
9Reid BoucherX100.005435936369766962696161596371665948610
10Austin CzarnikXX100.005136936163696759636558576073703748590
11Chase De LeoX100.005135945965847158636057615567645848590
12Mason Shaw (R)X100.005037875766959656635852535461636448590
13Henrik SamuelssonX100.007339835487837753595351585369657748580
14Michael Del ZottoX100.009337816775825565307361725477696648680
15Maxime LajoieX100.005438896674857164306663695763625848640
16Kevin CzuczmanX100.006739825682928954305651574575685748620
17Duncan SiemensX100.007141765385888252305451594871667748620
18Brandon CrawleyX100.006545665678898354305552594563626348610
19Joni Tuulola (R)X100.006736915583908454305451564565636248610
Rayé
1Kevin PorterX100.005838866072918759706254565782795246620
2Colin GreeningX100.006835945482928853565351565282735246590
3Spencer WatsonX100.005135935556726853565451565365636246550
4Juuso RiikolaX100.007336916372756962306558625470675346630
MOYENNE D'ÉQUIPE100.00663886607683775953595761557167614861
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
1Adin Hill100.00808179937978807978807965696748770
2Oscar Dansk100.00787775827776787776787769735148740
Rayé
1Kaden Fulcher100.00646563776362646362646361654946630
MOYENNE D'ÉQUIPE100.0074747284737274737274736569564771
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Van Ryn60706565595586CAN3951,000,000$


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
1Tyler GraovacCrunch (Tam)C4224-12055137315.38%18421.052245110001220070.83%7200000.9500000000
2Duncan SiemensCrunch (Tam)D4123-1807430433.33%78621.57123211000016000.00%000000.7000000000
3Mario KempeCrunch (Tam)RW4112-10074165146.25%16817.12112410000211000.00%100000.5800000000
4Matt PuempelCrunch (Tam)LW4022-1001713280.00%05814.53022311000000066.67%300000.6900000000
5Reid BoucherCrunch (Tam)C42021003990522.22%04511.2500000000001062.22%4500000.8900000100
6Mason ShawCrunch (Tam)LW4022100154140.00%14411.0900000000000066.67%300000.9000000001
7Nathan BastianCrunch (Tam)RW4011180357460.00%14511.43000010000000100.00%200000.4400000000
8Kevin CzuczmanCrunch (Tam)D4011-140120110.00%88822.07011011000019000.00%000000.2300000000
9Joni TuulolaCrunch (Tam)D4011020343210.00%15413.580000000000000.00%000000.3700000000
10Austin CzarnikCrunch (Tam)C/RW4000000017130.00%0266.5700000000000066.67%300000.0000000000
11Chase De LeoCrunch (Tam)C4000020013010.00%0307.7200000000050055.56%3600000.0000000000
12Byron FroeseCrunch (Tam)C4000-20011518470.00%09724.400003140001230068.70%13100000.0000000000
13Francis PerronCrunch (Tam)LW4000-2000511240.00%17117.81000415000010050.00%800000.0000000000
14Dmitrij JaskinCrunch (Tam)RW4000-28011913760.00%17919.78000214000090050.00%1000000.0000000000
15Maxime LajoieCrunch (Tam)D4000-100086750.00%59724.33000414000118000.00%000000.0000000000
16Brandon CrawleyCrunch (Tam)D4000040623010.00%05914.850000000005000.00%000000.0000000000
17Henrik SamuelssonCrunch (Tam)LW4000040510210.00%0256.3700000000000066.67%300000.0000000000
18Michael Del ZottoCrunch (Tam)D4000-1605481110.00%49423.56000514000014000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne7261218-10480599113746854.38%31115616.0648123213100051491065.62%31700000.3100000101
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
1Adin HillCrunch (Tam)41300.9161.77238017830010.000040010
Stats d'équipe Total ou en Moyenne41300.9161.77238017830010.000040010


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
Adin HillCrunch (Tam)G231996-05-11No202 Lbs6 ft6NoNoNo2Avec RestrictionPro & Farm500,000$0$0$NoLien
Austin CzarnikCrunch (Tam)C/RW261992-12-12No170 Lbs5 ft9NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Brandon CrawleyCrunch (Tam)D221997-02-02No204 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Byron FroeseCrunch (Tam)C281991-03-12No202 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm400,000$0$0$NoLien
Chase De LeoCrunch (Tam)C231995-10-25No179 Lbs5 ft9NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Colin GreeningCrunch (Tam)C331986-03-09No210 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm300,000$0$0$NoLien
Dmitrij JaskinCrunch (Tam)RW261993-03-23No216 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm500,000$0$0$NoLien
Duncan SiemensCrunch (Tam)D251993-09-07No210 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Francis PerronCrunch (Tam)LW231996-04-18No166 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Henrik SamuelssonCrunch (Tam)LW251994-02-07No219 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Joni TuulolaCrunch (Tam)D231996-01-01Yes198 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Juuso RiikolaCrunch (Tam)D251993-11-09No189 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Kaden FulcherCrunch (Tam)G201998-09-23No182 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Kevin CzuczmanCrunch (Tam)D281991-01-09No206 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Kevin PorterCrunch (Tam)C331986-03-12No190 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm300,000$0$0$NoLien
Mario KempeCrunch (Tam)RW301988-09-19No185 Lbs6 ft0NoNoNo4Sans RestrictionPro & Farm300,000$0$0$NoLien
Mason ShawCrunch (Tam)LW201998-11-03Yes182 Lbs5 ft9NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Matt PuempelCrunch (Tam)LW261993-01-24No205 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Maxime LajoieCrunch (Tam)D211997-11-05No183 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Michael Del ZottoCrunch (Tam)D291990-06-24No201 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm2,500,000$0$0$NoLien
Nathan BastianCrunch (Tam)RW211997-12-06No205 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Nicolas DeslauriersCrunch (Tam)LW/RW281991-02-22No221 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm903,386$0$0$NoLien
Oscar DanskCrunch (Tam)G251994-02-28No195 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm500,000$0$0$NoLien
Reid BoucherCrunch (Tam)C251993-09-08No195 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Spencer WatsonCrunch (Tam)RW231996-04-25No170 Lbs5 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Tyler GraovacCrunch (Tam)C261993-04-27No208 Lbs6 ft5NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2625.27196 Lbs6 ft12.62457,823$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Francis PerronByron FroeseDmitrij Jaskin40122
2Matt PuempelTyler GraovacMario Kempe30122
3Mason ShawReid BoucherNathan Bastian20122
4Henrik SamuelssonChase De LeoAustin Czarnik10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael Del ZottoMaxime Lajoie40122
2Kevin CzuczmanDuncan Siemens30122
3Joni TuulolaBrandon Crawley20122
4Michael Del ZottoMaxime Lajoie10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Francis PerronByron FroeseDmitrij Jaskin60122
2Matt PuempelTyler GraovacMario Kempe40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael Del ZottoMaxime Lajoie60122
2Kevin CzuczmanDuncan Siemens40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Byron FroeseTyler Graovac60122
2Dmitrij JaskinMario Kempe40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael Del ZottoMaxime Lajoie60122
2Kevin CzuczmanDuncan Siemens40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Byron Froese60122Michael Del ZottoMaxime Lajoie60122
2Tyler Graovac40122Kevin CzuczmanDuncan Siemens40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Byron FroeseTyler Graovac60122
2Dmitrij JaskinMario Kempe40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael Del ZottoMaxime Lajoie60122
2Kevin CzuczmanDuncan Siemens40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Francis PerronByron FroeseDmitrij JaskinMichael Del ZottoMaxime Lajoie
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Francis PerronByron FroeseDmitrij JaskinMichael Del ZottoMaxime Lajoie
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nathan Bastian, Reid Boucher, Chase De LeoNathan Bastian, Reid BoucherChase De Leo
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joni Tuulola, Brandon Crawley, Kevin CzuczmanJoni TuulolaBrandon Crawley, Kevin Czuczman
Tirs de Pénalité
Byron Froese, Tyler Graovac, Dmitrij Jaskin, Mario Kempe, Nathan Bastian
Gardien
#1 : Adin Hill, #2 : Oscar Dansk


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
1Americans1010000013-2000000000001010000013-200.00012300411024514442031820212150.00%8362.50%010114768.71%7011660.34%375468.52%1168679264423
2Bears1010000012-1000000000001010000012-100.000123004110265144420216101411100.00%5180.00%010114768.71%7011660.34%375468.52%1168679264423
3Checkers11000000303110000003030000000000021.0003690141105851444201554116116.67%20100.00%010114768.71%7011660.34%375468.52%1168679264423
4Devils1010000013-2000000000001010000013-200.000123104110295144420171214138112.50%70100.00%010114768.71%7011660.34%375468.52%1168679264423
Total4130000068-2110000003033030000038-520.2506121811411013751444208431485917423.53%22481.82%010114768.71%7011660.34%375468.52%1168679264423
_Since Last GM Reset4130000068-2110000003033030000038-520.2506121811411013751444208431485917423.53%22481.82%010114768.71%7011660.34%375468.52%1168679264423
_Vs Conference2020000025-3000000000002020000025-300.000246104110555144420381824279222.22%12191.67%010114768.71%7011660.34%375468.52%1168679264423
_Vs Division30100000550100000003032010000025-300.0005101511411011351444205323283815320.00%14192.86%010114768.71%7011660.34%375468.52%1168679264423

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
42L1612181378431485911
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
413000068
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
110000030
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
303000038
Derniers 10 Matchs
WLOTWOTL SOWSOL
130000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
17423.53%22481.82%0
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
51444204110
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
10114768.71%7011660.34%375468.52%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1168679264423


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
4 - 2019-09-0511Crunch1Bears2LSommaire du Match
8 - 2019-09-0930Crunch1Americans3LSommaire du Match
11 - 2019-09-1246Checkers0Crunch3WSommaire du Match
17 - 2019-09-1875Crunch1Devils3LSommaire du Match
18 - 2019-09-1985Comets-Crunch-
24 - 2019-09-25107Crunch-Marlies-
25 - 2019-09-26119Checkers-Crunch-
31 - 2019-10-02140Senators-Crunch-
32 - 2019-10-03157Senators-Crunch-
38 - 2019-10-09187Crunch-Americans-
40 - 2019-10-11209Bears-Crunch-
43 - 2019-10-14217Devils-Crunch-
45 - 2019-10-16224Crunch-Comets-
46 - 2019-10-17239Rocket-Crunch-
50 - 2019-10-21260Crunch-Devils-
52 - 2019-10-23265Devils-Crunch-
53 - 2019-10-24283Crunch-Thunderbirds-
59 - 2019-10-30308Crunch-Monsters-
60 - 2019-10-31318Crunch-Monsters-
66 - 2019-11-06350Devils-Crunch-
67 - 2019-11-07366Americans-Crunch-
71 - 2019-11-11384Crunch-Marlies-
73 - 2019-11-13396Crunch-Rocket-
74 - 2019-11-14401Crunch-Rocket-
78 - 2019-11-18429Crunch-Thunderbirds-
80 - 2019-11-20439Crunch-Phantoms-
81 - 2019-11-21457Penguins-Crunch-
85 - 2019-11-25468Crunch-Devils-
87 - 2019-11-27476Comets-Crunch-
88 - 2019-11-28489Thunderbirds-Crunch-
92 - 2019-12-02511Crunch-Comets-
94 - 2019-12-04518Sound Tigers-Crunch-
95 - 2019-12-05535Marlies-Crunch-
99 - 2019-12-09554Crunch-Devils-
101 - 2019-12-11563Monsters-Crunch-
102 - 2019-12-12577Crunch-Comets-
106 - 2019-12-16596Crunch-Comets-
108 - 2019-12-18605Senators-Crunch-
109 - 2019-12-19626Crunch-Devils-
111 - 2019-12-21636Devils-Crunch-
115 - 2019-12-25655Thunderbirds-Crunch-
116 - 2019-12-26673Americans-Crunch-
122 - 2020-01-01685Comets-Crunch-
123 - 2020-01-02702Monsters-Crunch-
127 - 2020-01-06719Crunch-Americans-
129 - 2020-01-08726Crunch-Wolf Pack-
131 - 2020-01-10752Crunch-Bruins-
134 - 2020-01-13765Crunch-Senators-
136 - 2020-01-15774Crunch-Americans-
137 - 2020-01-16782Americans-Crunch-
139 - 2020-01-18805Crunch-Marlies-
141 - 2020-01-20809Rocket-Crunch-
143 - 2020-01-22817Marlies-Crunch-
144 - 2020-01-23832Marlies-Crunch-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29856Phantoms-Crunch-
151 - 2020-01-30871Americans-Crunch-
152 - 2020-01-31884Crunch-Americans-
155 - 2020-02-03890Crunch-Comets-
157 - 2020-02-05897Comets-Crunch-
158 - 2020-02-06915Crunch-Penguins-
162 - 2020-02-10939Crunch-Rocket-
164 - 2020-02-12943Wolf Pack-Crunch-
165 - 2020-02-13958Devils-Crunch-
168 - 2020-02-16973Crunch-Checkers-
169 - 2020-02-17978Crunch-Checkers-
172 - 2020-02-20997Comets-Crunch-
173 - 2020-02-211013Crunch-Sound Tigers-
176 - 2020-02-241019Crunch-Senators-
178 - 2020-02-261027Bruins-Crunch-
179 - 2020-02-271043Comets-Crunch-
183 - 2020-03-021064Crunch-Senators-
185 - 2020-03-041077Crunch-Americans-
186 - 2020-03-051089Americans-Crunch-
192 - 2020-03-111117Rocket-Crunch-
193 - 2020-03-121130Americans-Crunch-
194 - 2020-03-131147Crunch-Comets-



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
37 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
98,056$ 119,034$ 27,930$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 10,438$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 177 5,768$ 1,020,936$




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
144130000068-2110000003033030000038-526121811411013751444208431485917423.53%22481.82%010114768.71%7011660.34%375468.52%1168679264423
Total Saison Régulière4130000068-2110000003033030000038-526121811411013751444208431485917423.53%22481.82%010114768.71%7011660.34%375468.52%1168679264423