Please rotate your device to landscape mode for a better experience.
Connexion

Cleveland
GP: 79 | W: 39 | L: 32 | OTL: 8 | P: 86
GF: 221 | GA: 256 | PP%: 17.13% | PK%: 81.66%
DG: Dany Bourdeau | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #1006 vs Lehigh Valley

Centre de jeu
Cleveland
39-32-8, 86pts
5
3 Utica
12-63-6, 30pts
Team Stats
L1SéquenceL4
19-17-4Fiche domicile6-31-3
20-15-4Fiche domicile6-32-3
7-2-1Derniers 10 matchs1-9-0
2.80Buts par match 2.23
3.24Buts contre par match 5.05
17.13%Pourcentage en avantage numérique16.08%
81.66%Pourcentage en désavantage numérique71.54%
Cleveland
39-32-8, 86pts
3
6 Charlotte
57-15-8, 122pts
Team Stats
L1SéquenceW2
19-17-4Fiche domicile33-4-3
20-15-4Fiche domicile24-11-5
7-2-1Derniers 10 matchs7-2-1
2.80Buts par match 3.86
3.24Buts contre par match 2.65
17.13%Pourcentage en avantage numérique21.24%
81.66%Pourcentage en désavantage numérique83.64%
Lehigh Valley
46-26-6, 98pts
Jour 191
Cleveland
39-32-8, 86pts
Statistiques d’équipe
W1SéquenceL1
24-11-5Fiche domicile19-17-4
22-15-1Fiche visiteur20-15-4
3-6-110 derniers matchs7-2-1
3.36Buts par match 2.80
2.73Buts contre par match 2.80
19.28%Pourcentage en avantage numérique17.13%
83.33%Pourcentage en désavantage numérique81.66%
Cleveland
39-32-8, 86pts
Jour 192
San Jose
40-32-8, 88pts
Statistiques d’équipe
L1SéquenceL1
19-17-4Fiche domicile20-16-4
20-15-4Fiche visiteur20-16-4
7-2-110 derniers matchs5-5-0
2.80Buts par match 3.35
3.24Buts contre par match 3.35
17.13%Pourcentage en avantage numérique19.29%
81.66%Pourcentage en désavantage numérique79.61%
Cleveland
39-32-8, 86pts
Jour 193
Charlotte
57-15-8, 122pts
Statistiques d’équipe
L1SéquenceW2
19-17-4Fiche domicile33-4-3
20-15-4Fiche visiteur24-11-5
7-2-110 derniers matchs7-2-1
2.80Buts par match 3.86
3.24Buts contre par match 3.86
17.13%Pourcentage en avantage numérique21.24%
81.66%Pourcentage en désavantage numérique83.64%
Meneurs d'équipe
Buts
Colin Wilson
23
Dylan SambergPasses
Dylan Samberg
45
Points
Matthew Benning
55
Chris WagnerPlus/Moins
Chris Wagner
11
Victoires
Joseph Woll
20
Pourcentage d’arrêts
Joseph Woll
0.92

Statistiques d’équipe
Buts pour
221
2.80 GFG
Tirs pour
2690
34.05 Avg
Pourcentage en avantage numérique
17.1%
49 GF
Début de zone offensive
41.1%
Buts contre
256
3.24 GAA
Tirs contre
2809
35.56 Avg
Pourcentage en désavantage numérique
81.7%%
73 GA
Début de la zone défensive
41.9%
Informations de l'équipe

Directeur généralDany Bourdeau
EntraîneurAndre Tourigny
DivisionAtlantique
ConférenceConference est
CapitaineRyan Kesler
Assistant #1Jeff Petry
Assistant #2Dustin Brown


Informations de l’aréna

Capacité3,000
Assistance2,441
Billets de saison300


Informations de la formation

Équipe Pro20
Équipe Mineure19
Limite contact 39 / 50
Espoirs23


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
1Cory ConacherXX100.00673394727269796953677060727064245000342800,000$
2Derick BrassardXXX97.006632925976668472747169667889662150003621,210,000$
3Chris WagnerX100.00782876677771846770656868757673235000332850,000$
4Ryan Kesler (C)XX95.009230624575729373997171718399991750003911,500,000$
5Tomas TatarXX100.00693388736982977470697155887158395000332900,000$
6Jordan MartinookXXX100.006317956581779064836367728562563150003111,000,000$
7Frank VatranoXX100.007738827479809469726674588362634850003011,100,000$
8Nick CousinsXXX100.006531807477758766736665578561493550003021,000,000$
9Dustin Brown (A)XX99.00682085577771997169736765838999205000391951,000$
10Oscar LindbergXXX100.00672989718071957086676963776556295000322900,000$
11Colin WilsonXXX99.006722947078699072826672668374672750003421,100,000$
12Jeff Petry (A)X97.008133666381789668256760875182702950003631,200,000$
13Michael StoneX100.00674561588278985350505285567460355000342950,000$
14Dylan Samberg (R)X100.00743281809083995372564697774849665000251800,000$
15Andreas EnglundX100.00887662718876994470464486755958515000273825,000$
16Brenden DillonX100.009457606990849754505455917578743650003321,300,000$
17Matthew BenningX100.007336527577859159535855907460504250003011,000,000$
Rayé
MOYENNE D’ÉQUIPE99.2474357867797692656863637376726534500
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
1Adin Hill100.0067878482758485868582795656645000281925,000$
2Chad Johnson100.005690828170817982837773969575000382500,000$
3Joseph Woll (R)98.0067928682768886908979705252725000251700,000$
Rayé
MOYENNE D’ÉQUIPE99.336390848274848386867974686848500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Andre Tourigny78748596928875CAN5122,500,000$


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
1Matthew BenningCleveland (CLB)D7916395581061014310017441999.20%126170021.5210132394246000329111100.00%100000.6500011122
2Ryan KeslerCleveland (CLB)C/RW70183250211602431701573311911.46%13150721.5339122620810152474161.04%220200100.6623000424
3Dylan SambergCleveland (CLB)D73445496380467212545963.20%137165222.6411920712300001297100%000000.5900000111
4Jeff PetryCleveland (CLB)D79113445367551101168711146.55%125189023.936410982260110290200%000200.4801000041
5Colin WilsonCleveland (CLB)C/LW/RW76232245-6220611262236117110.31%14153320.1859144022610182907152.92%154200000.5911000231
6Tomas TatarCleveland (CLB)LW/RW79182442-43809347243581387.41%1128316.24781557243000004144.66%10300000.6500000341
7Brenden DillonCleveland (CLB)D79132437-62266019987165481197.88%128180822.896511812230002251200%000000.4101237111
8Derick BrassardCleveland (CLB)C/LW/RW78122335-61806969201351505.97%14131816.904711362320001522152.24%42500000.5311000232
9Chris WagnerCleveland (CLB)RW791716331172012652191381278.90%11109413.85123554000054251.40%10700010.6000000324
10Dustin BrownCleveland (CLB)LW/RW669223121002554146321126.16%6142321.563253219200062630150.26%19500000.4412000001
11Oscar LindbergCleveland (CLB)C/LW/RW7892231-91402798136441226.62%9105213.49000040004731054.60%126000000.5900000102
12Frank VatranoCleveland (CLB)LW/RW75141024-7420774914743999.52%795612.7500029000082248.84%8600000.5000000124
13Andreas EnglundCleveland (CLB)D7981624-21163351666042133619.05%82114114.450001140000291260.00%500100.4200205011
14Jordan MartinookCleveland (CLB)C/LW/RW7971421-460175167236610.45%35366.7901101000120153.73%59000000.7800000200
15Michael StoneCleveland (CLB)D7941620-1631539406112366.56%106121315.37000230002129100%000000.3300001000
16Cory ConacherCleveland (CLB)LW/RW797613-14135304110037847.00%684010.64000010001211145.62%21700000.3100100200
17Noah GregorColumbusLW/RW101121356022284817412.08%224724.760228350000380157.75%14200001.0502000100
18Nick CousinsCleveland (CLB)C/LW/RW793811-816032196017575.00%05086.4400000000000151.95%7700000.4300000001
Statistiques d’équipe totales ou en moyenne1316194385579-64100412014661264245466817867.91%7902170916.5046811275532155213342294331655.42%695200410.535115414242526
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
1Joseph WollCleveland (CLB)34201040.9202.851961019311600100.636113411851
2Adin HillCleveland (CLB)40191720.9103.0323156111712940201.00033832334
3Chad JohnsonCleveland (CLB)20000.9502.11570024000000029000
Statistiques d’équipe totales ou en moyenne76392760.9152.9443346221224940301472721185


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Adin HillCleveland (CLB)G281996-05-11CANNo204 Lbs6 ft6NoNoN/ANoNo12024-09-14FalseFalsePro & Farm925,000$33,205$0$0$No---------------------------Lien / Lien NHL
Andreas EnglundCleveland (CLB)D271996-09-21SWENo200 Lbs6 ft4NoNoN/ANoNo32025-09-09FalseFalsePro & Farm825,000$29,615$0$0$No825,000$825,000$-------825,000$825,000$-------NoNo-------Lien NHL
Brenden DillonCleveland (CLB)D331990-11-13CANNo225 Lbs6 ft4NoNoFree AgentNoNo22024-10-02FalseFalsePro & Farm1,300,000$46,667$0$0$No1,300,000$--------1,300,000$--------No--------Lien / Lien NHL
Chad JohnsonCleveland (CLB)G381986-06-10CANNo218 Lbs6 ft3NoNoFree AgentNoNo22024-10-08FalseFalsePro & Farm500,000$17,949$0$0$No500,000$--------500,000$--------No--------Lien
Chris WagnerCleveland (CLB)RW331991-05-27USANo197 Lbs6 ft0NoNoFree AgentNoNo22024-09-26FalseFalsePro & Farm850,000$30,513$0$0$No850,000$--------850,000$--------No--------Lien / Lien NHL
Colin WilsonCleveland (CLB)C/LW/RW341989-10-20USANo223 Lbs6 ft1NoNoFree AgentNoNo22024-09-23FalseFalsePro & Farm1,100,000$39,487$0$0$No1,100,000$--------1,100,000$--------No--------Lien
Cory ConacherCleveland (CLB)LW/RW341989-12-14CANNo187 Lbs5 ft8NoNoFree AgentNoNo22025-09-26FalseFalsePro & Farm800,000$28,718$0$0$No800,000$--------800,000$--------No--------Lien
Derick BrassardCleveland (CLB)C/LW/RW361987-09-22CANNo200 Lbs6 ft1NoNoFree AgentNoNo22024-09-24FalseFalsePro & Farm1,210,000$43,436$0$0$No1,210,000$--------1,210,000$--------No--------
Dustin BrownCleveland (CLB)LW/RW391984-11-04USANo206 Lbs6 ft0NoNoFree AgentNoNo12025-09-23FalseFalsePro & Farm951,000$34,138$0$0$No---------------------------Lien
Dylan SambergCleveland (CLB)D251999-01-24NAYes216 Lbs6 ft4NoNoTrade2024-10-06NoNo1FalseFalsePro & Farm800,000$28,718$0$0$No---------------------------Lien NHL
Frank VatranoCleveland (CLB)LW/RW301994-03-14USANo206 Lbs5 ft9NoNoN/ANoNo12024-09-14FalseFalsePro & Farm1,100,000$39,487$0$0$No---------------------------Lien / Lien NHL
Jeff PetryCleveland (CLB)D361987-12-09USANo207 Lbs6 ft3NoNoFree Agent2025-01-14NoNo32025-09-23FalseFalsePro & Farm1,200,000$43,077$0$0$No1,200,000$1,200,000$-------1,200,000$1,200,000$-------NoNo-------Lien / Lien NHL
Jordan MartinookCleveland (CLB)C/LW/RW311992-07-25CANNo209 Lbs6 ft0NoNoFree AgentNoNo12024-09-26FalseFalsePro & Farm1,000,000$35,897$0$0$No---------------------------Lien / Lien NHL
Joseph WollCleveland (CLB)G251998-07-12USAYes212 Lbs6 ft3NoNoProspectNoNo12025-10-27FalseFalsePro & Farm700,000$25,128$0$0$No---------------------------
Matthew BenningCleveland (CLB)D301994-05-25CANNo208 Lbs6 ft1NoNoN/ANoNo12024-09-14FalseFalsePro & Farm1,000,000$35,897$0$0$No---------------------------Lien
Michael StoneCleveland (CLB)D341990-06-07CANNo218 Lbs6 ft3NoNoFree AgentNoNo22024-10-02FalseFalsePro & Farm950,000$34,103$0$0$No950,000$--------950,000$--------No--------Lien
Nick CousinsCleveland (CLB)C/LW/RW301993-07-20CANNo192 Lbs5 ft10NoNoFree AgentNoNo22024-10-02FalseFalsePro & Farm1,000,000$35,897$0$0$No1,000,000$--------1,000,000$--------No--------Lien / Lien NHL
Oscar LindbergCleveland (CLB)C/LW/RW321991-10-29SWENo201 Lbs6 ft1NoNoFree AgentNoNo22025-09-26FalseFalsePro & Farm900,000$32,308$0$0$No900,000$--------900,000$--------No--------Lien
Ryan KeslerCleveland (CLB)C/RW391984-08-31CANNo207 Lbs6 ft2NoNoFree Agent2025-03-13NoNo12025-09-22FalseFalsePro & Farm1,500,000$53,846$0$0$No---------------------------Lien
Tomas TatarCleveland (CLB)LW/RW331990-12-01SVKNo189 Lbs5 ft10NoNoFree AgentNoNo22025-09-30FalseFalsePro & Farm900,000$32,308$0$0$No900,000$--------900,000$--------No--------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2032.35206 Lbs6 ft11.70975,550$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dustin BrownRyan KeslerColin Wilson35122
2Tomas TatarDerick BrassardChris Wagner30122
3Frank VatranoOscar LindbergCory Conacher25122
4Nick CousinsJordan MartinookRyan Kesler10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brenden DillonJeff Petry35122
2Dylan SambergMatthew Benning30122
3Andreas EnglundMichael Stone25122
4Brenden DillonJeff Petry10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dustin BrownRyan KeslerColin Wilson50122
2Tomas TatarDerick BrassardChris Wagner50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brenden DillonJeff Petry50122
2Dylan SambergMatthew Benning50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Ryan KeslerDustin Brown50122
2Colin WilsonDerick Brassard50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brenden DillonJeff Petry50122
2Dylan SambergMatthew Benning50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Ryan Kesler50122Brenden DillonJeff Petry50122
2Dustin Brown50122Dylan SambergMatthew Benning50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ryan KeslerDustin Brown50122
2Colin WilsonDerick Brassard50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brenden DillonJeff Petry50122
2Dylan SambergMatthew Benning50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dustin BrownRyan KeslerColin WilsonBrenden DillonJeff Petry
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dustin BrownRyan KeslerColin WilsonBrenden DillonJeff Petry
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Frank Vatrano, Oscar Lindberg, Cory ConacherFrank Vatrano, Oscar LindbergCory Conacher
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Andreas Englund, Michael Stone, Dylan SambergAndreas EnglundMichael Stone, Dylan Samberg
Tirs de pénalité
Ryan Kesler, Dustin Brown, Colin Wilson, Derick Brassard, Tomas Tatar
Gardien
#1 : Joseph Woll, #2 : Adin Hill
Lignes d’attaque personnalisées en prolongation
Ryan Kesler, Dustin Brown, Colin Wilson, Derick Brassard, Tomas Tatar, Chris Wagner, Frank Vatrano, Oscar Lindberg, Cory Conacher, Jordan Martinook
Lignes de défense personnalisées en prolongation
Brenden Dillon, Jeff Petry, Dylan Samberg, Matthew Benning, Andreas Englund


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
1Abbotsford20000101810-21000000134-11000010056-120.50081624008059731177889821945478328293810330.00%12283.33%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
2Bakersfield211000009631010000045-11100000051420.50091726008059731194889821945476722162912216.67%7185.71%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
3Bridgeport633000002123-230300000813-5330000001310360.50021385900805973112138898219454717552549232721.88%25676.00%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
4Charlotte40400000817-92020000046-220200000411-700.0008162400805973111348898219454714243568019210.53%22577.27%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
5Coachella Valley21000010743100000103211100000042241.0007111800805973117088982194547802331399333.33%13192.31%11644303654.15%1679310054.16%709125456.54%1874124218636201059530
6Eagles21001000752100010004311100000032141.00071421008059731182889821945476017164313430.77%7271.43%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
7Grand Rapids4400000015105220000009632200000064281.00015223700805973111478898219454713535478218211.11%19573.68%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
8Hartford6220110014131210010007434120010079-270.58314274101805973111848898219454719352781072015.00%27388.89%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
9Hershey40400000623-1720200000310-720200000313-1000.000612180080597311119889821945471655869737228.57%27870.37%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
10Iowa2110000045-11010000014-31100000031220.500481200805973117288982194547592523271000.00%7185.71%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
11Laval40200110821-132010001059-420100100312-930.3758132100805973111368898219454716843636311218.18%27774.07%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
12Lehigh Valley30200100312-91000010023-12020000019-810.167358008059731195889821945471303337539111.11%15566.67%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
13Manitoba311010001293211000008621000100043140.6671222340080597311117889821945478924395212325.00%12191.67%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
14Ontario21100000541110000003121010000023-120.500510150080597311408898219454773231831600.00%9277.78%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
15Providence5220010013121311001008802110000054150.500132538008059731116588982194547199569210218316.67%31583.87%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
16Rochester531010001385220000006243110100076180.80013243701805973111718898219454715239669418211.11%26196.15%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
17Rockford21100000510-5110000004221010000018-720.500581300805973116488982194547671726506233.33%8187.50%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
18San Diego2020000039-61010000014-31010000025-300.0003580080597311648898219454778252639800.00%13284.62%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
19San Jose10001000541100010005410000000000021.000510150080597311388898219454737192714300.00%50100.00%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
20Springfield2020000059-41010000035-21010000024-200.000591400805973116488982194547751226448337.50%13561.54%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
21Syracuse42100100990211000003302100010066050.62591524008059731113688982194547126262971900.00%11190.91%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
22Texas211000007611010000034-11100000042220.500714210080597311688898219454785242636300.00%11372.73%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
23Utica 650010002214843001000149522000000853121.000224062008059731119288982194547226577611716425.00%27388.89%11644303654.15%1679310054.16%709125456.54%1874124218636201059530
24Wilkes-Barre/Scranton411001101213-12010010037-42100001096350.62512183000805973111488898219454714546481009333.33%24387.50%01644303654.15%1679310054.16%709125456.54%1874124218636201059530
Total79303206731221256-3540131704321114124-1039171502410107132-25860.54422139962002805973112690889821945472809799101814762864917.13%3987381.66%21644303654.15%1679310054.16%709125456.54%1874124218636201059530
_Since Last GM Reset79303206731221256-3540131704321114124-1039171502410107132-25860.54422139962002805973112690889821945472809799101814762864917.13%3987381.66%21644303654.15%1679310054.16%709125456.54%1874124218636201059530
_Vs Conference55222203620144175-31271011023107280-8281211013107295-23600.5451442553990280597311184088982194547195654071510341862915.59%2815281.49%11644303654.15%1679310054.16%709125456.54%1874124218636201059530
_Vs Division291112023107898-201446022003746-91576001104152-11310.534781402180180597311951889821945471034298362542931819.35%1452880.69%11644303654.15%1679310054.16%709125456.54%1874124218636201059530

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7986L1221399620269028097991018147602
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7930326731221256
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4013174321114124
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3917152410107132
Derniers 10 matchs
WLOTWOTL SOWSOL
720100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2864917.13%3987381.66%2
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
8898219454780597311
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
1644303654.15%1679310054.16%709125456.54%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1874124218636201059530


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
13Utica 4Cleveland5WXSommaire du match
315Cleveland4Hartford5LXSommaire du match
626Cleveland1Charlotte5LSommaire du match
939Cleveland3Rochester2WXSommaire du match
1249Providence2Cleveland4WSommaire du match
1463Utica 1Cleveland2WSommaire du match
1882Cleveland5Wilkes-Barre/Scranton4WXXSommaire du match
1988Cleveland6Bridgeport5WSommaire du match
2298Bridgeport3Cleveland2LSommaire du match
23107Cleveland0Hartford1LSommaire du match
26121Charlotte3Cleveland2LSommaire du match
30136Grand Rapids3Cleveland4WSommaire du match
32151Cleveland3Rochester4LSommaire du match
35168Hartford2Cleveland3WXSommaire du match
37181Cleveland1Providence3LSommaire du match
39191Bridgeport3Cleveland2LSommaire du match
42210Charlotte3Cleveland2LSommaire du match
46227Cleveland1Rochester0WSommaire du match
48237San Jose4Cleveland5WXSommaire du match
50246Cleveland2Springfield4LSommaire du match
52261Bridgeport7Cleveland4LSommaire du match
55269Cleveland4Manitoba3WXSommaire du match
57284Grand Rapids3Cleveland5WSommaire du match
61304Manitoba5Cleveland4LSommaire du match
63316Cleveland2San Diego5LSommaire du match
67332Ontario1Cleveland3WSommaire du match
69345Cleveland5Bakersfield1WSommaire du match
71356Rockford2Cleveland4WSommaire du match
73366Cleveland1Laval9LSommaire du match
75380Eagles3Cleveland4WXSommaire du match
77389Cleveland2Laval3LXSommaire du match
79406Laval5Cleveland0LSommaire du match
81417Cleveland4Coachella Valley2WSommaire du match
83431Laval4Cleveland5WXXSommaire du match
85442Cleveland1Rockford8LSommaire du match
87455Cleveland4Wilkes-Barre/Scranton2WSommaire du match
88462Coachella Valley2Cleveland3WXXSommaire du match
92480Iowa4Cleveland1LSommaire du match
94491Cleveland3Bridgeport2WSommaire du match
98508Manitoba1Cleveland4WSommaire du match
101528Springfield5Cleveland3LSommaire du match
103539Cleveland2Ontario3LSommaire du match
106553Hartford2Cleveland4WSommaire du match
109571Cleveland4Grand Rapids3WSommaire du match
110579Providence4Cleveland3LSommaire du match
112597Wilkes-Barre/Scranton4Cleveland3LXSommaire du match
114607Cleveland3Eagles2WSommaire du match
116617Cleveland4Bridgeport3WSommaire du match
118629Syracuse2Cleveland1LSommaire du match
119633Cleveland4Syracuse3WSommaire du match
122648Cleveland3Iowa1WSommaire du match
123658Wilkes-Barre/Scranton3Cleveland0LSommaire du match
126672Cleveland4Texas2WSommaire du match
127679Cleveland2Syracuse3LXSommaire du match
129688Hershey4Cleveland1LSommaire du match
132703Abbotsford4Cleveland3LXXSommaire du match
134715Cleveland5Abbotsford6LXSommaire du match
136727Cleveland1Lehigh Valley5LSommaire du match
137736Texas4Cleveland3LSommaire du match
139748Cleveland2Hershey6LSommaire du match
141761Hershey6Cleveland2LSommaire du match
143774Cleveland1Hershey7LSommaire du match
146785Lehigh Valley3Cleveland2LXSommaire du match
149802Cleveland0Lehigh Valley4LSommaire du match
151809San Diego4Cleveland1LSommaire du match
154830Bakersfield5Cleveland4LSommaire du match
156840Cleveland2Grand Rapids1WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
158853Cleveland4Providence1WSommaire du match
160862Syracuse1Cleveland2WSommaire du match
161870Cleveland2Hartford0WSommaire du match
164885Providence2Cleveland1LXSommaire du match
168906Utica 2Cleveland4WSommaire du match
172925Cleveland1Hartford3LSommaire du match
173932Utica 2Cleveland3WSommaire du match
178953Rochester1Cleveland3WSommaire du match
181969Cleveland3Utica 2WSommaire du match
184978Rochester1Cleveland3WSommaire du match
187991Cleveland5Utica 3WSommaire du match
188993Cleveland3Charlotte6LSommaire du match
1911006Lehigh Valley-Cleveland-
1921012Cleveland-San Jose-
1931019Cleveland-Charlotte-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5025
Assistance58,72838,915
Assistance PCT73.41%97.29%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
1 2441 - 81.37% 131,938$5,277,520$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
4,355,276$ 1,951,100$ 1,951,100$ 2,500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,006$ 1,944,966$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
131,938$ 7 22,826$ 159,782$




Cleveland Leaders statistiques des joueurs (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

Cleveland 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

Cleveland 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

Cleveland Leaders statistiques des joueurs (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

Cleveland 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