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Connexion

Syracuse
GP: 69 | W: 29 | L: 32 | OTL: 8 | P: 66
GF: 198 | GA: 240 | PP%: 18.56% | PK%: 81.25%
DG: William Mercier | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #880 vs Ontario

Centre de jeu
Abbotsford
26-38-7, 59pts
1
2 Syracuse
29-32-8, 66pts
Team Stats
W1SéquenceL1
14-19-2Fiche domicile13-19-3
12-19-5Fiche domicile16-13-5
5-4-1Derniers 10 matchs4-5-1
2.94Buts par match 2.87
3.69Buts contre par match 3.48
15.36%Pourcentage en avantage numérique18.56%
78.33%Pourcentage en désavantage numérique81.25%
Syracuse
29-32-8, 66pts
1
2 Cleveland
33-30-7, 73pts
Team Stats
L1SéquenceW4
13-19-3Fiche domicile15-17-3
16-13-5Fiche domicile18-13-4
4-5-1Derniers 10 matchs4-5-1
2.87Buts par match 2.79
3.48Buts contre par match 3.34
18.56%Pourcentage en avantage numérique17.87%
81.25%Pourcentage en désavantage numérique81.09%
Syracuse
29-32-8, 66pts
Jour 163
Ontario
47-19-3, 97pts
Statistiques d’équipe
L1SéquenceW1
13-19-3Fiche domicile23-12-0
16-13-5Fiche visiteur24-7-3
4-5-110 derniers matchs7-3-0
2.87Buts par match 3.86
3.48Buts contre par match 3.86
18.56%Pourcentage en avantage numérique24.82%
81.25%Pourcentage en désavantage numérique82.76%
Lehigh Valley
42-20-5, 89pts
Jour 164
Syracuse
29-32-8, 66pts
Statistiques d’équipe
W3SéquenceL1
23-9-4Fiche domicile13-19-3
19-11-1Fiche visiteur16-13-5
9-0-110 derniers matchs4-5-1
3.58Buts par match 2.87
2.76Buts contre par match 2.87
20.07%Pourcentage en avantage numérique18.56%
83.33%Pourcentage en désavantage numérique81.25%
Syracuse
29-32-8, 66pts
Jour 166
Bridgeport
32-33-5, 69pts
Statistiques d’équipe
L1SéquenceL2
13-19-3Fiche domicile13-20-2
16-13-5Fiche visiteur19-13-3
4-5-110 derniers matchs4-5-1
2.87Buts par match 3.46
3.48Buts contre par match 3.46
18.56%Pourcentage en avantage numérique21.43%
81.25%Pourcentage en désavantage numérique82.28%
Meneurs d'équipe
Justin BaileyButs
Justin Bailey
28
Justin BaileyPasses
Justin Bailey
33
Justin BaileyPoints
Justin Bailey
61
Plus/Moins
Chris Wideman
22
Victoires
Devan Dubnyk
21
Pourcentage d’arrêts
Devan Dubnyk
0.93

Statistiques d’équipe
Buts pour
198
2.87 GFG
Tirs pour
2405
34.86 Avg
Pourcentage en avantage numérique
18.6%
54 GF
Début de zone offensive
40.2%
Buts contre
240
3.48 GAA
Tirs contre
2628
38.09 Avg
Pourcentage en désavantage numérique
81.3%%
39 GA
Début de la zone défensive
42.3%
Informations de l'équipe

Directeur généralWilliam Mercier
EntraîneurRob Murray
DivisionNord
ConférenceConference est
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,204
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure17
Limite contact 42 / 50
Espoirs40


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
1Jori LehteraXXX100.00622991518268876580616761797771185000361500,000$
2Carl HagelinXX100.00654284696978846754686862778063245000351800,000$
3Taylor RaddyshX100.007832907987889675727277637952496450002611,400,000$
4Rocco GrimaldiXX100.00682093736875816670656760826452425000311500,000$
5Trevor LewisXXX100.00612793567363906686676665676761165000371500,000$
6Anders BjorkXX100.007433859188858775777275648453535250002711,400,000$
7Trevor MooreXX100.00672389787679946370646564756253495000291800,000$
8Pontus AbergXX98.00602797788371856973696757836257405000301700,000$
9Ben Jones (R)XX100.00754585727970996370646463704949555000251500,000$
10Cale FleuryX100.007128878289779948704847867748465150002531,250,000$
11Nikita NesterovX100.00712966797086874953494982705941415000301800,000$
12Travis HamonicX100.0074515161758088511514485527672275000341500,000$
13Chris WidemanX100.00702868697776865150514884727973155000341750,000$
14Alex GoligoskiX100.00563189457559845835515487799694145000381500,000$
15Brandon DavidsonX100.00653183648581885450525288767058295000321890,000$
16Dylan OlsenX100.00653764658478875150474988505847275000331500,000$
17Samuel MorinX100.00704670759683775255515183765844505000281950,000$
18Ryan JohnsonX100.00732598878678994570484188754040675000222700,000$
Rayé
1Anders LeeX100.00732985679076926568646658757592245000331800,000$
2Justin BaileyXX100.00623190808978796976677065695650365000291800,000$
3Landon Slaggert (R)XX100.00713082857979996669676767703838685000223500,000$
4Mark BarberioX100.00653282608172824850454584737162235000341500,000$
MOYENNE D’ÉQUIPE99.9168328371817689606159597373635838500
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
1James Reimer100.0057827882718685838473798281385000361800,000$
2Devan Dubnyk100.0058798984768283848373718684215000381800,000$
Rayé
1Dustin Tokarski100.0059877776718081787775707069325000341670,000$
MOYENNE D’ÉQUIPE100.005883818173838382817473797830500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Rob Murray79768970999964CAN5711,400,000$


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
1Justin BaileySyracuse (TAM)LW/RW67283361016052852587918810.85%16121618.1531417622110001395151.05%14300011.0023000522
2Landon SlaggertSyracuse (TAM)C/LW63203050-2034089125284541667.04%27123019.53121325992510001133144.91%140500000.8114000203
3Carl HagelinSyracuse (TAM)LW/RW67182543-2774308447213651438.45%15122818.334162067227000053140.40%15100000.7001312421
4Travis HamonicSyracuse (TAM)D67122537-389251345088255813.64%94123118.385611351110000125300%200000.6000202222
5Cale FleurySyracuse (TAM)D5992433-1730038589326679.68%82126721.4858135118500022003145.45%2200000.5200000002
6Damien GirouxTampa Bay C50141832-5003951385012010.14%2081316.2735831140000031044.48%111500000.7900000110
7Samuel MorinSyracuse (TAM)D69112132-16610683511643799.48%54101814.76268491500111881044.00%2500000.6302101113
8Ryan JohnsonSyracuse (TAM)D5682129-8240355212227836.56%93127822.83549681900000512128.57%700000.4502000211
9Dylan OlsenSyracuse (TAM)D6272128-1134047658041668.75%113128620.75347268000021302139.55%13400000.4400000101
10Nikita NesterovSyracuse (TAM)D5672027-434084519734617.22%94115320.60491350157000012901100.00%200000.4700000101
11Pontus AbergSyracuse (TAM)LW/RW69131427-201004989164571207.93%21115516.7502284710141623254.12%17000010.4717000102
12Trevor LewisSyracuse (TAM)C/LW/RW6771926-6100426312130865.79%1286912.980002260001270050.62%48200000.6000000020
13Rocco GrimaldiSyracuse (TAM)LW/RW59121224-1220051691174610610.26%2287614.8503372400051102061.19%6700000.5501000023
14Jori LehteraSyracuse (TAM)C/LW/RW5881321-158041778631599.30%1376113.121012200031080053.05%82000000.5500000021
15Trevor MooreSyracuse (TAM)LW/RW6741721518050588921804.49%1169010.300004170001271248.88%22300000.6100000022
16Taylor RaddyshSyracuse (TAM)RW31118195120402989226912.36%252917.0823528940000561249.66%14900000.7212000220
17Ben JonesSyracuse (TAM)C/LW5261319-15515856713532734.44%1191017.51426341350000270047.50%82100000.4200100012
18Chris WidemanSyracuse (TAM)D65313162241555253120279.68%4668310.5100012000047000%000000.4700000100
19Anders BjorkSyracuse (TAM)LW/RW126915340101748123012.50%225321.142139291014311061.02%5900011.1800000210
20David DesharnaisTampa Bay C/LW417815-34015387327579.59%1054613.3300000000000057.86%15900000.5501000002
21Alex GoligoskiSyracuse (TAM)D337512-104082153122513.21%4361418.61516301110000861148.15%5400000.3901000110
22Mark BarberioSyracuse (TAM)D29459-4606252582116.00%3942514.67000130001330120.00%500000.4200000011
23Anders LeeSyracuse (TAM)LW23156-38032122410154.17%736015.6900000000000034.78%4600000.3300000000
24Brandon DavidsonSyracuse (TAM)D19066-91001812269150%3639921.030111767000015000%000000.3000000000
25Nicklas BergforsTampa Bay LW/RW15213-6801413419244.88%122014.73011414000030057.14%1400000.2700000001
Statistiques d’équipe totales ou en moyenne1256225386611-1646157511501278261179018388.62%8842102016.7460991596852283213261526321547.79%607500030.58524715262330
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
1Devan DubnykSyracuse (TAM)40211350.9302.6523972210615080100.696233931833
2James ReimerSyracuse (TAM)2061030.9063.01117721596280020.33331925210
3Corey CrawfordTampa Bay 42200.8834.8719700161370010040000
Statistiques d’équipe totales ou en moyenne64292580.9202.8837724318122730132662561043


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
Alex GoligoskiSyracuse (TAM)D381985-07-30USANo187 Lbs5 ft11NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------
Anders BjorkSyracuse (TAM)LW/RW271996-08-05USANo196 Lbs6 ft0NoNoTrade2026-03-16NoNo12025-09-11FalseFalsePro & Farm1,400,000$236,923$0$0$No---------------------------Lien
Anders LeeSyracuse (TAM)LW331990-07-03USANo235 Lbs6 ft3NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$135,385$0$0$No---------------------------Lien / Lien NHL
Ben JonesSyracuse (TAM)C/LW251999-02-26CANYes187 Lbs6 ft0NoNoProspectNoNo12025-11-01FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------
Brandon DavidsonSyracuse (TAM)D321991-08-21CANNo219 Lbs6 ft2NoNoTrade2025-01-19NoNo1FalseFalsePro & Farm890,000$150,615$0$0$No---------------------------Lien
Cale FleurySyracuse (TAM)D251998-11-19CANNo204 Lbs6 ft1NoNoTrade2026-03-25NoNo32025-09-09FalseFalsePro & Farm1,250,000$211,538$0$0$No1,250,000$1,250,000$-------1,250,000$1,250,000$-------NoNo-------
Carl HagelinSyracuse (TAM)LW/RW351988-08-23SWENo195 Lbs5 ft11NoNoFree AgentNoNo12025-09-30FalseFalsePro & Farm800,000$135,385$0$0$No---------------------------Lien
Chris WidemanSyracuse (TAM)D341990-01-07USANo180 Lbs5 ft10NoNoTrade2026-04-25NoNo1FalseFalsePro & Farm750,000$126,923$0$0$No---------------------------Lien
Devan DubnykSyracuse (TAM)G381986-05-04CANNo221 Lbs6 ft6NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$135,385$0$0$No---------------------------
Dustin TokarskiSyracuse (TAM)G341989-09-16CANNo203 Lbs5 ft11NoNoFree AgentNoNo12024-10-09FalseFalsePro & Farm670,000$113,385$0$0$No---------------------------Lien
Dylan OlsenSyracuse (TAM)D331991-01-03USANo233 Lbs6 ft2NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------Lien
James ReimerSyracuse (TAM)G361988-01-21CANNo228 Lbs6 ft2NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$135,385$0$0$No---------------------------Lien NHL
Jori LehteraSyracuse (TAM)C/LW/RW361987-12-23FINNo212 Lbs6 ft2NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------Lien
Justin BaileySyracuse (TAM)LW/RW291995-07-01USANo220 Lbs6 ft3NoNoFree Agent2025-03-23NoNo12025-09-30FalseFalsePro & Farm800,000$135,385$0$0$No---------------------------Lien / Lien NHL
Landon SlaggertSyracuse (TAM)C/LW222002-06-25USAYes180 Lbs6 ft0NoNoProspectNoNo32025-11-01FalseFalsePro & Farm500,000$84,615$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------
Mark BarberioSyracuse (TAM)D341990-03-23CANNo209 Lbs6 ft1NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------
Nikita NesterovSyracuse (TAM)D301994-03-28RUSNo197 Lbs5 ft11NoNoFree AgentNoNo12024-10-11FalseFalsePro & Farm800,000$135,385$0$0$No---------------------------Lien
Pontus AbergSyracuse (TAM)LW/RW301993-09-23SWENo197 Lbs6 ft0NoNoFree AgentNoNo12025-09-27FalseFalsePro & Farm700,000$118,462$0$0$No---------------------------Lien
Rocco GrimaldiSyracuse (TAM)LW/RW311993-02-08USANo183 Lbs5 ft6NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$84,615$0$0$No---------900,000$900,000$----------------Lien
Ryan JohnsonSyracuse (TAM)D222001-07-24USANo195 Lbs6 ft1NoNoProspectNoNo22024-10-08FalseFalsePro & Farm700,000$118,462$0$0$No700,000$--------700,000$--------No--------
Samuel Morin (contrat à 1 volet)Syracuse (TAM)D281995-07-12CANNo206 Lbs6 ft6NoNoTrade2026-03-25YesYes1FalseFalsePro & Farm950,000$180,500$9,500$1,805$No---------------------------Lien
Taylor RaddyshSyracuse (TAM)RW261998-02-18CANNo198 Lbs6 ft3NoNoTrade2026-03-16NoNo12025-09-11FalseFalsePro & Farm1,400,000$236,923$0$0$No---------------------------Lien NHL
Travis HamonicSyracuse (TAM)D341990-01-19CANNo219 Lbs6 ft3NoNoFree Agent2025-03-19NoNo12025-11-05FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------Lien NHL
Trevor LewisSyracuse (TAM)C/LW/RW371987-01-08USANo208 Lbs6 ft1NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------Lien / Lien NHL
Trevor MooreSyracuse (TAM)LW/RW291995-03-31USANo186 Lbs5 ft10NoNoFree AgentNoNo12025-09-30FalseFalsePro & Farm800,000$135,385$0$0$No---------------------------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2531.12204 Lbs6 ft11.20752,400$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anders BjorkTaylor Raddysh35005
2Carl HagelinBen Jones30014
3Pontus AbergTrevor LewisJori Lehtera25122
4Rocco GrimaldiTrevor Moore10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Cale FleuryRyan Johnson35023
2Travis HamonicSamuel Morin30023
3Dylan OlsenNikita Nesterov25122
4Ryan Johnson10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anders BjorkTaylor Raddysh60005
2Carl HagelinBen Jones40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Cale FleuryRyan Johnson50005
2Travis HamonicSamuel Morin50005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Trevor LewisRocco Grimaldi50041
2Pontus Aberg50041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alex GoligoskiNikita Nesterov50050
2Travis HamonicDylan Olsen50050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Trevor Lewis50122Samuel MorinRyan Johnson50122
2Ben Jones50122Travis HamonicDylan Olsen50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Anders Bjork50122
2Ben Jones50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Samuel MorinRyan Johnson50122
2Travis HamonicCale Fleury50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anders BjorkTaylor RaddyshSamuel MorinRyan Johnson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Taylor RaddyshSamuel MorinRyan Johnson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, , Carl Hagelin, Carl Hagelin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Cale Fleury, Samuel Morin, Travis HamonicNikita Nesterov, Travis Hamonic
Tirs de pénalité
Anders Bjork, Taylor Raddysh, Pontus Aberg, ,
Gardien
#1 : Devan Dubnyk, #2 : James Reimer
Lignes d’attaque personnalisées en prolongation
, Anders Bjork, Pontus Aberg, , Ben Jones, Carl Hagelin, Taylor Raddysh, Trevor Lewis, Rocco Grimaldi, Trevor Moore
Lignes de défense personnalisées en prolongation
Samuel Morin, Ryan Johnson, Travis Hamonic, Dylan Olsen,


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
1Abbotsford3110100011101210010006421010000056-140.66711193000786251101048168057456310025184314428.57%7185.71%01220258447.21%1294271447.68%517112246.08%155010391736536908444
2Bakersfield32100000972110000005232110000045-140.667917260078625110968168057456311027204315320.00%10280.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
3Bridgeport31100001710-3210000015501010000025-330.500712190078625110888168057456311436234013323.08%80100.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
4Charlotte20100001611-50000000000020100001611-510.25061016007862511069816805745637019163716318.75%8450.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
5Cleveland41201000990201010006602110000033040.500916250078625110126816805745631362425611119.09%90100.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
6Coachella Valley20200000615-91010000037-41010000038-500.000610160078625110688168057456398366444125.00%30100.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
7Eagles404000001017-720200000610-42020000047-300.00010182800786251101248168057456312230326013646.15%15473.33%01220258447.21%1294271447.68%517112246.08%155010391736536908444
8Grand Rapids532000001716121100000660321000001110160.60017345110786251101728168057456321060497722313.64%15473.33%01220258447.21%1294271447.68%517112246.08%155010391736536908444
9Hartford412001001019-920100100614-82110000045-130.37510172700786251101138168057456316957446313215.38%13284.62%01220258447.21%1294271447.68%517112246.08%155010391736536908444
10Hershey2100001010550000000000021000010105541.00010172700786251108181680574563593110281119.09%4250.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
11Iowa211000007611010000005-51100000071620.50071421007862511076816805745636824162912325.00%8275.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
12Laval30300000513-82020000039-61010000024-200.00058131078625110105816805745631233424551516.67%11190.91%01220258447.21%1294271447.68%517112246.08%155010391736536908444
13Lehigh Valley21000100550000000000002100010055030.75059140078625110618168057456386251831400.00%90100.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
14Manitoba33000000615110000003122200000030361.00061117027862511011481680574563983416411200.00%80100.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
15Ontario1010000034-11010000034-10000000000000.0003470078625110418168057456332821510220.00%110.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
16Providence403000011016-62020000037-42010000179-210.12510182800786251101018168057456316655945610330.00%22577.27%01220258447.21%1294271447.68%517112246.08%155010391736536908444
17Rochester411011001418-421100000711-42000110077050.62514213500786251101638168057456319366266221523.81%13376.92%01220258447.21%1294271447.68%517112246.08%155010391736536908444
18Rockford41300000715-831200000610-41010000015-420.250714210078625110160816805745631524024602229.09%9366.67%01220258447.21%1294271447.68%517112246.08%155010391736536908444
19San Diego20000011880100000104311000000145-130.75081018007862511067816805745638730834500.00%40100.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
20San Jose2010100056-11010000024-21000100032120.500591400786251105981680574563702112304125.00%6183.33%01220258447.21%1294271447.68%517112246.08%155010391736536908444
21Springfield2110000011921010000034-11100000085320.5001120310078625110858168057456369208277228.57%3233.33%01220258447.21%1294271447.68%517112246.08%155010391736536908444
22Texas32001000963210010007521100000021161.0009142300786251101268168057456313841124713215.38%50100.00%11220258447.21%1294271447.68%517112246.08%155010391736536908444
23Utica 321000008622110000056-11100000030340.667814220178625110131816805745638727283812325.00%13192.31%01220258447.21%1294271447.68%517112246.08%155010391736536908444
24Wilkes-Barre/Scranton2010000158-32010000158-30000000000010.25051015107862511075816805745637111133012325.00%4175.00%01220258447.21%1294271447.68%517112246.08%155010391736536908444
Total69223205325198240-42359190311294131-3734131302213104109-5660.4781983465443378625110240581680574563262878154410512915418.56%2083981.25%11220258447.21%1294271447.68%517112246.08%155010391736536908444
_Since Last GM Reset69223205325198240-42359190311294131-3734131302213104109-5660.4781983465443378625110240581680574563262878154410512915418.56%2083981.25%11220258447.21%1294271447.68%517112246.08%155010391736536908444
_Vs Conference38111702314106136-3018410011024672-262077012126064-4350.461106186292317862511012858168057456314844453705781602817.50%1292382.17%01220258447.21%1294271447.68%517112246.08%155010391736536908444
_Vs Division18410011025274-22826000001933-141024011023341-8130.3615291143207862511061081680574563762234209287841517.86%691775.36%01220258447.21%1294271447.68%517112246.08%155010391736536908444

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6966L119834654424052628781544105133
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6922325325198240
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
35919311294131
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3413132213104109
Derniers 10 matchs
WLOTWOTL SOWSOL
450001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2915418.56%2083981.25%1
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
8168057456378625110
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
1220258447.21%1294271447.68%517112246.08%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
155010391736536908444


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
17Syracuse5Grand Rapids4WSommaire du match
316Laval6Syracuse2LSommaire du match
730Utica 4Syracuse1LSommaire du match
1146Syracuse3Eagles4LSommaire du match
1459Rockford3Syracuse4WSommaire du match
1776Bridgeport2Syracuse1LXXSommaire du match
22100Rockford4Syracuse1LSommaire du match
27126Wilkes-Barre/Scranton5Syracuse3LSommaire du match
30137Syracuse3Lehigh Valley2WSommaire du match
32149Syracuse3Bakersfield1WSommaire du match
33155Eagles4Syracuse3LSommaire du match
36174Grand Rapids4Syracuse1LSommaire du match
38184Syracuse3Grand Rapids5LSommaire du match
39193Syracuse2Hartford4LSommaire du match
41203Hartford4Syracuse3LXSommaire du match
44220Syracuse2Manitoba0WSommaire du match
46226Syracuse2Providence3LSommaire du match
47232Laval3Syracuse1LSommaire du match
50248Syracuse3San Jose2WXSommaire du match
52258Rockford3Syracuse1LSommaire du match
55273Syracuse1Bakersfield4LSommaire du match
57283Manitoba1Syracuse3WSommaire du match
59293Syracuse4San Diego5LXXSommaire du match
62306Syracuse3Rochester4LXSommaire du match
63313Bridgeport3Syracuse4WSommaire du match
67333Texas2Syracuse3WSommaire du match
70349Syracuse2Texas1WSommaire du match
71357Ontario4Syracuse3LSommaire du match
75378Texas3Syracuse4WXSommaire du match
77390Syracuse3Grand Rapids1WSommaire du match
78401Syracuse2Lehigh Valley3LXSommaire du match
80409San Jose4Syracuse2LSommaire du match
83429Coachella Valley7Syracuse3LSommaire du match
85443Syracuse3Charlotte7LSommaire du match
86451Syracuse5Abbotsford6LSommaire du match
88461Hartford10Syracuse3LSommaire du match
91475Syracuse3Coachella Valley8LSommaire du match
93482Rochester9Syracuse3LSommaire du match
97504Eagles6Syracuse3LSommaire du match
99515Syracuse1Rockford5LSommaire du match
101524Syracuse3Charlotte4LXXSommaire du match
103533Springfield4Syracuse3LSommaire du match
106555Grand Rapids2Syracuse5WSommaire du match
107564Syracuse7Iowa1WSommaire du match
109577Syracuse4Rochester3WXSommaire du match
111586Bakersfield2Syracuse5WSommaire du match
113599Syracuse1Manitoba0WSommaire du match
114609San Diego3Syracuse4WXXSommaire du match
118629Syracuse2Cleveland1WSommaire du match
119633Cleveland4Syracuse3LSommaire du match
122652Utica 2Syracuse4WSommaire du match
124661Syracuse2Bridgeport5LSommaire du match
127679Cleveland2Syracuse3WXSommaire du match
130692Syracuse2Hartford1WSommaire du match
132700Syracuse3Hershey2WXXSommaire du match
133709Rochester2Syracuse4WSommaire du match
136725Syracuse7Hershey3WSommaire du match
137734Wilkes-Barre/Scranton3Syracuse2LXXSommaire du match
140753Providence4Syracuse2LSommaire du match
141760Syracuse5Providence6LXXSommaire du match
143775Syracuse2Laval4LSommaire du match
145782Syracuse8Springfield5WSommaire du match
147788Abbotsford3Syracuse4WSommaire du match
150805Syracuse1Eagles3LSommaire du match
151811Syracuse3Utica 0WSommaire du match
153821Iowa5Syracuse0LSommaire du match
156838Providence3Syracuse1LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
158854Abbotsford1Syracuse2WXSommaire du match
160862Syracuse1Cleveland2LSommaire du match
163880Syracuse-Ontario-
164887Lehigh Valley-Syracuse-
166897Syracuse-Bridgeport-
169910Charlotte-Syracuse-
171922Syracuse-Wilkes-Barre/Scranton-
174934Charlotte-Syracuse-
177947Syracuse-Utica -
180961Lehigh Valley-Syracuse-
182971Syracuse-Wilkes-Barre/Scranton-
185982Hershey-Syracuse-
1901004Syracuse-Laval-
1921010Hershey-Syracuse-
1931015Syracuse-Ontario-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance51,58025,560
Assistance PCT73.69%73.03%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
6 2204 - 73.47% 129,052$4,516,825$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,380,268$ 1,786,000$ 1,786,000$ 1,400,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,159$ 1,216,770$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
774,313$ 33 16,338$ 539,154$




Syracuse 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

Syracuse 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

Syracuse 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

Syracuse 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

Syracuse 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