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Connexion

Syracuse
GP: 79 | W: 32 | L: 38 | OTL: 9 | P: 73
GF: 222 | GA: 274 | PP%: 17.41% | PK%: 81.09%
DG: William Mercier | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #1004 vs Laval

Centre de jeu
Syracuse
32-38-9, 73pts
4
6 Wilkes-Barre/Scranton
47-29-5, 99pts
Team Stats
L3SéquenceL1
13-23-4Fiche domicile24-15-1
19-15-5Fiche domicile23-14-4
3-6-1Derniers 10 matchs7-2-1
2.81Buts par match 3.51
3.47Buts contre par match 2.96
17.41%Pourcentage en avantage numérique20.61%
81.09%Pourcentage en désavantage numérique80.87%
Hershey
38-31-8, 84pts
5
3 Syracuse
32-38-9, 73pts
Team Stats
L1SéquenceL3
21-17-2Fiche domicile13-23-4
17-14-6Fiche domicile19-15-5
6-4-0Derniers 10 matchs3-6-1
3.22Buts par match 2.81
3.12Buts contre par match 3.47
19.57%Pourcentage en avantage numérique17.41%
81.75%Pourcentage en désavantage numérique81.09%
Syracuse
32-38-9, 73pts
Jour 190
Laval
38-33-8, 84pts
Statistiques d’équipe
L3SéquenceW4
13-23-4Fiche domicile18-17-5
19-15-5Fiche visiteur20-16-3
3-6-110 derniers matchs6-3-1
2.81Buts par match 3.24
3.47Buts contre par match 3.24
17.41%Pourcentage en avantage numérique19.18%
81.09%Pourcentage en désavantage numérique85.07%
Hershey
38-31-8, 84pts
Jour 192
Syracuse
32-38-9, 73pts
Statistiques d’équipe
L1SéquenceL3
21-17-2Fiche domicile13-23-4
17-14-6Fiche visiteur19-15-5
6-4-010 derniers matchs3-6-1
3.22Buts par match 2.81
3.12Buts contre par match 2.81
19.57%Pourcentage en avantage numérique17.41%
81.75%Pourcentage en désavantage numérique81.09%
Syracuse
32-38-9, 73pts
Jour 193
Ontario
53-23-3, 109pts
Statistiques d’équipe
L3SéquenceL1
13-23-4Fiche domicile25-15-0
19-15-5Fiche visiteur28-8-3
3-6-110 derniers matchs6-4-0
2.81Buts par match 3.90
3.47Buts contre par match 3.90
17.41%Pourcentage en avantage numérique25.38%
81.09%Pourcentage en désavantage numérique82.78%
Meneurs d'équipe
Justin BaileyButs
Justin Bailey
29
Justin BaileyPasses
Justin Bailey
36
Justin BaileyPoints
Justin Bailey
65
Plus/Moins
Chris Wideman
20
Victoires
Devan Dubnyk
23
Pourcentage d’arrêts
Devan Dubnyk
0.93

Statistiques d’équipe
Buts pour
222
2.81 GFG
Tirs pour
2701
34.19 Avg
Pourcentage en avantage numérique
17.4%
55 GF
Début de zone offensive
40.0%
Buts contre
274
3.47 GAA
Tirs contre
2971
37.61 Avg
Pourcentage en désavantage numérique
81.1%%
45 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
Assistance2,214
Billets de saison300


Informations de la formation

Équipe Pro24
Équipe Mineure19
Limite contact 43 / 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 LehteraXXX100.00622991518268876480616761797771175000361500,000$
2Anders LeeX100.00742985679076926568646658757692235000331800,000$
3Carl HagelinXX100.00654284696978846754686762778064245000351800,000$
4Rocco GrimaldiXX100.00682093736875816670656759826552415000311500,000$
5Damien Giroux (R)X100.00403099757781996469656664754440575000241500,000$
6Trevor LewisXXX100.00602793567363906786676665676762165000371500,000$
7David DesharnaisXX100.00542295596272926485656561868468265000371500,000$
8Trevor MooreXX100.00672389787679946370646564756254495000291800,000$
9Justin BaileyXX100.00623190808978796976687064695651365000291800,000$
10Pontus AbergXX100.00592798788371856973686757836258405000301700,000$
11Ben Jones (R)XX100.00754585727970996270646363704949545000251500,000$
12Landon Slaggert (R)XX100.00713082857979996669676767703938685000223500,000$
13Cale FleuryX100.007128878289779948704847867748475150002531,250,000$
14Nikita NesterovX100.00712966797086874953494982706041405000301800,000$
15Travis HamonicX100.0074515161758088511514484527673275000341500,000$
16Mark BarberioX100.00643282608172824850454584737162235000341500,000$
17Chris WidemanX100.00702868697776865150514884727974155000341750,000$
18Alex GoligoskiX100.00563189457559845935515488799794135000381500,000$
19Dylan OlsenX100.00653763658478875150474988505847275000331500,000$
20Ryan JohnsonX100.00722598878678994570484188754140665000222700,000$
Rayé
MOYENNE D’ÉQUIPE100.0065318470787590596259597173655936500
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
1Devan Dubnyk100.0058798984768283848373718684215000381800,000$
2Corey Crawford100.005584888174827980807881949985000392600,000$
Rayé
1Dustin Tokarski100.0059877776718081787775707069325000341670,000$
2James Reimer100.0057827882718685838473798281385000361800,000$
MOYENNE D’ÉQUIPE100.005783838173838281817575838325500
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/RW74293665-521558932838520810.25%18135718.3431417662270001575151.28%15600010.9623100532
2Landon SlaggertSyracuse (TAM)C/LW70213354-24360107147302591776.95%28136619.531213251042670001303145.46%159700000.7914000303
3Carl HagelinSyracuse (TAM)LW/RW77193150-2978309956237711728.02%19143618.6551621712470000233138.71%18600000.7001312421
4Travis HamonicSyracuse (TAM)D77132841-71072514958101296612.87%107144318.755611401340000143300%200000.5700202222
5Cale FleurySyracuse (TAM)D6992635-1838049719930809.09%103147521.3958135320400022183147.06%3400000.4700000002
6Ryan JohnsonSyracuse (TAM)D6692534-122604061135311006.67%109149922.72549772130000692133.33%900000.4513000211
7Damien GirouxSyracuse (TAM)C57141933-700398141511239.93%2184814.8835831140000031044.52%115900000.7800000110
8Samuel MorinTampa Bay D7211223306610683912344808.94%57108515.08268511560111891044.00%2500000.6103101113
9Trevor LewisSyracuse (TAM)C/LW/RW7792332-2120467713739946.57%16104313.550115420001320051.21%70500000.6100000120
10Pontus AbergSyracuse (TAM)LW/RW79161531-241205199182611438.79%23137017.3502296310171863354.47%23500010.4518000113
11Rocco GrimaldiSyracuse (TAM)LW/RW69151530-1324061801455313610.34%22106515.4504483900051153057.69%7800000.5601000023
12Nikita NesterovSyracuse (TAM)D6682129-2360915310736637.48%102123718.7549135416100001370183.33%600000.4700000111
13Dylan OlsenSyracuse (TAM)D6582129-1151548688241689.76%118132320.36347268200021353138.97%13600000.4400001111
14Trevor MooreSyracuse (TAM)LW/RW776182432005764112261005.36%1385111.060004170001291248.73%23600000.5600000023
15Jori LehteraSyracuse (TAM)C/LW/RW6281321-1410042788932618.99%1383213.421012200031080053.03%84100000.5000000021
16Ben JonesSyracuse (TAM)C/LW6271421-18515947614433784.86%1399616.08426351400000280046.93%88000000.4200100012
17Taylor RaddyshTampa Bay RW32118196140423094226911.70%254617.0823528940000561249.33%15000000.7012000220
18Chris WidemanSyracuse (TAM)D724141820455622940223410.00%6079611.0600024000047000%000000.4500000100
19David DesharnaisSyracuse (TAM)C/LW4881018-44015459334658.60%1064913.5200000000000057.19%27800000.5501000002
20Alex GoligoskiSyracuse (TAM)D438917-11135103063133712.70%6683419.405163112900001031233.33%11100000.4101010111
21Anders BjorkTampa Bay LW/RW137916440131853143413.21%226920.762139301014311059.02%6100011.1900000210
22Mark BarberioSyracuse (TAM)D364610-714083031112512.90%5054315.09000130001420120.00%500000.3700000011
23Anders LeeSyracuse (TAM)LW30268-412045174711274.26%847315.7800004000000039.22%5100000.3400000000
24Brandon DavidsonTampa Bay D19066-91001812269150%3639921.030111767000015000%000000.3000000000
25Nicklas BergforsTampa Bay LW/RW15213-6801413419244.88%122014.73011414000030057.14%1400000.2700000001
Statistiques d’équipe totales ou en moyenne1427248429677-1947129012901442290786620798.53%10172396716.80611011627282493213291708341747.81%695500030.56627826282733
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)43231450.9302.6325822211316210100.731264238934
2James ReimerSyracuse (TAM)2061030.9063.01117721596280020.33331928210
3Corey CrawfordSyracuse (TAM)113710.8854.08618004236600200110000
Statistiques d’équipe totales ou en moyenne74323190.9182.9343784321426150142972661144


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$17,949$0$0$No---------------------------
Anders LeeSyracuse (TAM)LW331990-07-03USANo235 Lbs6 ft3NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$28,718$0$0$No---------------------------Lien / Lien NHL
Ben JonesSyracuse (TAM)C/LW251999-02-26CANYes187 Lbs6 ft0NoNoProspectNoNo12025-11-01FalseFalsePro & Farm500,000$17,949$0$0$No---------------------------
Cale FleurySyracuse (TAM)D251998-11-19CANNo204 Lbs6 ft1NoNoTrade2026-03-25NoNo32025-09-09FalseFalsePro & Farm1,250,000$44,872$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$28,718$0$0$No---------------------------Lien
Chris WidemanSyracuse (TAM)D341990-01-07USANo180 Lbs5 ft10NoNoTrade2026-04-25NoNo1FalseFalsePro & Farm750,000$26,923$0$0$No---------------------------Lien
Corey CrawfordSyracuse (TAM)G391984-12-31CANNo221 Lbs6 ft2NoNoFree AgentNoNo22025-09-27FalseFalsePro & Farm600,000$21,538$0$0$No600,000$--------600,000$--------No--------Lien
Damien GirouxSyracuse (TAM)C242000-03-03CANYes179 Lbs5 ft10NoNoTrade2025-08-27NoNo1FalseFalsePro & Farm500,000$17,949$0$0$No---------------------------
David DesharnaisSyracuse (TAM)C/LW371986-09-14CANNo177 Lbs5 ft7NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$17,949$0$0$No---------------------------Lien
Devan DubnykSyracuse (TAM)G381986-05-04CANNo221 Lbs6 ft6NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$28,718$0$0$No---------------------------
Dustin TokarskiSyracuse (TAM)G341989-09-16CANNo203 Lbs5 ft11NoNoFree AgentNoNo12024-10-09FalseFalsePro & Farm670,000$24,051$0$0$No---------------------------Lien
Dylan OlsenSyracuse (TAM)D331991-01-03USANo233 Lbs6 ft2NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$17,949$0$0$No---------------------------Lien
James ReimerSyracuse (TAM)G361988-01-21CANNo228 Lbs6 ft2NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$28,718$0$0$No---------------------------Lien NHL
Jori LehteraSyracuse (TAM)C/LW/RW361987-12-23FINNo212 Lbs6 ft2NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$17,949$0$0$No---------------------------Lien
Justin BaileySyracuse (TAM)LW/RW291995-07-01USANo220 Lbs6 ft3NoNoFree Agent2025-03-23NoNo12025-09-30FalseFalsePro & Farm800,000$28,718$0$0$No---------------------------Lien / Lien NHL
Landon SlaggertSyracuse (TAM)C/LW222002-06-25USAYes180 Lbs6 ft0NoNoProspectNoNo32025-11-01FalseFalsePro & Farm500,000$17,949$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------
Mark BarberioSyracuse (TAM)D341990-03-23CANNo209 Lbs6 ft1NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$17,949$0$0$No---------------------------
Nikita NesterovSyracuse (TAM)D301994-03-28RUSNo197 Lbs5 ft11NoNoFree AgentNoNo12024-10-11FalseFalsePro & Farm800,000$28,718$0$0$No---------------------------Lien
Pontus AbergSyracuse (TAM)LW/RW301993-09-23SWENo197 Lbs6 ft0NoNoFree AgentNoNo12025-09-27FalseFalsePro & Farm700,000$25,128$0$0$No---------------------------Lien
Rocco GrimaldiSyracuse (TAM)LW/RW311993-02-08USANo183 Lbs5 ft6NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$17,949$0$0$No---------900,000$900,000$----------------Lien
Ryan JohnsonSyracuse (TAM)D222001-07-24USANo195 Lbs6 ft1NoNoProspectNoNo22024-10-08FalseFalsePro & Farm700,000$25,128$0$0$No700,000$--------700,000$--------No--------
Travis HamonicSyracuse (TAM)D341990-01-19CANNo219 Lbs6 ft3NoNoFree Agent2025-03-19NoNo12025-11-05FalseFalsePro & Farm500,000$17,949$0$0$No---------------------------Lien NHL
Trevor LewisSyracuse (TAM)C/LW/RW371987-01-08USANo208 Lbs6 ft1NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$17,949$0$0$No---------------------------Lien / Lien NHL
Trevor MooreSyracuse (TAM)LW/RW291995-03-31USANo186 Lbs5 ft10NoNoFree AgentNoNo12025-09-30FalseFalsePro & Farm800,000$28,718$0$0$No---------------------------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2431.88202 Lbs6 ft01.25657,083$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Pontus AbergLandon SlaggertJustin Bailey35122
2Carl HagelinTrevor LewisRocco Grimaldi30122
3Anders LeeDavid DesharnaisTrevor Moore25122
4Ben JonesDamien GirouxJustin Bailey10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alex GoligoskiCale Fleury35122
2Travis HamonicRyan Johnson30122
3Chris WidemanMark Barberio25122
4Nikita NesterovAlex Goligoski10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anders LeeLandon SlaggertJustin Bailey50122
2Carl HagelinTrevor LewisRocco Grimaldi50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alex GoligoskiCale Fleury50122
2Travis HamonicRyan Johnson50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Pontus AbergJustin Bailey50122
2Landon SlaggertCarl Hagelin50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alex GoligoskiCale Fleury50122
2Travis HamonicRyan Johnson50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Landon Slaggert50122Alex GoligoskiCale Fleury50122
2Justin Bailey50122Travis HamonicRyan Johnson50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Anders LeeJustin Bailey50122
2Landon SlaggertCarl Hagelin50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alex GoligoskiCale Fleury50122
2Travis HamonicRyan Johnson50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Pontus AbergLandon SlaggertJustin BaileyAlex GoligoskiCale Fleury
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Pontus AbergLandon SlaggertJustin BaileyAlex GoligoskiCale Fleury
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Anders Lee, David Desharnais, Trevor MooreAnders Lee, David DesharnaisTrevor Moore
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Chris Wideman, Mark Barberio, Nikita NesterovChris WidemanMark Barberio, Nikita Nesterov
Tirs de pénalité
David Desharnais, Justin Bailey, Landon Slaggert, Carl Hagelin, Anders Lee
Gardien
#1 : Corey Crawford, #2 : Devan Dubnyk
Lignes d’attaque personnalisées en prolongation
Pontus Aberg, Justin Bailey, Landon Slaggert, Carl Hagelin, Anders Lee, Rocco Grimaldi, Trevor Lewis, David Desharnais, Trevor Moore, Damien Giroux
Lignes de défense personnalisées en prolongation
Alex Goligoski, Cale Fleury, Travis Hamonic, Ryan Johnson, Chris Wideman


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
1Abbotsford3110100011101210010006421010000056-140.66711193000926755111049199118306810025184314428.57%7185.71%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
2Bakersfield32100000972110000005232110000045-140.667917260092675511969199118306811027204315320.00%10280.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
3Bridgeport411000111113-2210000015502010001068-250.62511172800926755111109199118306814453255116318.75%90100.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
4Charlotte40200101918-92010010037-420100001611-520.2509162500926755111169199118306815748366517317.65%18761.11%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
5Cleveland41201000990201010006602110000033040.500916250092675511126919911830681362425611119.09%90100.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
6Coachella Valley20200000615-91010000037-41010000038-500.000610160092675511689199118306898366444125.00%30100.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
7Eagles404000001017-720200000610-42020000047-300.00010182800926755111249199118306812230326013646.15%15473.33%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
8Grand Rapids532000001716121100000660321000001110160.60017345110926755111729199118306821060497722313.64%15473.33%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
9Hartford412001001019-920100100614-82110000045-130.37510172700926755111139199118306816957446313215.38%13284.62%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
10Hershey31100010131031010000035-221000010105540.6671323361092675511115919911830688939265315213.33%5260.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
11Iowa211000007611010000005-51100000071620.50071421009267551176919911830686824162912325.00%8275.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
12Laval30300000513-82020000039-61010000024-200.00058131092675511105919911830681233424551516.67%11190.91%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
13Lehigh Valley41200100811-32020000036-32100010055030.37581422009267551111991991183068164535158800.00%15193.33%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
14Manitoba33000000615110000003122200000030361.00061117029267551111491991183068983416411200.00%80100.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
15Ontario211000005501010000034-11100000021120.5005712009267551165919911830686521103012216.67%4250.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
16Providence403000011016-62020000037-42010000179-210.12510182800926755111019199118306816655945610330.00%22577.27%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
17Rochester411011001418-421100000711-42000110077050.62514213500926755111639199118306819366266221523.81%13376.92%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
18Rockford41300000715-831200000610-41010000015-420.250714210092675511160919911830681524024602229.09%9366.67%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
19San Diego20000011880100000104311000000145-130.75081018009267551167919911830688730834500.00%40100.00%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
20San Jose2010100056-11010000024-21000100032120.500591400926755115991991183068702112304125.00%6183.33%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
21Springfield2110000011921010000034-11100000085320.5001120310092675511859199118306869208277228.57%3233.33%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
22Texas32001000963210010007521100000021161.0009142300926755111269199118306813841124713215.38%50100.00%11380292147.24%1485308948.07%588128645.72%1779119219796121044510
23Utica 4310000012842110000056-12200000072560.75012223401926755111719199118306810236305115320.00%14192.86%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
24Wilkes-Barre/Scranton403000011018-82010000158-320200000510-510.12510203010926755111469199118306814140295120315.00%12283.33%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
Total79243805435222274-524092303212103149-4639151502223119125-6730.4622223896114392675511270191991183068297191464111913165517.41%2384581.09%11380292147.24%1485308948.07%588128645.72%1779119219796121044510
_Since Last GM Reset79243805435222274-524092303212103149-4639151502223119125-6730.4622223896114392675511270191991183068297191464111913165517.41%2384581.09%11380292147.24%1485308948.07%588128645.72%1779119219796121044510
_Vs Conference47122302424128169-4123414012025590-352489012227379-6400.426128226354419267551115579199118306817945654597031832915.85%1562882.05%01380292147.24%1485308948.07%588128645.72%1779119219796121044510
_Vs Division20411012025581-261027001002240-181024011023341-8140.3505597152209267551165791991183068849263229315851517.65%792074.68%01380292147.24%1485308948.07%588128645.72%1779119219796121044510

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7973L322238961127012971914641119143
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7924385435222274
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
409233212103149
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3915152223119125
Derniers 10 matchs
WLOTWOTL SOWSOL
360100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3165517.41%2384581.09%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
9199118306892675511
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
1380292147.24%1485308948.07%588128645.72%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1779119219796121044510


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
163880Syracuse2Ontario1WSommaire du match
164887Lehigh Valley3Syracuse1LSommaire du match
166897Syracuse4Bridgeport3WXXSommaire du match
169910Charlotte2Syracuse1LXSommaire du match
171922Syracuse1Wilkes-Barre/Scranton4LSommaire du match
174934Charlotte5Syracuse2LSommaire du match
177947Syracuse4Utica 2WSommaire du match
180961Lehigh Valley3Syracuse2LSommaire du match
182971Syracuse4Wilkes-Barre/Scranton6LSommaire du match
185982Hershey5Syracuse3LSommaire du match
1901004Syracuse-Laval-
1921010Hershey-Syracuse-
1931015Syracuse-Ontario-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance59,38729,163
Assistance PCT74.23%72.91%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
1 2214 - 73.79% 129,743$5,189,719$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,780,212$ 1,577,000$ 1,577,000$ 1,400,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,087$ 1,430,040$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
129,743$ 7 15,267$ 106,869$




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