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

Phantoms
GP: 27 | W: 19 | L: 7 | OTL: 1 | P: 39
GF: 130 | GA: 95 | PP%: 44.26% | PK%: 83.64%
GM : Richard Duguay | Morale : 50 | Team Overall : 62
Next Games #469 vs Sags

Game Center
Crunch
7-20-1, 15pts
1
FINAL
3 Phantoms
19-7-1, 39pts
Team Stats
L5StreakL1
4-11-1Home Record10-5-1
3-9-0Home Record9-2-0
2-8-0Last 10 Games7-3-0
4.11Goals Per Game4.81
6.07Goals Against Per Game3.52
25.00%Power Play Percentage44.26%
58.82%Penalty Kill Percentage83.64%
Monsters
20-5-4, 44pts
4
FINAL
2 Phantoms
19-7-1, 39pts
Team Stats
W3StreakL1
7-2-4Home Record10-5-1
13-3-0Home Record9-2-0
8-0-2Last 10 Games7-3-0
4.93Goals Per Game4.81
3.72Goals Against Per Game3.52
44.74%Power Play Percentage44.26%
75.31%Penalty Kill Percentage83.64%
Sags
19-8-3, 41pts
2025-12-09
Phantoms
19-7-1, 39pts
Team Stats
W1StreakL1
12-3-2Home Record10-5-1
7-5-1Away Record9-2-0
5-4-1Last 10 Games7-3-0
4.33Goals Per Game4.81
3.53Goals Against Per Game4.81
27.14%Power Play Percentage44.26%
66.67%Penalty Kill Percentage83.64%
Las Vegas
8-18-2, 18pts
2025-12-11
Phantoms
19-7-1, 39pts
Team Stats
L2StreakL1
4-9-2Home Record10-5-1
4-9-0Away Record9-2-0
3-7-0Last 10 Games7-3-0
3.93Goals Per Game4.81
5.14Goals Against Per Game4.81
29.51%Power Play Percentage44.26%
56.00%Penalty Kill Percentage83.64%
Caroline
8-17-3, 19pts
2025-12-13
Phantoms
19-7-1, 39pts
Team Stats
L1StreakL1
5-8-2Home Record10-5-1
3-9-1Away Record9-2-0
4-6-0Last 10 Games7-3-0
3.96Goals Per Game4.81
5.82Goals Against Per Game4.81
16.39%Power Play Percentage44.26%
58.59%Penalty Kill Percentage83.64%
Team Leaders
Goals
Frank Nazar
21
Assists
Frank Nazar
28
Points
Frank Nazar
49
Plus/Minus
Caleb Jones
16
Wins
Devon Levi
12
Save Percentage
James Reimer
0.89

Team Stats
Goals For
130
4.81 GFG
Shots For
712
26.37 Avg
Power Play Percentage
44.3%
27 GF
Offensive Zone Start
31.7%
Goals Against
95
3.52 GAA
Shots Against
764
28.30 Avg
Penalty Kill Percentage
83.6%%
9 GA
Defensive Zone Start
35.5%
Team Info

General ManagerRichard Duguay
DivisionNord-Est
ConferenceEst
Captain
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance2,890
Season Tickets300


Roster Info

Pro Team20
Farm Team21
Contract Limit41 / 50
Prospects16


Filter Tips
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
# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPAgeContractSalary
1Frank Nazar (R)X100.00604076787684687260686867735550050680202950,000$
2Conor Geekie (R)X100.00704076697875666759636564675250050640203886,667$
3Tanner LaczynskiX100.0059427267646965644563596263605005061X0271775,000$
4Nick Abruzzese (R)X100.00564174676069676444645855635450050600251850,000$
5Ryder Rolston (R)X100.0064417364666463624259575961515005059X0222895,000$
6Elliot Desnoyers (R)X100.00584271666264636142605355605150050580221825,000$
7Dalibor Dvorský (R)X100.00604167626358576242616055625050050580193886,667$
8Tristan Broz (R)X100.00574264626162616255605955615050050580213925,000$
9Julian Lutz (R)X100.00604168586361595741575454575050050560203923,333$
10Caleb JonesX100.0064427568697472654063566963755605065N0272680,000$
11Kevin Korchinski (R)X100.00604473686970656840655962655550050630202918,333$
12Dylan CoghlanX100.0054426968666864664061646266605005062N0261650,000$
13Tobias Bjornfot (R)X100.0062417165656361594056536559525005060X0232800,000$
14Topi Niemelä (R)X100.00564271686164626240625563625150050600221856,667$
Scratches
1Trey Fix-Wolansky (R)X100.00574762715867666746656360675450050620251650,000$
TEAM AVERAGE100.0060427167656764644562596063555005061
Filter Tips
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
# Goalie Name CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SPAgeContractSalary
1Devon Levi (R)100.0077697268737575767674675850050670221925,000$
2Chris Driedger100.00697071676969706868696965580506303031,000,000$
Scratches
1James Reimer100.007085847880807780807878908305073N03612,222,222$
2Vadim Zherenko (R)100.0071636666686871666968585250050620231846,667$
3Cooper Black (R)100.0066595769646466656562545250050590232950,000$
TEAM AVERAGE100.007169707071717271727065635805065
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


Filter Tips
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
# Player Name Team NamePOSGP 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
1Frank NazarPhantoms (Phi)C2721284941354454110596519.09%1963423.494111510391012470157.45%6442720021.5422100432
2Conor GeekiePhantoms (Phi)C27182038175413676144823.68%1453319.752686291016442153.81%2361517001.4302010341
3Ryder RolstonPhantoms (Phi)RW27131831995364163243220.63%454820.314812839000034147.37%381522011.1300001303
4Elliot DesnoyersPhantoms (Phi)LW271613295100352760153126.67%1351919.226391634000292248.28%291315001.1200000322
5Nick AbruzzesePhantoms (Phi)C27111627620413174154914.86%1046017.06000111012192049.37%791310001.1700000214
6Dalibor DvorskýPhantoms (Phi)RW27815232135392366193212.12%447817.72336832000061035.00%201117000.9600001102
7Tanner LaczynskiPhantoms (Phi)C2711920560272356173819.64%841615.43000010002201152.63%1711314000.9612000031
8Caleb JonesPhantoms (Phi)D27414181695313634151211.76%2672126.71112348011257100%1836000.5000100000
9Kevin KorchinskiPhantoms (Phi)D27216181616021293212196.25%3272226.76123348033148000%01729000.5000000001
10Dylan CoghlanPhantoms (Phi)D272121484018152810107.14%1654120.060110270111380050.00%2726100.5200000001
11Topi NiemeläPhantoms (Phi)D27110114195132919985.26%1753819.9613422600003610100.00%1725000.4100001010
12Tristan BrozPhantoms (Phi)C27459-510022182351317.39%941715.4800006000081046.67%30519000.4300000010
13Michael McLeodPhiladelphieC3235120781191218.18%37324.6201104000180073.56%8703001.3501000002
14Tobias BjornfotPhantoms (Phi)D27044-79592010530%1338314.2000004000070050.00%2213000.2100001000
15Julian LutzPhantoms (Phi)LW27224-97526221431014.29%634812.901011140110140064.71%17110000.2300100000
Team Total or Average381115185300561364041041267623138217.01%194733819.26233962583583691937315655.78%1357154276130.8237314161519
Filter Tips
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
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Devon LeviPhantoms (Phi)1912410.8763.4710560061492264001.0003189210
2James ReimerPhantoms (Phi)97100.8902.915160125228108000.750497010
3Chris DriedgerPhantoms (Phi)30200.7958.71620094418000009000
Team Total or Average3119710.8763.49163501957643900072725220


Filter Tips
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
Player Name Team NamePOS Age Birthday Country Rookie Weight Height No Trade Available For Trade Acquired By Last Trade Date Force Waivers Waiver Possible Contract Contract Signature Date Force UFA Emergency Recall Type Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Salary Cap Year 2Salary Cap Year 3Salary Cap Year 4Salary Cap Year 5Salary Cap Year 6Salary Cap Year 7Salary Cap Year 8Salary Cap Year 9Salary Cap Year 10No Trade Year 2No Trade Year 3No Trade Year 4No Trade Year 5No Trade Year 6No Trade Year 7No Trade Year 8No Trade Year 9No Trade Year 10Link
Caleb JonesPhantoms (Phi)D271997-06-06USANo194 Lbs6 ft1YesNoFree AgentYesYes22025-09-21FalseFalsePro & Farm680,000$0$0$No680,000$--------680,000$--------No--------Link
Chris Driedger (1 Way Contract)Phantoms (Phi)G301994-05-18CANNo207 Lbs6 ft4NoNoFree AgentYesYes32024-09-23FalseFalsePro & Farm1,000,000$80,000$54,301$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Link
Conor GeekiePhantoms (Phi)C202004-05-05CANYes207 Lbs6 ft4NoNoProspectNoNo32025-07-10FalseFalsePro & Farm886,667$0$0$No886,667$886,667$-------886,667$886,667$-------NoNo-------Link
Cooper BlackPhantoms (Phi)G232001-06-14USAYes194 Lbs6 ft8NoNoDraftNoNo22024-06-25FalseFalsePro & Farm950,000$0$0$No950,000$--------950,000$--------No--------Link
Dalibor DvorskýPhantoms (Phi)RW192005-06-15SLVYes201 Lbs6 ft1NoNoTrade2025-07-18NoNo32025-07-10FalseFalsePro & Farm886,667$0$0$No886,667$886,667$-------886,667$886,667$-------NoNo-------Link
Devon LeviPhantoms (Phi)G222001-12-27CANYes183 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Link
Dylan CoghlanPhantoms (Phi)D261998-02-19CANNo205 Lbs6 ft2YesNoFree AgentYesYes12025-09-21FalseFalsePro & Farm650,000$0$0$No---------600,000$-----------------Link
Elliot DesnoyersPhantoms (Phi)LW222002-01-21CANYes183 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm825,000$0$0$No---------------------------Link
Frank NazarPhantoms (Phi)C202004-01-14USAYes190 Lbs5 ft10NoNoProspectNoNo22024-06-25FalseFalsePro & Farm950,000$0$0$No950,000$--------950,000$--------No--------Link
James Reimer (1 Way Contract)Phantoms (Phi)G361988-03-15CANNo200 Lbs6 ft2YesNoTrade2024-12-12YesYes1FalseFalsePro & Farm2,222,222$1,302,222$883,892$No---------------------------Link
Julian LutzPhantoms (Phi)LW202004-02-29GERYes194 Lbs6 ft3NoNoProspectNoNo32025-07-10FalseFalsePro & Farm923,333$0$0$No923,333$923,333$-------923,333$923,333$-------NoNo-------Link
Kevin KorchinskiPhantoms (Phi)D202004-06-21CANYes192 Lbs6 ft3NoNoProspectNoNo22024-06-25FalseFalsePro & Farm918,333$0$0$No918,333$--------918,333$--------No--------Link
Nick AbruzzesePhantoms (Phi)C251999-06-04USAYes181 Lbs5 ft11NoNoTrade2024-10-17YesYes1FalseFalsePro & Farm850,000$0$0$No---------------------------Link
Ryder RolstonPhantoms (Phi)RW222001-10-31USAYes201 Lbs6 ft2NoYesProspectNoNo22024-06-25FalseFalsePro & Farm895,000$0$0$No895,000$--------895,000$--------No--------Link
Tanner LaczynskiPhantoms (Phi)C271997-06-01USANo190 Lbs6 ft1NoYesN/AYesYes1FalseFalsePro & Farm775,000$0$0$No---------------------------Link
Tobias BjornfotPhantoms (Phi)D232001-04-06SWEYes203 Lbs6 ft0NoYesFree Agent2024-06-23NoNo22024-08-31FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Link
Topi NiemeläPhantoms (Phi)D222002-03-25FINYes179 Lbs6 ft0NoNoTrade2024-01-24NoNo1FalseFalsePro & Farm856,667$0$0$No---------------------------Link
Trey Fix-Wolansky (1 Way Contract)Phantoms (Phi)RW251999-05-26CANYes179 Lbs5 ft7NoNoWaiver2025-07-23YesYes12025-09-05FalseFalsePro & Farm650,000$0$0$No---------------------------Link
Tristan BrozPhantoms (Phi)C212002-10-10USAYes179 Lbs6 ft0NoNoProspectNoNo32025-07-10FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Link
Vadim ZherenkoPhantoms (Phi)G232001-03-15RUSYes196 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm846,667$0$0$No---------------------------Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2023.65193 Lbs6 ft11.80920,778$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Elliot DesnoyersFrank NazarRyder Rolston40122
2Julian LutzConor GeekieDalibor Dvorský30122
3Nick AbruzzeseTanner LaczynskiTristan Broz20122
4Frank NazarNick AbruzzeseConor Geekie10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Caleb JonesKevin Korchinski40122
2Dylan CoghlanTopi Niemelä30122
3Tobias Bjornfot20122
4Caleb JonesKevin Korchinski10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Elliot DesnoyersFrank NazarRyder Rolston60122
2Julian LutzConor GeekieDalibor Dvorský40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Caleb JonesKevin Korchinski60122
2Dylan CoghlanTopi Niemelä40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Frank NazarConor Geekie60122
2Tanner LaczynskiNick Abruzzese40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Caleb JonesKevin Korchinski60122
2Dylan CoghlanTopi Niemelä40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Frank Nazar60122Caleb JonesKevin Korchinski60122
2Conor Geekie40122Dylan CoghlanTopi Niemelä40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Frank NazarConor Geekie60122
2Tanner LaczynskiNick Abruzzese40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Caleb JonesKevin Korchinski60122
2Dylan CoghlanTopi Niemelä40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Elliot DesnoyersFrank NazarRyder RolstonCaleb JonesKevin Korchinski
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Elliot DesnoyersFrank NazarRyder RolstonCaleb JonesKevin Korchinski
Extra Forwards
Normal PowerPlayPenalty Kill
Tristan Broz, Ryder Rolston, Dalibor DvorskýTristan Broz, Ryder RolstonDalibor Dvorský
Extra Defensemen
Normal PowerPlayPenalty Kill
Tobias Bjornfot, Dylan Coghlan, Topi NiemeläTobias BjornfotDylan Coghlan, Topi Niemelä
Penalty Shots
Frank Nazar, Conor Geekie, Tanner Laczynski, Nick Abruzzese, Ryder Rolston
Goalie
#1 : Devon Levi, #2 : Chris Driedger


Filter Tips
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
OverallHomeVisitor
# VS Team 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
1Cabaret Lady Mary Ann33000000198111100000091822000000107361.00019294800314253579171268267127221275510770.00%6266.67%025743858.68%26349153.56%25245455.51%513250576245545285
2Caroline10001000651000000000001000100065121.00061117003142535311712682671234209300.00%000%025743858.68%26349153.56%25245455.51%513250576245545285
3Chiefs20200000613-71010000049-51010000024-200.00068140031425355817126826712441610383133.33%5180.00%025743858.68%26349153.56%25245455.51%513250576245545285
4Crunch11000000312110000003120000000000021.00036900314253530171268267123011412300.00%2150.00%025743858.68%26349153.56%25245455.51%513250576245545285
5Firebirds1010000013-21010000013-20000000000000.0001120031425352117126826712244920000%20100.00%025743858.68%26349153.56%25245455.51%513250576245545285
6Heat11000000936110000009360000000000021.0009142300314253525171268267124565193266.67%000%025743858.68%26349153.56%25245455.51%513250576245545285
7Jayhawks220000001266110000006331100000063341.000122133003142535541712682671243154358337.50%20100.00%125743858.68%26349153.56%25245455.51%513250576245545285
8Manchots20000110990200001109900000000000030.750913220031425353617126826712691714352150.00%8187.50%125743858.68%26349153.56%25245455.51%513250576245545285
9Marlies1010000035-21010000035-20000000000000.0003470031425352717126826712287421100.00%2150.00%025743858.68%26349153.56%25245455.51%513250576245545285
10Minnesota11000000642110000006420000000000021.000610160031425352217126826712226216200.00%10100.00%125743858.68%26349153.56%25245455.51%513250576245545285
11Monsters1010000024-21010000024-20000000000000.0002350031425351517126826712228413100.00%20100.00%125743858.68%26349153.56%25245455.51%513250576245545285
12Oceanics11000000734110000007340000000000021.00071219003142535331712682671241162625200.00%30100.00%025743858.68%26349153.56%25245455.51%513250576245545285
13Oil Kings1010000023-11010000023-10000000000000.00022400314253524171268267122154212150.00%2150.00%025743858.68%26349153.56%25245455.51%513250576245545285
14Rocket11000000642000000000001100000064221.00061016003142535171712682671221461311100.00%30100.00%025743858.68%26349153.56%25245455.51%513250576245545285
15Senators220000001028110000006241100000040441.0001014240131425353617126826712391413304250.00%40100.00%025743858.68%26349153.56%25245455.51%513250576245545285
16Sound Tigers21001000752110000005411000100021141.00071118003142535631712682671261199394250.00%20100.00%025743858.68%26349153.56%25245455.51%513250576245545285
17Spiders21100000121201100000042210100000810-220.5001220320031425357717126826712962212296466.67%6183.33%025743858.68%26349153.56%25245455.51%513250576245545285
18Stars10000010431000000000001000001043121.00044800314253528171268267123012615100.00%3166.67%025743858.68%26349153.56%25245455.51%513250576245545285
19Thunder11000000624000000000001100000062421.000681400314253536171268267122289125360.00%20100.00%025743858.68%26349153.56%25245455.51%513250576245545285
Total27157021201309535169500110765620116202010543915390.72213020133101314253571217126826712764213168457612744.26%55983.64%425743858.68%26349153.56%25245455.51%513250576245545285
_Since Last GM Reset27157021201309535169500110765620116202010543915390.72213020133101314253571217126826712764213168457612744.26%55983.64%425743858.68%26349153.56%25245455.51%513250576245545285
_Vs Conference11620111054381674100110342594210100020137170.77354821360131425353081712682671235610387191241250.00%27388.89%125743858.68%26349153.56%25245455.51%513250576245545285
_Vs Division72101000343134200000018153301010001616060.42934558900314253520717126826712260603511215746.67%16287.50%125743858.68%26349153.56%25245455.51%513250576245545285

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
2739L113020133171276421316845701
All Games
GPWLOTWOTL SOWSOLGFGA
27157212013095
Home Games
GPWLOTWOTL SOWSOLGFGA
169501107656
Visitor Games
GPWLOTWOTL SOWSOLGFGA
116220105439
Last 10 Games
WLOTWOTL SOWSOL
730000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
612744.26%55983.64%4
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
171268267123142535
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
25743858.68%26349153.56%25245455.51%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
513250576245545285


Last Played Games
Filter Tips
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
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
3 - 2025-10-0912Phantoms5Cabaret Lady Mary Ann3WBoxScore
5 - 2025-10-1130Phantoms6Caroline5WXBoxScore
7 - 2025-10-1344Cabaret Lady Mary Ann1Phantoms9WBoxScore
10 - 2025-10-1666Oceanics3Phantoms7WBoxScore
12 - 2025-10-1881Minnesota4Phantoms6WBoxScore
14 - 2025-10-2094Firebirds3Phantoms1LBoxScore
17 - 2025-10-23112Phantoms4Senators0WBoxScore
19 - 2025-10-25127Sound Tigers4Phantoms5WBoxScore
22 - 2025-10-28150Manchots6Phantoms5LXBoxScore
24 - 2025-10-30170Jayhawks3Phantoms6WBoxScore
26 - 2025-11-01188Marlies5Phantoms3LBoxScore
27 - 2025-11-02196Heat3Phantoms9WBoxScore
29 - 2025-11-04204Phantoms6Rocket4WBoxScore
31 - 2025-11-06223Phantoms6Jayhawks3WBoxScore
33 - 2025-11-08232Senators2Phantoms6WBoxScore
37 - 2025-11-12266Oil Kings3Phantoms2LBoxScore
39 - 2025-11-14281Phantoms2Chiefs4LBoxScore
40 - 2025-11-15293Phantoms4Stars3WXXBoxScore
45 - 2025-11-20324Chiefs9Phantoms4LBoxScore
47 - 2025-11-22339Spiders2Phantoms4WBoxScore
49 - 2025-11-24353Phantoms6Thunder2WBoxScore
51 - 2025-11-26363Phantoms5Cabaret Lady Mary Ann4WBoxScore
53 - 2025-11-28381Phantoms2Sound Tigers1WXBoxScore
54 - 2025-11-29395Phantoms8Spiders10LBoxScore
56 - 2025-12-01407Manchots3Phantoms4WXXBoxScore
58 - 2025-12-03423Crunch1Phantoms3WBoxScore
62 - 2025-12-07453Monsters4Phantoms2LBoxScore
64 - 2025-12-09469Sags-Phantoms-
66 - 2025-12-11483Las Vegas-Phantoms-
68 - 2025-12-13501Caroline-Phantoms-
69 - 2025-12-14510Phantoms-Caroline-
71 - 2025-12-16521Phantoms-Rocket-
73 - 2025-12-18535Phantoms-Crunch-
75 - 2025-12-20549Phantoms-Wolf Pack-
77 - 2025-12-22572Comets-Phantoms-
78 - 2025-12-23583Phantoms-Baby Hawks-
83 - 2025-12-28605Phantoms-Firebirds-
85 - 2025-12-30621Phantoms-Comets-
86 - 2025-12-31630Phantoms-Heat-
89 - 2026-01-03647Phantoms-Oil Kings-
92 - 2026-01-06670Admirals-Phantoms-
94 - 2026-01-08686Marlies-Phantoms-
96 - 2026-01-10705Thunder-Phantoms-
98 - 2026-01-12719Thunder-Phantoms-
100 - 2026-01-14736Phantoms-Crunch-
101 - 2026-01-15741Phantoms-Manchots-
103 - 2026-01-17755Wolf Pack-Phantoms-
105 - 2026-01-19775Phantoms-Las Vegas-
107 - 2026-01-21790Phantoms-Roadrunners-
109 - 2026-01-23805Phantoms-Monsters-
112 - 2026-01-26827Sound Tigers-Phantoms-
114 - 2026-01-28840Phantoms-Monsters-
115 - 2026-01-29843Phantoms-Bruins-
117 - 2026-01-31859Monarchs-Phantoms-
120 - 2026-02-03889Bears-Phantoms-
122 - 2026-02-05907Senators-Phantoms-
142 - 2026-02-25911Phantoms-Bears-
143 - 2026-02-26924Phantoms-Wolf Pack-
145 - 2026-02-28935Bruins-Phantoms-
147 - 2026-03-02954Phantoms-Marlies-
150 - 2026-03-05976Roadrunners-Phantoms-
152 - 2026-03-07993Phantoms-Manchots-
Trade Deadline --- Trades can’t be done after this day is simulated!
154 - 2026-03-091008Wolf Pack-Phantoms-
156 - 2026-03-111026Bears-Phantoms-
157 - 2026-03-121035Phantoms-Minnesota-
159 - 2026-03-141052Monsters-Phantoms-
163 - 2026-03-181082Phantoms-Admirals-
164 - 2026-03-191093Phantoms-Monarchs-
166 - 2026-03-211103Phantoms-Sags-
169 - 2026-03-241125Monsters-Phantoms-
171 - 2026-03-261142Baby Hawks-Phantoms-
173 - 2026-03-281163Phantoms-Cougars-
174 - 2026-03-291172Stars-Phantoms-
176 - 2026-03-311184Phantoms-Bears-
178 - 2026-04-021196Cougars-Phantoms-
179 - 2026-04-031205Phantoms-Sound Tigers-
181 - 2026-04-051224Bruins-Phantoms-
183 - 2026-04-071236Phantoms-Spiders-
185 - 2026-04-091250Phantoms-Cougars-
187 - 2026-04-111272Phantoms-Oceanics-
189 - 2026-04-131284Caroline-Phantoms-
190 - 2026-04-141294Rocket-Phantoms-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance30,92815,318
Attendance PCT96.65%95.74%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
-13 2890 - 96.35% 98,419$1,574,700$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Salaries CapCoaches Salaries
477,122$ 1,454,334$ 1,454,334$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
7,535$ 477,122$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
-1,181,025$ 131 7,535$ 987,085$




Phantoms Players Stat Leaders (Regular Season)

# Player Name 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

Phantoms Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Phantoms Career Team Stats

OverallHomeVisitor
Year 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

Phantoms Players Stat Leaders (Play-Off)

# Player Name 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

Phantoms Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA