Rhinos

GP: 6 | W: 3 | L: 3 | OTL: 0 | P: 6
GF: 9 | GA: 10 | PP%: 5.56% | PK%: 83.33%
GM : Pierrick Jubinville | Morale : 80 | Team Overall : 63
Next Games #85 vs Pitbulls
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

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 SP
1Matthew NietoXX98.00714395816967866350755787256769080690
2Marcus FolignoXX99.00908881738762976240625983256970080680
3Nate ThompsonXX100.00765492697765916188605785257578080670
4Riley NashXX100.00735391797158946257615676856970080660
5Joonas DonskoiXX100.00654295787066906228747159596466070660
6Jordan SchroederXX100.00716194746179836580616267596162080650
7Curtis LazarXXX100.00767481727474776580596470616465070650
8Melker KarlssonXX100.00714289786559925951556874756567080650
9Adam ErneXX100.00896682727857826241656070755656080640
10Jordan NolanXX100.00814572738051876425625569256769080630
11Brendan LeipsicXX100.00734288716566777250716056255959080630
12Nathan GerbeXX100.00635873735862626750656065576869080620
13Ryan SproulX100.00827892737875805525464966474646080630
14Jarred TinordiX100.00828869658876844925394365414848080620
15Darren RaddyshX100.00777386657380875325464365415353080620
16Jakub JerabekX100.00767284767259625025384564435253080600
17Rob O'GaraX100.00768163708170774725374161394444080590
Scratches
1Matthew HighmoreXX100.00716684706662626550656263594444074610
2Paul BittnerX100.00828087658066686250625768544444074610
3Nicolas DeslauriersXX100.00937186717956775725565663256565074610
4Nick LappinXX100.00804499756666856557505561254949074600
5Jayden Halbgewachs (R)XX100.00655589655579846075575859554444074590
6Jeffrey Truchon-Viel (R)X100.00687161647173795350475458514444074560
7Olivier ArchambaultX100.00726490686455555550614461424444074560
TEAM AVERAGE99.8876638472726680604757566747575707763
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 SP
1Antti Raanta100.0070595971806161677670486061080660
2Aaron Dell100.0054575673595055555754655353080570
Scratches
TEAM AVERAGE100.006258587270565861676257575708062
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Randy Carlyle90947561636875CAN587300,000$


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
1Adam ErneRhinos (SJS)LW/RW6033-18019911460.00%09315.6500000000010050.00%200000.6400000000
2Matthew NietoRhinos (SJS)LW/RW6123100414101810.00%213021.690112290001241047.14%7000000.4600000011
3Jordan SchroederRhinos (SJS)C/RW6213-100310122416.67%210818.10000020000110075.00%800000.5500000000
4Melker KarlssonRhinos (SJS)C/RW6213220107130615.38%110016.77011229000000183.33%600000.6000000111
5Jakub JerabekRhinos (SJS)D6022300352110.00%112120.21000128000020000.00%000000.3300000001
6Jordan NolanRhinos (SJS)LW/RW6112010012221250.00%39115.180000000000000.00%100000.4400000000
7Marcus FolignoRhinos (SJS)LW/RW62021801010124716.67%111218.781018300000211060.00%500000.3600000100
8Riley NashRhinos (SJS)C/RW60222607133270.00%010016.74011129000000047.31%9300000.4000000000
9Joonas DonskoiRhinos (SJS)LW/RW61122203382412.50%111419.09101327000017100.00%300000.3500000010
10Rob O'GaraRhinos (SJS)D6011-120732010.00%310116.940002700009000.00%000000.2000000000
11Brendan LeipsicRhinos (SJS)LW/RW6011000211000.00%0162.710000000000000.00%100001.2300000000
12Darren RaddyshRhinos (SJS)D6011020412110.00%513923.18000031000123000.00%000000.1400000000
13Nate ThompsonRhinos (SJS)C/LW60111402149360.00%010818.160003300000160073.58%10600000.1800000000
14Jarred TinordiRhinos (SJS)D600031001312000.00%212220.46000031000018000.00%000000.0000000000
15Nathan GerbeRhinos (SJS)LW/RW6000020113010.00%1325.4600018000070066.67%300000.0000000000
16Ryan SproulRhinos (SJS)D6000-120672120.00%613823.06000030000020000.00%000000.0000000000
17Curtis LazarRhinos (SJS)C/LW/RW1000020120000.00%01111.8800000000000050.00%600000.0000000000
Team Total or Average9791726116001071039422569.57%28164416.962352331900021943157.57%30400000.3200000233
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
1Antti RaantaRhinos (SJS)63300.8921.673600210930000.000060100
Team Total or Average63300.8921.673600210930000.000060100


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 Rookie Weight Height No Trade Available For Trade Force Waivers Contract StatusType Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Link
Aaron Dell (1 Way Contract)Rhinos (SJS)G301989-05-04No200 Lbs6 ft0NoNoNo4UFAPro & Farm3,499,999$1,499,999$1,385,416$NoLink / NHL Link
Adam ErneRhinos (SJS)LW/RW241995-04-20No214 Lbs6 ft1NoNoNo1RFAPro & Farm925,000$0$0$NoLink
Antti Raanta (1 Way Contract)Rhinos (SJS)G301989-05-11No195 Lbs6 ft0NoNoNo1UFAPro & Farm1,000,000$0$0$NoLink / NHL Link
Brendan LeipsicRhinos (SJS)LW/RW251994-05-19No180 Lbs5 ft10NoNoNo1RFAPro & Farm700,000$0$0$NoLink
Curtis Lazar (1 Way Contract)Rhinos (SJS)C/LW/RW241995-02-02No209 Lbs6 ft0NoNoNo1RFAPro & Farm700,000$0$0$NoLink / NHL Link
Darren Raddysh (1 Way Contract)Rhinos (SJS)D231996-02-28No200 Lbs6 ft0NoNoNo2ELCPro & Farm1,300,000$0$0$NoLink
Jakub JerabekRhinos (SJS)D281991-05-12No200 Lbs5 ft11NoNoNo2UFAPro & Farm925,000$0$0$NoLink
Jarred TinordiRhinos (SJS)D271992-02-20No230 Lbs6 ft6NoNoNo2RFAPro & Farm850,000$0$0$NoLink / NHL Link
Jayden HalbgewachsRhinos (SJS)C/LW221997-03-22Yes157 Lbs5 ft8NoNoNo3ELCPro & Farm792,500$0$0$NoLink
Jeffrey Truchon-VielRhinos (SJS)LW221997-01-28Yes196 Lbs6 ft0NoNoNo3ELCPro & Farm780,000$0$0$NoLink
Joonas Donskoi (1 Way Contract)Rhinos (SJS)LW/RW271992-04-13No190 Lbs6 ft0NoNoNo1RFAPro & Farm3,900,000$1,900,000$1,754,861$NoLink / NHL Link
Jordan NolanRhinos (SJS)LW/RW301989-06-22No219 Lbs6 ft3NoNoNo1UFAPro & Farm950,000$0$0$NoLink / NHL Link
Jordan SchroederRhinos (SJS)C/RW281990-09-28No170 Lbs5 ft9NoNoNo2UFAPro & Farm700,000$0$0$NoLink / NHL Link
Marcus Foligno (1 Way Contract)Rhinos (SJS)LW/RW271991-08-10No232 Lbs6 ft3NoNoNo3RFAPro & Farm2,875,000$1,270,312$1,173,274$NoLink / NHL Link
Matthew HighmoreRhinos (SJS)LW/RW231996-02-27No181 Lbs5 ft11NoNoNo2ELCPro & Farm817,500$0$0$NoLink
Matthew Nieto (1 Way Contract)Rhinos (SJS)LW/RW261992-11-05No190 Lbs5 ft11NoNoNo1RFAPro & Farm1,975,000$0$0$NoLink
Melker Karlsson (1 Way Contract)Rhinos (SJS)C/RW281990-07-18No182 Lbs5 ft10NoNoNo5UFAPro & Farm2,000,000$550,000$507,986$NoLink / NHL Link
Nate Thompson (1 Way Contract)Rhinos (SJS)C/LW341984-10-05No214 Lbs6 ft1NoNoNo2UFAPro & Farm1,650,000$0$0$NoLink / NHL Link
Nathan GerbeRhinos (SJS)LW/RW311987-07-24No178 Lbs5 ft5NoNoNo2UFAPro & Farm700,000$0$0$NoLink
Nick LappinRhinos (SJS)LW/RW261992-11-01No175 Lbs6 ft1NoNoNo2RFAPro & Farm842,500$0$0$NoLink
Nicolas Deslauriers (1 Way Contract)Rhinos (SJS)LW/RW281991-02-22No215 Lbs6 ft1NoNoNo3UFAPro & Farm950,000$0$0$NoLink / NHL Link
Olivier Archambault (1 Way Contract)Rhinos (SJS)LW261993-02-17No177 Lbs5 ft11NoNoNo2RFAPro & Farm1,200,000$0$0$NoLink
Paul BittnerRhinos (SJS)LW221996-11-03No214 Lbs6 ft4NoNoNo1ELCPro & Farm800,000$0$0$NoLink
Riley Nash (1 Way Contract)Rhinos (SJS)C/RW301989-05-09No190 Lbs6 ft1NoNoNo4UFAPro & Farm2,750,000$1,355,000$1,251,493$NoLink / NHL Link
Rob O'GaraRhinos (SJS)D251993-07-06No215 Lbs6 ft4NoNoNo2RFAPro & Farm925,000$0$0$NoLink
Ryan SproulRhinos (SJS)D261993-01-12No205 Lbs6 ft4NoNoNo1RFAPro & Farm700,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2626.62197 Lbs6 ft02.081,354,135$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Matthew NietoNate ThompsonMarcus Foligno30122
2Joonas DonskoiRiley NashMelker Karlsson30122
3Adam ErneJordan Schroeder25122
4Jordan NolanMatthew NietoBrendan Leipsic15122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan SproulDarren Raddysh30122
2Jarred TinordiJakub Jerabek30122
3Rob O'GaraJordan Nolan25122
4Ryan SproulDarren Raddysh15122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Matthew NietoNate ThompsonMarcus Foligno55122
2Joonas DonskoiRiley NashMelker Karlsson45122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan SproulDarren Raddysh55122
2Jarred TinordiJakub Jerabek45122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Matthew NietoMarcus Foligno55122
2Nate ThompsonJoonas Donskoi45122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan SproulDarren Raddysh55122
2Jarred TinordiJakub Jerabek45122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Matthew Nieto55122Ryan SproulDarren Raddysh55122
2Marcus Foligno45122Jarred TinordiJakub Jerabek45122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Matthew NietoMarcus Foligno55122
2Nate ThompsonJoonas Donskoi45122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan SproulDarren Raddysh55122
2Jarred TinordiJakub Jerabek45122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Matthew NietoNate ThompsonMarcus FolignoRyan SproulDarren Raddysh
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Matthew NietoNate ThompsonMarcus FolignoRyan SproulDarren Raddysh
Extra Forwards
Normal PowerPlayPenalty Kill
Nathan Gerbe, , Jordan SchroederNathan Gerbe, Jordan Schroeder
Extra Defensemen
Normal PowerPlayPenalty Kill
Rob O'Gara, Jarred Tinordi, Jakub JerabekRob O'GaraJarred Tinordi, Jakub Jerabek
Penalty Shots
Matthew Nieto, Marcus Foligno, Nate Thompson, Joonas Donskoi, Riley Nash
Goalie
#1 : Antti Raanta, #2 : Aaron Dell


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
1Bengals1010000014-3000000000001010000014-300.0001230003601733214001961414200.00%7271.43%07414052.86%7714752.38%357546.67%148103137467436
2Devil Dogs1010000013-21010000013-20000000000000.0001230003601033214002021823500.00%9188.89%07414052.86%7714752.38%357546.67%148103137467436
3Indians1010000002-2000000000001010000002-200.000000000360123321400169818900.00%4250.00%07414052.86%7714752.38%357546.67%148103137467436
4Oil Kings11000000303000000000001100000030321.0003580103601733214001024178112.50%20100.00%07414052.86%7714752.38%357546.67%148103137467436
5Pitbulls11000000101110000001010000000000021.0001230103609332140017412217114.29%60100.00%07414052.86%7714752.38%357546.67%148103137467436
6Rivercats11000000312110000003120000000000021.000369000360293321400115414500.00%20100.00%07414052.86%7714752.38%357546.67%148103137467436
Total63300000910-1321000005413120000046-260.500917260203609433214009328601073625.56%30583.33%07414052.86%7714752.38%357546.67%148103137467436
_Since Last GM Reset63300000910-1321000005413120000046-260.500917260203609433214009328601073625.56%30583.33%07414052.86%7714752.38%357546.67%148103137467436
_Vs Conference63300000910-1321000005413120000046-260.500917260203609433214009328601073625.56%30583.33%07414052.86%7714752.38%357546.67%148103137467436
_Vs Division32100000422110000001012110000032140.6674711020360383321400431524562428.33%12283.33%07414052.86%7714752.38%357546.67%148103137467436

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
66L3917269493286010702
All Games
GPWLOTWOTL SOWSOLGFGA
6330000910
Home Games
GPWLOTWOTL SOWSOLGFGA
321000054
Visitor Games
GPWLOTWOTL SOWSOLGFGA
312000046
Last 10 Games
WLOTWOTL SOWSOL
330000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
3625.56%30583.33%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
33214000360
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
7414052.86%7714752.38%357546.67%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
148103137467436


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
1 - 2019-10-073Pitbulls0Rhinos1WBoxScore
4 - 2019-10-1024Rivercats1Rhinos3WBoxScore
6 - 2019-10-1238Rhinos3Oil Kings0WBoxScore
8 - 2019-10-1448Rhinos1Bengals4LBoxScore
9 - 2019-10-1558Rhinos0Indians2LBoxScore
11 - 2019-10-1769Devil Dogs3Rhinos1LBoxScore
13 - 2019-10-1985Pitbulls-Rhinos-
15 - 2019-10-2198Gamblers-Rhinos-
16 - 2019-10-22104Rhinos-Liberty-
18 - 2019-10-24120Rhinos-Broncos-
21 - 2019-10-27132Aces-Rhinos-
22 - 2019-10-28143Rhinos-Aces-
24 - 2019-10-30154Cobras-Rhinos-
26 - 2019-11-01163Rhinos-Cobras-
28 - 2019-11-03177Rhinos-Citadels-
30 - 2019-11-05188Aces-Rhinos-
32 - 2019-11-07200Rhinos-Aces-
34 - 2019-11-09214Devil Dogs-Rhinos-
37 - 2019-11-12228Oil Kings-Rhinos-
39 - 2019-11-14241Rhinos-Boys-
41 - 2019-11-16250Blazers-Rhinos-
43 - 2019-11-18263Rhinos-Blazers-
44 - 2019-11-19271Cobras-Rhinos-
46 - 2019-11-21284Rhinos-Cobras-
48 - 2019-11-23296Citadels-Rhinos-
50 - 2019-11-25312Broncos-Rhinos-
52 - 2019-11-27323Rhinos-Citadels-
54 - 2019-11-29333Rhinos-Rivercats-
55 - 2019-11-30343Rhinos-Liberty-
57 - 2019-12-02356Rhinos-Indians-
58 - 2019-12-03359Olympic-Rhinos-
60 - 2019-12-05379Rhinos-Devil Dogs-
62 - 2019-12-07388Mystery-Rhinos-
65 - 2019-12-10403Rhinos-Broncos-
66 - 2019-12-11412Sun Devils-Rhinos-
68 - 2019-12-13424Rhinos-Redhawks-
69 - 2019-12-14433Aeros-Rhinos-
71 - 2019-12-16448Rhinos-Bengals-
73 - 2019-12-18459Oil Kings-Rhinos-
74 - 2019-12-19475Rivercats-Rhinos-
76 - 2019-12-21483Rhinos-Surfers-
77 - 2019-12-22494Bengals-Rhinos-
79 - 2019-12-24510Redhawks-Rhinos-
81 - 2019-12-26523Rhinos-Redhawks-
83 - 2019-12-28530Rhinos-Olympic-
84 - 2019-12-29542Jets-Rhinos-
86 - 2019-12-31554Rhinos-Olympic-
88 - 2020-01-02568Jets-Rhinos-
90 - 2020-01-04584Rhinos-Aeros-
92 - 2020-01-06595Aeros-Rhinos-
94 - 2020-01-08608Blazers-Rhinos-
96 - 2020-01-10616Rhinos-Oil Kings-
97 - 2020-01-11630Indians-Rhinos-
99 - 2020-01-13642Rhinos-Winterhawks-
100 - 2020-01-14656Winterhawks-Rhinos-
102 - 2020-01-16669Rhinos-Pitbulls-
103 - 2020-01-17678Rhinos-Sun Devils-
105 - 2020-01-19691Winterhawks-Rhinos-
107 - 2020-01-21704Rhinos-Gamblers-
108 - 2020-01-22714Boys-Rhinos-
110 - 2020-01-24727Rhinos-Aeros-
112 - 2020-01-26736Rhinos-Gators-
113 - 2020-01-27744Gamblers-Rhinos-
115 - 2020-01-29759Rhinos-Pitbulls-
Trade Deadline --- Trades can’t be done after this day is simulated!
117 - 2020-01-31766Pitbulls-Rhinos-
119 - 2020-02-02779Rhinos-Gamblers-
120 - 2020-02-03788Liberty-Rhinos-
122 - 2020-02-05807Gators-Rhinos-
124 - 2020-02-07818Rhinos-Winterhawks-
125 - 2020-02-08831Surfers-Rhinos-
128 - 2020-02-11848Rhinos-Mystery-
130 - 2020-02-13854Indians-Rhinos-
131 - 2020-02-14866Rhinos-Mystery-
133 - 2020-02-16878Gators-Rhinos-
136 - 2020-02-19893Rhinos-Sun Devils-
138 - 2020-02-21902Boys-Rhinos-
139 - 2020-02-22910Rhinos-Jets-
143 - 2020-02-26934Surfers-Rhinos-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price7020
Attendance3,0641,599
Attendance PCT51.07%53.30%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
36 1554 - 51.81% 82,153$246,460$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
92,631$ 912,600$ 912,600$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
6,338$ 69,718$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
2,957,520$ 133 8,421$ 1,119,993$




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
201963300000910-1321000005413120000046-26917260203609433214009328601073625.56%30583.33%07414052.86%7714752.38%357546.67%148103137467436
Total Regular Season63300000910-1321000005413120000046-26917260203609433214009328601073625.56%30583.33%07414052.86%7714752.38%357546.67%148103137467436