These functions are used to summarise the simulation outputs, typically by joining the optimal scores with a matching schedule.
Usage
ffs_summarise_week(optimal_scores, schedules)
ffs_summarise_season(summary_week)
ffs_summarise_simulation(summary_season)
ffs_summarise_inseason(summary_week, n)
ffs_summarize_week(optimal_scores, schedules)
ffs_summarize_season(summary_week)
ffs_summarize_simulation(summary_season)Arguments
- optimal_scores
a dataframe of optimized lineups as created by
ffs_optimize_lineups()- schedules
a dataframe of schedules as created by
ffs_build_schedules()orffs_actual_schedules()- summary_week
a dataframe as created by
ffs_summarise_week()- summary_season
a dataframe as created by
ffs_summarise_season()- n
number of weeks
Value
ffs_summarise_week: a dataframe summarising team results by simulation week
ffs_summarise_season: a dataframe summarising franchise results across each simulation season
ffs_summarise_simulation: a dataframe summarising franchise results across the simulation
ffs_summarise_inseason: a dataframe summarising franchise results for the inseason simulation
See also
vignette("custom") for example usage
Examples
# \donttest{
# cached examples
optimal_scores <- .ffs_cache("optimal_scores.rds")
schedules <- .ffs_cache("schedules.rds")
summary_week <- ffs_summarise_week(optimal_scores, schedules)
summary_week
#> season week franchise_name optimal_score lineup_efficiency
#> <int> <int> <char> <num> <num>
#> 1: 1 1 Mexico City Space Force 189.38 0.840
#> 2: 1 1 Dirty Dgens 127.19 0.810
#> 3: 1 1 Alberta Armadillos 187.08 0.758
#> 4: 1 1 Electric Woodies 158.05 0.830
#> 5: 1 1 Motor City Mutts 131.59 0.757
#> 6: 1 1 Hoth City Tauntauns 121.98 0.808
#> 7: 1 1 Paw Patrol 175.41 0.764
#> 8: 1 1 Domination Station 191.49 0.818
#> 9: 1 1 Kill Devil Hills Carpetbaggers 219.67 0.755
#> 10: 1 1 [Redacted] 165.27 0.754
#> 11: 1 1 TB12 149.53 0.820
#> 12: 1 1 Indigo Plateau Elite 205.11 0.803
#> 13: 1 2 Mexico City Space Force 180.82 0.679
#> 14: 1 2 Dirty Dgens 69.30 0.804
#> 15: 1 2 Alberta Armadillos 135.32 0.825
#> 16: 1 2 Electric Woodies 163.90 0.815
#> 17: 1 2 Motor City Mutts 174.86 0.858
#> 18: 1 2 Hoth City Tauntauns 146.23 0.872
#> 19: 1 2 Paw Patrol 106.17 0.769
#> 20: 1 2 Domination Station 173.30 0.707
#> 21: 1 2 Kill Devil Hills Carpetbaggers 163.46 0.822
#> 22: 1 2 [Redacted] 104.77 0.832
#> 23: 1 2 TB12 164.16 0.732
#> 24: 1 2 Indigo Plateau Elite 173.42 0.812
#> 25: 1 3 Mexico City Space Force 198.14 0.820
#> 26: 1 3 Dirty Dgens 97.60 0.825
#> 27: 1 3 Alberta Armadillos 128.70 0.830
#> 28: 1 3 Electric Woodies 168.57 0.851
#> 29: 1 3 Motor City Mutts 144.93 0.817
#> 30: 1 3 Hoth City Tauntauns 198.28 0.762
#> 31: 1 3 Paw Patrol 150.44 0.729
#> 32: 1 3 Domination Station 188.13 0.765
#> 33: 1 3 Kill Devil Hills Carpetbaggers 189.04 0.764
#> 34: 1 3 [Redacted] 123.63 0.736
#> 35: 1 3 TB12 220.86 0.726
#> 36: 1 3 Indigo Plateau Elite 190.83 0.738
#> 37: 2 1 Mexico City Space Force 185.69 0.860
#> 38: 2 1 Dirty Dgens 106.80 0.696
#> 39: 2 1 Alberta Armadillos 124.05 0.806
#> 40: 2 1 Electric Woodies 150.16 0.796
#> 41: 2 1 Motor City Mutts 151.70 0.778
#> 42: 2 1 Hoth City Tauntauns 104.60 0.794
#> 43: 2 1 Paw Patrol 158.65 0.703
#> 44: 2 1 Domination Station 158.34 0.798
#> 45: 2 1 Kill Devil Hills Carpetbaggers 120.53 0.727
#> 46: 2 1 [Redacted] 166.64 0.739
#> 47: 2 1 TB12 236.82 0.863
#> 48: 2 1 Indigo Plateau Elite 195.58 0.812
#> 49: 2 2 Mexico City Space Force 220.84 0.832
#> 50: 2 2 Dirty Dgens 134.42 0.780
#> 51: 2 2 Alberta Armadillos 165.20 0.741
#> 52: 2 2 Electric Woodies 159.49 0.847
#> 53: 2 2 Motor City Mutts 172.44 0.838
#> 54: 2 2 Hoth City Tauntauns 168.38 0.832
#> 55: 2 2 Paw Patrol 175.36 0.706
#> 56: 2 2 Domination Station 153.40 0.677
#> 57: 2 2 Kill Devil Hills Carpetbaggers 176.83 0.710
#> 58: 2 2 [Redacted] 105.14 0.735
#> 59: 2 2 TB12 174.02 0.756
#> 60: 2 2 Indigo Plateau Elite 172.41 0.776
#> 61: 2 3 Mexico City Space Force 260.17 0.779
#> 62: 2 3 Dirty Dgens 128.42 0.800
#> 63: 2 3 Alberta Armadillos 154.36 0.697
#> 64: 2 3 Electric Woodies 149.82 0.790
#> 65: 2 3 Motor City Mutts 169.84 0.805
#> 66: 2 3 Hoth City Tauntauns 88.82 0.787
#> 67: 2 3 Paw Patrol 163.74 0.816
#> 68: 2 3 Domination Station 199.54 0.727
#> 69: 2 3 Kill Devil Hills Carpetbaggers 181.67 0.839
#> 70: 2 3 [Redacted] 173.88 0.811
#> 71: 2 3 TB12 152.97 0.843
#> 72: 2 3 Indigo Plateau Elite 162.65 0.799
#> season week franchise_name optimal_score lineup_efficiency
#> team_score opponent_score result opponent_name
#> <num> <num> <char> <char>
#> 1: 158.99 122.62 W TB12
#> 2: 103.04 131.13 L Electric Woodies
#> 3: 141.82 134.04 W Paw Patrol
#> 4: 131.13 103.04 W Dirty Dgens
#> 5: 99.61 98.56 W Hoth City Tauntauns
#> 6: 98.56 99.61 L Motor City Mutts
#> 7: 134.04 141.82 L Alberta Armadillos
#> 8: 156.63 124.65 W [Redacted]
#> 9: 165.75 164.65 W Indigo Plateau Elite
#> 10: 124.65 156.63 L Domination Station
#> 11: 122.62 158.99 L Mexico City Space Force
#> 12: 164.65 165.75 L Kill Devil Hills Carpetbaggers
#> 13: 122.71 122.45 W Domination Station
#> 14: 55.74 87.21 L [Redacted]
#> 15: 111.64 150.05 L Motor City Mutts
#> 16: 133.63 127.57 W Hoth City Tauntauns
#> 17: 150.05 111.64 W Alberta Armadillos
#> 18: 127.57 133.63 L Electric Woodies
#> 19: 81.64 134.30 L Kill Devil Hills Carpetbaggers
#> 20: 122.45 122.71 L Mexico City Space Force
#> 21: 134.30 81.64 W Paw Patrol
#> 22: 87.21 55.74 W Dirty Dgens
#> 23: 120.17 140.73 L Indigo Plateau Elite
#> 24: 140.73 120.17 W TB12
#> 25: 162.41 109.68 W Paw Patrol
#> 26: 80.48 151.01 L Hoth City Tauntauns
#> 27: 106.85 143.99 L Domination Station
#> 28: 143.43 140.74 W Indigo Plateau Elite
#> 29: 118.47 91.02 W [Redacted]
#> 30: 151.01 80.48 W Dirty Dgens
#> 31: 109.68 162.41 L Mexico City Space Force
#> 32: 143.99 106.85 W Alberta Armadillos
#> 33: 144.42 160.27 L TB12
#> 34: 91.02 118.47 L Motor City Mutts
#> 35: 160.27 144.42 W Kill Devil Hills Carpetbaggers
#> 36: 140.74 143.43 L Electric Woodies
#> 37: 159.64 83.05 W Hoth City Tauntauns
#> 38: 74.33 117.96 L Motor City Mutts
#> 39: 99.96 111.51 L Paw Patrol
#> 40: 119.57 126.38 L Domination Station
#> 41: 117.96 74.33 W Dirty Dgens
#> 42: 83.05 159.64 L Mexico City Space Force
#> 43: 111.51 99.96 W Alberta Armadillos
#> 44: 126.38 119.57 W Electric Woodies
#> 45: 87.62 204.32 L TB12
#> 46: 123.10 158.76 L Indigo Plateau Elite
#> 47: 204.32 87.62 W Kill Devil Hills Carpetbaggers
#> 48: 158.76 123.10 W [Redacted]
#> 49: 183.64 104.85 W Dirty Dgens
#> 50: 104.85 183.64 L Mexico City Space Force
#> 51: 122.42 125.62 L Kill Devil Hills Carpetbaggers
#> 52: 135.11 77.28 W [Redacted]
#> 53: 144.59 123.81 W Paw Patrol
#> 54: 140.16 133.82 W Indigo Plateau Elite
#> 55: 123.81 144.59 L Motor City Mutts
#> 56: 103.79 131.54 L TB12
#> 57: 125.62 122.42 W Alberta Armadillos
#> 58: 77.28 135.11 L Electric Woodies
#> 59: 131.54 103.79 W Domination Station
#> 60: 133.82 140.16 L Hoth City Tauntauns
#> 61: 202.71 129.93 W Indigo Plateau Elite
#> 62: 102.70 141.01 L [Redacted]
#> 63: 107.59 129.01 L TB12
#> 64: 118.31 136.67 L Motor City Mutts
#> 65: 136.67 118.31 W Electric Woodies
#> 66: 69.90 152.46 L Kill Devil Hills Carpetbaggers
#> 67: 133.68 145.10 L Domination Station
#> 68: 145.10 133.68 W Paw Patrol
#> 69: 152.46 69.90 W Hoth City Tauntauns
#> 70: 141.01 102.70 W Dirty Dgens
#> 71: 129.01 107.59 W Alberta Armadillos
#> 72: 129.93 202.71 L Mexico City Space Force
#> team_score opponent_score result opponent_name
#> allplay_wins allplay_games allplay_pct league_id franchise_id
#> <num> <num> <num> <char> <char>
#> 1: 9 11 0.818 22627 0001
#> 2: 2 11 0.182 22627 0002
#> 3: 7 11 0.636 22627 0003
#> 4: 5 11 0.455 22627 0004
#> 5: 1 11 0.091 22627 0005
#> 6: 0 11 0.000 22627 0006
#> 7: 6 11 0.545 22627 0007
#> 8: 8 11 0.727 22627 0008
#> 9: 11 11 1.000 22627 0009
#> 10: 4 11 0.364 22627 0010
#> 11: 3 11 0.273 22627 0011
#> 12: 10 11 0.909 22627 0012
#> 13: 6 11 0.545 22627 0001
#> 14: 0 11 0.000 22627 0002
#> 15: 3 11 0.273 22627 0003
#> 16: 8 11 0.727 22627 0004
#> 17: 11 11 1.000 22627 0005
#> 18: 7 11 0.636 22627 0006
#> 19: 1 11 0.091 22627 0007
#> 20: 5 11 0.455 22627 0008
#> 21: 9 11 0.818 22627 0009
#> 22: 2 11 0.182 22627 0010
#> 23: 4 11 0.364 22627 0011
#> 24: 10 11 0.909 22627 0012
#> 25: 11 11 1.000 22627 0001
#> 26: 0 11 0.000 22627 0002
#> 27: 2 11 0.182 22627 0003
#> 28: 6 11 0.545 22627 0004
#> 29: 4 11 0.364 22627 0005
#> 30: 9 11 0.818 22627 0006
#> 31: 3 11 0.273 22627 0007
#> 32: 7 11 0.636 22627 0008
#> 33: 8 11 0.727 22627 0009
#> 34: 1 11 0.091 22627 0010
#> 35: 10 11 0.909 22627 0011
#> 36: 5 11 0.455 22627 0012
#> 37: 10 11 0.909 22627 0001
#> 38: 0 11 0.000 22627 0002
#> 39: 3 11 0.273 22627 0003
#> 40: 6 11 0.545 22627 0004
#> 41: 5 11 0.455 22627 0005
#> 42: 1 11 0.091 22627 0006
#> 43: 4 11 0.364 22627 0007
#> 44: 8 11 0.727 22627 0008
#> 45: 2 11 0.182 22627 0009
#> 46: 7 11 0.636 22627 0010
#> 47: 11 11 1.000 22627 0011
#> 48: 9 11 0.818 22627 0012
#> 49: 11 11 1.000 22627 0001
#> 50: 2 11 0.182 22627 0002
#> 51: 3 11 0.273 22627 0003
#> 52: 8 11 0.727 22627 0004
#> 53: 10 11 0.909 22627 0005
#> 54: 9 11 0.818 22627 0006
#> 55: 4 11 0.364 22627 0007
#> 56: 1 11 0.091 22627 0008
#> 57: 5 11 0.455 22627 0009
#> 58: 0 11 0.000 22627 0010
#> 59: 6 11 0.545 22627 0011
#> 60: 7 11 0.636 22627 0012
#> 61: 11 11 1.000 22627 0001
#> 62: 1 11 0.091 22627 0002
#> 63: 2 11 0.182 22627 0003
#> 64: 3 11 0.273 22627 0004
#> 65: 7 11 0.636 22627 0005
#> 66: 0 11 0.000 22627 0006
#> 67: 6 11 0.545 22627 0007
#> 68: 9 11 0.818 22627 0008
#> 69: 10 11 0.909 22627 0009
#> 70: 8 11 0.727 22627 0010
#> 71: 4 11 0.364 22627 0011
#> 72: 5 11 0.455 22627 0012
#> allplay_wins allplay_games allplay_pct league_id franchise_id
#> optimal_player_id
#> <list>
#> 1: 14777,15241,12447,14079,13722,14137,...
#> 2: 12610,15238,11747,14803,12212,12263,...
#> 3: 10700,11644,13610,14085,14802,14806,...
#> 4: 10703,14778,13319,13364,13880,10973,...
#> 5: 13593,9431,12171,13234,12677,9474,...
#> 6: 13590,15237,14804,14808,14870,9925,...
#> 7: 12611,12620,13128,15257,14807,13679,...
#> 8: 15240,9099,13290,13604,13607,13299,...
#> 9: 10697,7836,11657,13132,13427,12187,...
#> 10: 12140,13116,13622,14827,12676,11671,...
#> 11: 14782,5848,13131,13850,15329,10729,...
#> 12: 14056,7401,11193,12626,13130,14071,...
#> 13: 13592,14777,14079,15260,13672,14138,...
#> 14: 15238,11747,13138,14803,12212,15330,...
#> 15: 11644,13424,13610,14075,14087,14802,...
#> 16: 10703,13589,13139,13378,14813,13236,...
#> 17: 13593,9431,13404,14080,12677,14867,...
#> 18: 13590,15237,11886,15414,11247,12656,...
#> 19: 12620,11761,15255,13679,13153,13164,...
#> 20: 15240,9099,12164,13290,13604,14798,...
#> 21: 14059,7836,11657,12625,13132,13133,...
#> 22: 12140,13116,13136,14223,13680,11671,...
#> 23: 15239,5848,13131,13614,13850,14828,...
#> 24: 14056,8062,11193,13130,14071,14852,...
#> 25: 13592,14777,12447,14797,13722,12175,...
#> 26: 15238,11390,11747,14815,15268,12212,...
#> 27: 11644,13113,13610,14087,14085,11695,...
#> 28: 10703,14778,13139,13319,13364,13880,...
#> 29: 13593,9431,13135,13620,13919,14867,...
#> 30: 11640,15237,11886,13726,11247,14875,...
#> 31: 12611,12620,12152,13128,15255,13679,...
#> 32: 11760,12164,13604,13607,14798,13299,...
#> 33: 10697,7836,11657,13132,12678,13427,...
#> 34: 12140,13116,14223,15254,12676,13680,...
#> 35: 14783,12630,13131,13850,15262,13192,...
#> 36: 14056,14779,12626,13130,13606,14071,...
#> 37: 13592,14777,14081,14073,14079,14797,...
#> 38: 12141,15238,13138,14803,15268,12263,...
#> 39: 10700,11644,12386,13610,14087,14802,...
#> 40: 10703,13115,13319,13378,14801,13236,...
#> 41: 13593,13135,13404,15258,12677,9474,...
#> 42: 13590,15237,13726,14804,9925,12176,...
#> 43: 10413,12620,11761,13128,15257,10276,...
#> 44: 14067,9099,12164,12629,13604,13188,...
#> 45: 10697,14059,12625,13108,13753,11222,...
#> 46: 13116,14223,15254,12676,11671,13163,...
#> 47: 15239,5848,13131,13614,14017,13192,...
#> 48: 14056,7401,12626,13130,14852,11244,...
#> 49: 13592,15241,14073,15260,14143,11674,...
#> 50: 12610,15238,11747,13138,12212,12263,...
#> 51: 10700,11644,13610,14075,14085,14802,...
#> 52: 13589,14778,13139,13146,13319,14813,...
#> 53: 13593,9431,13234,14095,14072,13919,...
#> 54: 13590,14057,13789,14808,15414,14870,...
#> 55: 12620,15252,12152,13128,14811,15255,...
#> 56: 15246,9099,12164,13604,14798,13188,...
#> 57: 13846,7836,11657,12625,13108,13132,...
#> 58: 12140,13116,13622,15254,12676,11671,...
#> 59: 14783,5848,13131,13850,13192,13674,...
#> 60: 14056,14779,11193,12626,14071,11647,...
#> 61: 13592,14777,12447,14073,14797,14805,...
#> 62: 12610,14780,11747,14803,14815,12263,...
#> 63: 10700,13424,12386,13610,14802,15256,...
#> 64: 13589,14778,13319,13364,13236,13880,...
#> 65: 13593,9431,13135,13404,15258,12677,...
#> 66: 11640,13590,13789,14808,15337,12176,...
#> 67: 12611,12620,12151,13128,15257,11516,...
#> 68: 15240,9099,13604,13608,14798,15272,...
#> 69: 14059,7836,12625,13108,13132,12678,...
#> 70: 12623,13116,13136,14223,12676,11671,...
#> 71: 14783,15239,12630,13129,15262,13674,...
#> 72: 7401,8062,12626,13130,13606,11244,...
#> optimal_player_id
#> optimal_player_score
#> <list>
#> 1: 13.88,14.30,23.70, 6.40, 8.55, 6.05,...
#> 2: 10.94,15.15,13.90,22.50, 6.40, 9.40,...
#> 3: 27.54,26.74,11.80,12.20,28.10,15.10,...
#> 4: 29.90,17.30, 8.20,18.50, 7.15, 6.70,...
#> 5: 19.50,23.88,13.00, 6.70, 9.50,10.45,...
#> 6: 4.32,17.36,31.70, 3.20, 9.50, 6.90,...
#> 7: 33.74,20.82,28.90, 5.50, 8.70, 9.75,...
#> 8: 24.38,22.06, 7.30,13.60, 7.10,16.10,...
#> 9: 21.28,36.14, 8.30, 8.00,17.55,37.20,...
#> 10: 10.40,19.22, 4.30, 0.80, 8.95,31.30,...
#> 11: 25.04,24.44, 4.40,14.70,10.05, 6.50,...
#> 12: 39.61,17.60, 9.70,20.20,22.80,25.30,...
#> 13: 17.76,28.76,10.10, 8.30,12.85,13.95,...
#> 14: 9.35, 4.50, 8.40,14.90, 2.45, 3.30,...
#> 15: 30.20,17.22,17.50, 6.70, 6.50, 8.40,...
#> 16: 23.12,28.48,27.10, 5.50,11.90, 7.60,...
#> 17: 17.52,33.84, 7.90,21.10, 9.50, 8.30,...
#> 18: 26.34,15.74,15.20,11.20, 6.75, 8.80,...
#> 19: 14.12,14.40,12.00, 1.65,10.30, 6.40,...
#> 20: 32.66,25.04, 7.70, 9.80,41.10,11.70,...
#> 21: 30.88,14.58, 9.00,11.60,18.30, 7.80,...
#> 22: 21.42,42.00, 0.00,10.20, 1.65, 3.40,...
#> 23: 22.44,22.62,11.80, 8.60,13.40, 9.00,...
#> 24: 29.86,27.51,12.20,19.00, 8.20, 8.40,...
#> 25: 12.14,15.00,15.90,27.80,16.70,22.10,...
#> 26: 21.70, 2.80,16.70, 2.70, 7.00, 1.85,...
#> 27: 23.40, 8.70,10.40,11.30, 6.60, 6.35,...
#> 28: 27.80,18.42,27.10, 6.80,21.10, 6.25,...
#> 29: 21.46, 7.62, 4.60, 4.40,17.55, 6.90,...
#> 30: 21.42,26.56, 4.70,13.10,10.35, 7.15,...
#> 31: 33.74,22.90,11.80, 7.80,12.30, 5.00,...
#> 32: 18.03,14.10,22.90,28.00,12.40, 9.20,...
#> 33: 25.42,18.32, 0.00,32.60,11.75,22.25,...
#> 34: 10.40,28.08, 4.20,12.20, 7.15, 7.70,...
#> 35: 38.86, 6.70,13.60,26.30, 7.20, 9.20,...
#> 36: 19.22,27.96,14.80,23.00,11.70,15.50,...
#> 37: 9.58,20.46,11.30,26.80,24.70, 9.50,...
#> 38: 6.84,16.36, 3.20,13.80,12.70,12.75,...
#> 39: 16.34,19.16,13.30, 9.50,12.30,14.90,...
#> 40: 39.00,29.96,22.70,13.20, 4.60, 9.30,...
#> 41: 19.9,11.6,13.3, 9.7,15.8, 9.3,...
#> 42: 11.32,13.58, 2.00, 0.90,19.00, 4.40,...
#> 43: 16.88,23.12,19.20,13.60, 8.60,15.70,...
#> 44: 12.30,19.44,17.50, 9.00,11.80, 9.50,...
#> 45: 27.96,13.12,14.80, 0.60, 6.85,10.90,...
#> 46: 39.64, 9.70,32.40, 0.00,12.60,12.00,...
#> 47: 25.60,21.12,12.70,17.70,26.40,15.45,...
#> 48: 12.94,27.51,17.80,26.80,19.10,18.75,...
#> 49: 29.60,24.02,21.10,15.10,22.50,23.60,...
#> 50: 21.42,13.00,14.90,15.90, 5.55, 6.05,...
#> 51: 14.58,17.02,29.60,17.50, 4.70,13.10,...
#> 52: 31.92,29.32, 7.00, 7.70,13.40,28.20,...
#> 53: 12.94,22.20,18.20, 7.50,12.90,22.30,...
#> 54: 19.26,10.52,18.50,15.30,31.40, 9.50,...
#> 55: 13.32,29.54,18.40,11.40,19.20,18.20,...
#> 56: 23.46,16.34, 8.40,15.10,15.70, 8.65,...
#> 57: 23.83,37.50, 5.90,42.40,12.90,10.50,...
#> 58: 10.98, 3.96, 4.30,15.10, 6.90,12.50,...
#> 59: 32.88,24.44,20.90, 8.40,12.45,12.35,...
#> 60: 17.96,39.00,13.30,15.90,11.90,12.75,...
#> 61: 21.42,19.80,14.70,24.10,27.30,17.00,...
#> 62: 13.32,17.50, 5.00,17.10, 8.20, 5.30,...
#> 63: 16.60,18.01,13.30,13.70,22.50,11.30,...
#> 64: 18.32,30.00, 8.80,25.30, 7.85,10.75,...
#> 65: 18.79,25.40,15.10,16.20, 8.60,11.00,...
#> 66: 10.94,22.38, 1.90, 3.20, 6.00, 3.30,...
#> 67: 22.50,21.44, 9.40,22.30, 7.90, 5.80,...
#> 68: 19.37,31.35,39.80,15.00,12.20, 9.40,...
#> 69: 23.44,15.68,24.50,15.90,13.50,11.90,...
#> 70: 14.88,42.00, 3.40,10.30, 0.00,23.20,...
#> 71: 31.92,21.60, 7.60, 7.70, 7.90,14.45,...
#> 72: 14.56,21.64,10.40,19.20,20.50,14.20,...
#> optimal_player_score
summary_season <- ffs_summarise_season(summary_week)
summary_season
#> season league_id franchise_id franchise_name h2h_wins
#> <int> <char> <char> <char> <int>
#> 1: 1 22627 0001 Mexico City Space Force 3
#> 2: 1 22627 0002 Dirty Dgens 0
#> 3: 1 22627 0003 Alberta Armadillos 1
#> 4: 1 22627 0004 Electric Woodies 3
#> 5: 1 22627 0005 Motor City Mutts 3
#> 6: 1 22627 0006 Hoth City Tauntauns 1
#> 7: 1 22627 0007 Paw Patrol 0
#> 8: 1 22627 0008 Domination Station 2
#> 9: 1 22627 0009 Kill Devil Hills Carpetbaggers 2
#> 10: 1 22627 0010 [Redacted] 1
#> 11: 1 22627 0011 TB12 1
#> 12: 1 22627 0012 Indigo Plateau Elite 1
#> 13: 2 22627 0001 Mexico City Space Force 3
#> 14: 2 22627 0002 Dirty Dgens 0
#> 15: 2 22627 0003 Alberta Armadillos 0
#> 16: 2 22627 0004 Electric Woodies 1
#> 17: 2 22627 0005 Motor City Mutts 3
#> 18: 2 22627 0006 Hoth City Tauntauns 1
#> 19: 2 22627 0007 Paw Patrol 1
#> 20: 2 22627 0008 Domination Station 2
#> 21: 2 22627 0009 Kill Devil Hills Carpetbaggers 2
#> 22: 2 22627 0010 [Redacted] 1
#> 23: 2 22627 0011 TB12 3
#> 24: 2 22627 0012 Indigo Plateau Elite 1
#> season league_id franchise_id franchise_name h2h_wins
#> h2h_winpct allplay_wins allplay_games allplay_winpct points_for
#> <num> <num> <num> <num> <num>
#> 1: 1.000 26 33 0.788 444.11
#> 2: 0.000 2 33 0.061 239.26
#> 3: 0.333 12 33 0.364 360.31
#> 4: 1.000 19 33 0.576 408.19
#> 5: 1.000 16 33 0.485 368.13
#> 6: 0.333 16 33 0.485 377.14
#> 7: 0.000 10 33 0.303 325.36
#> 8: 0.667 20 33 0.606 423.07
#> 9: 0.667 28 33 0.848 444.47
#> 10: 0.333 7 33 0.212 302.88
#> 11: 0.333 17 33 0.515 403.06
#> 12: 0.333 25 33 0.758 446.12
#> 13: 1.000 32 33 0.970 545.99
#> 14: 0.000 3 33 0.091 281.88
#> 15: 0.000 8 33 0.242 329.97
#> 16: 0.333 17 33 0.515 372.99
#> 17: 1.000 22 33 0.667 399.22
#> 18: 0.333 10 33 0.303 293.11
#> 19: 0.333 14 33 0.424 369.00
#> 20: 0.667 18 33 0.545 375.27
#> 21: 0.667 17 33 0.515 365.70
#> 22: 0.333 15 33 0.455 341.39
#> 23: 1.000 21 33 0.636 464.87
#> 24: 0.333 21 33 0.636 422.51
#> h2h_winpct allplay_wins allplay_games allplay_winpct points_for
#> points_against potential_points
#> <num> <num>
#> 1: 354.75 568.34
#> 2: 369.35 294.09
#> 3: 428.08 451.10
#> 4: 371.35 490.52
#> 5: 301.22 451.38
#> 6: 313.72 466.49
#> 7: 438.53 432.02
#> 8: 354.21 552.92
#> 9: 406.56 572.17
#> 10: 330.84 393.67
#> 11: 444.14 534.55
#> 12: 429.35 569.36
#> 13: 317.83 666.70
#> 14: 442.61 369.64
#> 15: 366.14 443.61
#> 16: 340.33 459.47
#> 17: 316.45 493.98
#> 18: 445.92 361.80
#> 19: 389.65 497.75
#> 20: 384.79 511.28
#> 21: 396.64 479.03
#> 22: 396.57 445.66
#> 23: 299.00 563.81
#> 24: 465.97 530.64
#> points_against potential_points
summary_simulation <- ffs_summarise_simulation(summary_season)
summary_simulation
#> league_id franchise_id franchise_name seasons h2h_wins
#> <char> <char> <char> <int> <num>
#> 1: 22627 0001 Mexico City Space Force 2 3.0
#> 2: 22627 0012 Indigo Plateau Elite 2 1.0
#> 3: 22627 0009 Kill Devil Hills Carpetbaggers 2 2.0
#> 4: 22627 0005 Motor City Mutts 2 3.0
#> 5: 22627 0008 Domination Station 2 2.0
#> 6: 22627 0011 TB12 2 2.0
#> 7: 22627 0004 Electric Woodies 2 2.0
#> 8: 22627 0006 Hoth City Tauntauns 2 1.0
#> 9: 22627 0007 Paw Patrol 2 0.5
#> 10: 22627 0010 [Redacted] 2 1.0
#> 11: 22627 0003 Alberta Armadillos 2 0.5
#> 12: 22627 0002 Dirty Dgens 2 0.0
#> h2h_winpct allplay_wins allplay_winpct points_for points_against
#> <num> <num> <num> <num> <num>
#> 1: 1.000 29.0 0.879 495.050 336.290
#> 2: 0.333 23.0 0.697 434.315 447.660
#> 3: 0.667 22.5 0.681 405.085 401.600
#> 4: 1.000 19.0 0.576 383.675 308.835
#> 5: 0.667 19.0 0.576 399.170 369.500
#> 6: 0.666 19.0 0.576 433.965 371.570
#> 7: 0.666 18.0 0.545 390.590 355.840
#> 8: 0.333 13.0 0.394 335.125 379.820
#> 9: 0.166 12.0 0.364 347.180 414.090
#> 10: 0.333 11.0 0.334 322.135 363.705
#> 11: 0.166 10.0 0.303 345.140 397.110
#> 12: 0.000 2.5 0.076 260.570 405.980
#> potential_points
#> <num>
#> 1: 617.520
#> 2: 550.000
#> 3: 525.600
#> 4: 472.680
#> 5: 532.100
#> 6: 549.180
#> 7: 474.995
#> 8: 414.145
#> 9: 464.885
#> 10: 419.665
#> 11: 447.355
#> 12: 331.865
# }