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MinV and MVP College Football Rankings |
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Performance
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Below is an assessment of the ranking systems posted on Kenneth Massey's ranking compilation page for this season. Using a simple form of Data Envelopment Analysis and software from Holger Scheel, each system is given an efficiency score representing how close its combined retrodictive and predictive performance is to the efficient frontier. Retrodictive performance is measured by the number of past head-to-head results that were correctly matched by the weekly ranking (the first number in the "Retrodictive" column below), while predictive performance is measured by the number of games in the following week that were correctly predicted (the first number in the "Predictive" column below). If one were to plot each system's performance, with retrodictive performance on one axis and predictive performance on the other, the efficient frontier would be formed by the most extreme systems in all possible directions. The efficient frontier approach is an arguably fair way to compare ranking systems regardless of whether they focus on retrodictive or predictive performance (or some combination thereof). The approach determines the implicit weight that a system places on each objective, and uses these weights (shown in parenthese below) to determine the appropriate comparison point on the efficient frontier. Each system is thus evaluated only against peers with a similar combination of objectives. Any system with 100% efficiency is on the efficient frontier, meaning that if the weights noted for that system are applied, no other system surpasses it. If a system has an efficiency less than 100%, then even if the weights noted for the system are applied, there is at least one other system (or a linear combination of other systems) whose performance is better. Columns can be sorted from high to low by clicking on the column header. Results shown are for games on or before December 2, 2017 using rankings posted through the games of the respective preceding week. Note that the system abbreviations are the same as those used by Massey, who denotes the MinV ranking as "CMV" and the MVP ranking as "MVP." |
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Full Season Last Week
Rnk System Efficiency Retrodictive Predictive Efficiency Retrodictive Predictive
1 GRR 59.71% 2733 (1.00) 218 (.000) 100.0% 581 (.000) 15 (1.00)
2 DII 98.79% 4079 (.090) 535 (.910) 98.50% 588 (.670) 14 (.330)
3 STH 12.54% 574 (1.00) 14 (.000) 96.92% 574 (.670) 14 (.330)
4 JWN 52.33% 2395 (1.00) 180 (.000) 95.90% 565 (.670) 14 (.330)
5 WIL 86.32% 3951 (1.00) 363 (.000) 97.23% 597 (.690) 13 (.310)
6 SOR 82.57% 3583 (.090) 445 (.910) 97.12% 596 (.690) 13 (.310)
7 BIH 86.02% 3937 (1.00) 367 (.000) 97.00% 595 (.690) 13 (.310)
8 EZ 81.21% 3717 (1.00) 327 (.000) 97.00% 595 (.690) 13 (.310)
9 AND 54.95% 2515 (1.00) 178 (.000) 97.00% 595 (.690) 13 (.310)
10 KRA 36.12% 1653 (1.00) 97 (.000) 97.00% 595 (.690) 13 (.310)
11 ABC 81.12% 3713 (1.00) 331 (.000) 96.78% 593 (.690) 13 (.310)
12 WOB 35.83% 1640 (1.00) 95 (.000) 96.78% 593 (.690) 13 (.310)
13 PGH 95.83% 4198 (.090) 516 (.910) 96.67% 592 (.690) 13 (.310)
14 ISR 80.84% 3700 (1.00) 328 (.000) 96.67% 592 (.690) 13 (.310)
15 WOL 69.87% 3198 (1.00) 258 (.000) 96.67% 592 (.690) 13 (.310)
16 RTH 69.83% 3196 (1.00) 257 (.000) 96.55% 591 (.690) 13 (.310)
17 DOL 88.60% 4055 (1.00) 399 (.000) 96.44% 590 (.690) 13 (.310)
18 VRN 75.66% 3463 (1.00) 291 (.000) 96.44% 590 (.690) 13 (.310)
19 FMG 85.16% 3898 (1.00) 373 (.000) 96.33% 589 (.690) 13 (.310)
20 KNT 69.22% 3168 (1.00) 260 (.000) 96.33% 589 (.690) 13 (.310)
21 RUD 98.62% 4160 (.090) 533 (.910) 96.21% 588 (.690) 13 (.310)
22 COL 88.44% 4048 (1.00) 431 (.000) 96.21% 588 (.690) 13 (.310)
23 SEL 81.47% 3729 (1.00) 337 (.000) 96.21% 588 (.690) 13 (.310)
24 JNK 85.14% 3897 (1.00) 364 (.000) 96.10% 587 (.690) 13 (.310)
25 BOW 70.59% 3231 (1.00) 295 (.000) 96.10% 587 (.690) 13 (.310)
26 PPP 92.72% 4082 (.090) 499 (.910) 95.99% 586 (.690) 13 (.310)
27 CSL 87.00% 3982 (1.00) 424 (.000) 95.99% 586 (.690) 13 (.310)
28 MRK 80.45% 3682 (1.00) 329 (.000) 95.99% 586 (.690) 13 (.310)
29 PIR 98.35% 4109 (.090) 532 (.910) 95.87% 585 (.690) 13 (.310)
30 HKB 84.66% 3875 (1.00) 374 (.000) 95.76% 584 (.690) 13 (.310)
31 ASH 80.53% 3686 (1.00) 342 (.000) 95.76% 584 (.690) 13 (.310)
32 MvG 80.40% 3680 (1.00) 327 (.000) 95.76% 584 (.690) 13 (.310)
33 RWP 95.35% 4050 (.090) 515 (.910) 95.65% 583 (.690) 13 (.310)
34 ACU 88.81% 4065 (1.00) 460 (.000) 95.65% 583 (.690) 13 (.310)
35 WEL 84.68% 3876 (1.00) 361 (.000) 95.65% 583 (.690) 13 (.310)
36 GBE 68.71% 3145 (1.00) 254 (.000) 95.65% 583 (.690) 13 (.310)
37 Con 98.88% 4122 (.090) 535 (.910) 95.54% 582 (.690) 13 (.310)
38 HAT 94.84% 4128 (.090) 511 (.910) 95.54% 582 (.690) 13 (.310)
39 LSD 88.55% 4053 (1.00) 459 (.000) 95.54% 582 (.690) 13 (.310)
40 BSS 86.34% 3952 (1.00) 402 (.000) 95.54% 582 (.690) 13 (.310)
41 WLK 82.81% 3790 (1.00) 379 (.000) 95.54% 582 (.690) 13 (.310)
42 KEE 75.11% 3438 (1.00) 303 (.000) 95.54% 582 (.690) 13 (.310)
43 HEN 79.97% 3660 (1.00) 336 (.000) 95.42% 581 (.690) 13 (.310)
44 MJS 74.94% 3430 (1.00) 285 (.000) 95.42% 581 (.690) 13 (.310)
45 KPK 97.30% 4011 (.090) 527 (.910) 95.31% 580 (.690) 13 (.310)
46 OSC 89.60% 3557 (.080) 487 (.920) 95.31% 580 (.690) 13 (.310)
47 COF 80.14% 3668 (1.00) 341 (.000) 95.31% 580 (.690) 13 (.310)
48 WWP 45.12% 2065 (1.00) 139 (.000) 95.31% 580 (.690) 13 (.310)
49 MDS 74.46% 3408 (1.00) 289 (.000) 95.20% 579 (.690) 13 (.310)
50 SMS 99.67% 4018 (.080) 541 (.920) 95.08% 578 (.690) 13 (.310)
51 KEL 95.71% 4057 (.090) 517 (.910) 95.08% 578 (.690) 13 (.310)
52 GLD 74.90% 3428 (1.00) 290 (.000) 95.08% 578 (.690) 13 (.310)
53 MTN 61.85% 2831 (1.00) 222 (.000) 95.08% 578 (.690) 13 (.310)
54 HOW 96.18% 4041 (.090) 520 (.910) 94.97% 577 (.690) 13 (.310)
55 FAS 84.12% 3850 (1.00) 375 (.000) 94.97% 577 (.690) 13 (.310)
56 JTR 86.24% 3947 (1.00) 411 (.000) 94.86% 576 (.690) 13 (.310)
57 HNL 78.41% 3589 (1.00) 339 (.000) 94.86% 576 (.690) 13 (.310)
58 PAY 97.83% 4102 (.090) 529 (.910) 94.74% 575 (.690) 13 (.310)
59 LAZ 97.63% 4088 (.090) 528 (.910) 94.52% 573 (.690) 13 (.310)
60 KEN 79.05% 3618 (1.00) 329 (.000) 94.41% 572 (.680) 13 (.320)
61 MAR 95.41% 3997 (.090) 516 (.910) 94.18% 570 (.680) 13 (.320)
62 YCM 74.87% 3427 (1.00) 327 (.000) 94.18% 570 (.680) 13 (.320)
63 CGV 96.85% 3958 (.090) 525 (.910) 93.50% 564 (.680) 13 (.320)
64 MAS 97.80% 4089 (.090) 529 (.910) 94.15% 590 (.710) 12 (.290)
65 BIL 98.38% 4125 (.090) 532 (.910) 93.81% 587 (.710) 12 (.290)
66 RME 84.33% 3860 (1.00) 363 (.000) 93.36% 583 (.710) 12 (.290)
67 DWI 97.38% 4050 (.090) 527 (.910) 93.25% 582 (.710) 12 (.290)
68 ENG 95.30% 4023 (.090) 515 (.910) 93.25% 582 (.710) 12 (.290)
69 SGR 78.50% 3593 (1.00) 335 (.000) 93.25% 582 (.710) 12 (.290)
70 MGS 94.51% 4132 (.090) 509 (.910) 93.13% 581 (.710) 12 (.290)
71 BMC 75.01% 3117 (.090) 406 (.910) 93.13% 581 (.710) 12 (.290)
72 RT 83.79% 3835 (1.00) 381 (.000) 92.91% 579 (.700) 12 (.300)
73 BCM 65.94% 3018 (1.00) 302 (.000) 92.68% 577 (.700) 12 (.300)
74 HUF 34.91% 1598 (1.00) 98 (.000) 92.57% 576 (.700) 12 (.300)
75 NUT 93.28% 3866 (.090) 505 (.910) 92.46% 575 (.700) 12 (.300)
76 ARG 98.38% 4046 (.090) 533 (.910) 92.34% 574 (.700) 12 (.300)
77 KAM 98.14% 3930 (.080) 533 (.920) 92.34% 574 (.700) 12 (.300)
78 KLK 77.10% 3529 (1.00) 342 (.000) 92.23% 573 (.700) 12 (.300)
79 LAB 67.90% 3108 (1.00) 256 (.000) 92.23% 573 (.700) 12 (.300)
80 RSL 80.05% 3664 (1.00) 374 (.000) 92.12% 572 (.700) 12 (.300)
81 BBT 95.54% 3976 (.090) 517 (.910) 92.00% 571 (.700) 12 (.300)
82 MGN 79.13% 3622 (1.00) 333 (.000) 91.89% 570 (.700) 12 (.300)
83 LMC 75.09% 3437 (1.00) 341 (.000) 91.78% 569 (.700) 12 (.300)
84 NGS 50.27% 2301 (1.00) 231 (.000) 91.10% 563 (.700) 12 (.300)
85 FEI 85.46% 3754 (.090) 460 (.910) 90.87% 561 (.700) 12 (.300)
86 TFG 34.08% 1560 (1.00) 103 (.000) 90.42% 557 (.700) 12 (.300)
87 S&P 80.99% 3707 (1.00) 434 (.000) 89.97% 553 (.690) 12 (.310)
88 CMV 100.0% 4577 (.950) 536 (.050) 100.0% 662 (1.00) 11 (.000)
89 RTB 93.31% 4271 (1.00) 359 (.000) 99.43% 657 (.750) 11 (.250)
90 RTP 95.34% 4125 (.090) 514 (.910) 92.31% 594 (.730) 11 (.270)
91 PCP 84.51% 3868 (1.00) 375 (.000) 91.98% 591 (.730) 11 (.270)
92 REW 69.46% 3179 (1.00) 255 (.000) 91.30% 585 (.720) 11 (.280)
93 DOK 100.0% 3932 (.000) 544 (1.00) 90.39% 577 (.720) 11 (.280)
94 TRP 72.56% 3321 (1.00) 303 (.000) 90.28% 576 (.720) 11 (.280)
95 DEZ 96.25% 3996 (.090) 521 (.910) 90.17% 575 (.720) 11 (.280)
96 BWE 98.59% 3983 (.080) 535 (.920) 89.94% 573 (.720) 11 (.280)
97 FPI 99.53% 3947 (.080) 541 (.920) 89.71% 571 (.720) 11 (.280)
98 BRN 99.37% 3952 (.080) 540 (.920) 89.71% 571 (.720) 11 (.280)
99 TPR 92.57% 3849 (.090) 501 (.910) 89.15% 566 (.720) 11 (.280)
100 YAG 82.35% 3059 (.000) 448 (1.00) 88.47% 560 (.720) 11 (.280)
101 PFZ 88.85% 3600 (.080) 482 (.920) 88.25% 558 (.710) 11 (.290)
102 SFX 77.58% 3551 (1.00) 374 (.000) 88.13% 557 (.710) 11 (.290)
103 RBA 33.58% 1537 (1.00) 97 (.000) 87.91% 555 (.710) 11 (.290)
104 MCK 80.10% 3666 (1.00) 294 (.000) 94.71% 627 (1.00) 10 (.000)
105 ATC 39.17% 1793 (1.00) 166 (.000) 88.56% 581 (.740) 10 (.260)
106 SAG 97.95% 4001 (.090) 531 (.910) 88.44% 580 (.740) 10 (.260)
107 CTW 96.03% 3971 (.090) 520 (.910) 88.33% 579 (.740) 10 (.260)
108 PIG 99.17% 4019 (.080) 538 (.920) 87.88% 575 (.740) 10 (.260)
109 DES 97.62% 4006 (.090) 529 (.910) 87.88% 575 (.740) 10 (.260)
110 BAS 89.73% 3863 (.090) 484 (.910) 87.20% 569 (.740) 10 (.260)
111 LOG 96.33% 3954 (.090) 522 (.910) 86.86% 575 (1.00) 9 (.000)
112 DCI 97.62% 4005 (.090) 529 (.910) 86.71% 574 (1.00) 9 (.000)
113 BDF 97.16% 3867 (.080) 528 (.920) 84.89% 562 (1.00) 9 (.000)
114 MOR 96.97% 3933 (.080) 526 (.920) 85.35% 565 (1.00) 8 (.000)
115 PIT 68.39% 3130 (1.00) 365 (.000) . . (. ) . (. )
116 DUN 51.93% 2164 (.090) 281 (.910) . . (. ) . (. )
117 KH 44.19% 2010 (.100) 237 (.900) . . (. ) . (. )
118 CI 32.82% 1502 (1.00) 163 (.000) . . (. ) . (. )
119 SP 29.56% 1308 (.090) 159 (.910) . . (. ) . (. )
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B. Jay Coleman, Ph.D. Richard deR. Kip Professor of Operations Management & Quantitative Methods Department of Management | Coggin College of Business | University of North Florida | Jacksonville, FL 32224 jcoleman@unf.edu Disclaimer |
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