2016 NCAA Football Standings #2 – (post-Week 4)

One of the features of a model like this – where strength of schedule is being sorted out as results get added – is that the fluctuations will be very large now, and then get incrementally smaller.  Did last week’s #1, Alabama really deserve to be knocked all the way out of “playoff” range?  Well, while they added a flimsy opponent in Kent State, thus making their four wins over USC (#32), Western Kentucky (#68), Ole Miss (#22) and Kent State (#119) come out to an average place of #60.

As a point of comparison, Stanford’s 3 wins are over Kansas State (#17), USC (#32) and UCLA (#20) – so as of now with current info, Stanford’s results are better.  Even if you look at SEC teams, Texas A&M’s wins are UCLA (#20), Arkansas (#33), Auburn (#34) and some non-FBS (#123) , so again a better SoS (and both teams have true road wins to brag about).  That said, if you want a forward looking indicator, the Top 4 teams by point margin relative to opponents (the thing we use in SoS calculations) are Ohio State, Louisville, Stanford and Alabama.

W L Pts Scale SOS Rank
1 Stanford 3 0 0.6009 1.000 0.6009 7
2 Ohio State 3 0 0.5122 0.930 0.5122 15
3 Clemson 4 0 0.4907 0.913 0.4907 23
4 Texas A&M 4 0 0.4807 0.905 0.4807 24
5 Tennessee 4 0 0.4750 0.900 0.4750 25
6 Alabama 4 0 0.4714 0.897 0.4714 28
7 Boise State 3 0 0.4487 0.879 0.4487 35
8 Houston 4 0 0.4480 0.879 0.4480 37
9 Louisville 4 0 0.4291 0.864 0.4291 41
10 Wisconsin 4 0 0.4006 0.841 0.4006 52
11 Nebraska 4 0 0.3816 0.826 0.3816 62
12 Wake Forest 4 0 0.3694 0.816 0.3694 68
13 Florida State 3 1 0.3649 0.813 0.6149 5
14 Miami-FL 3 0 0.3617 0.810 0.3617 75
15 Western Michigan 4 0 0.3505 0.801 0.3505 82
16 West Virginia 3 0 0.3402 0.793 0.3402 87
17 Michigan 4 0 0.3183 0.776 0.3183 96
18 Arizona State 4 0 0.3183 0.776 0.3183 97
19 Colorado 3 1 0.2760 0.742 0.5260 10
20 Navy 3 0 0.2746 0.741 0.2746 110
21 Georgia 3 1 0.2739 0.741 0.5239 11
22 Utah 4 0 0.2652 0.734 0.2652 112
23 Maryland 3 0 0.2615 0.731 0.2615 113
24 Arkansas 3 1 0.2524 0.724 0.5024 19
25 Air Force 3 0 0.2517 0.723 0.2517 117
26 Minnesota 3 0 0.2467 0.719 0.2467 119
27 San Diego State 3 0 0.2355 0.710 0.2355 121
28 Baylor 4 0 0.2243 0.701 0.2243 122
29 Toledo 3 0 0.1820 0.668 0.1820 126
30 Washington 3 0 0.1795 0.666 0.1795 127
31 Memphis 3 0 0.1583 0.649 0.1583 129
32 Tulsa 3 1 0.1547 0.646 0.4047 50
33 Central Michigan 3 1 0.1408 0.635 0.3908 56
34 UCLA 2 2 0.1359 0.631 0.6359 4
35 Troy 3 1 0.1358 0.631 0.3858 59
36 Ball State 3 1 0.1247 0.622 0.3747 65
37 Georgia Tech 3 1 0.1247 0.622 0.3747 66
38 Virginia Tech 3 1 0.1242 0.622 0.3742 67
39 North Carolina 3 1 0.1154 0.615 0.3654 73
40 Appalachian State 2 2 0.1058 0.607 0.6058 6
41 South Florida 3 1 0.1028 0.605 0.3528 81
42 Georgia Southern 3 1 0.0982 0.601 0.3482 83
43 Eastern Michigan 3 1 0.0834 0.589 0.3334 91
44 Cincinnati 3 1 0.0810 0.588 0.3310 92
45 Kansas State 2 1 0.0807 0.587 0.4141 46
46 Florida 3 1 0.0805 0.587 0.3305 93
47 MTSU 3 1 0.0722 0.581 0.3222 95
48 Michigan State 2 1 0.0589 0.570 0.3922 55
49 Texas Tech 2 1 0.0486 0.562 0.3820 61
50 Oklahoma 1 2 0.0239 0.542 0.6906 1
51 TCU 3 1 0.0206 0.540 0.2706 111
52 Penn State 2 2 0.0171 0.537 0.5171 13
53 Ole Miss 2 2 0.0041 0.527 0.5041 18
54 Southern Miss 3 1 0.0019 0.525 0.2519 116
55 Texas State 1 2 -0.0030 0.521 0.6636 2
56 NC State 2 1 -0.0189 0.508 0.3144 99
57 Syracuse 2 2 -0.0276 0.501 0.4724 26
58 Texas 2 1 -0.0284 0.501 0.3050 102
59 South Carolina 2 2 -0.0288 0.501 0.4712 29
60 Auburn 2 2 -0.0294 0.500 0.4706 30
61 Idaho 2 2 -0.0347 0.496 0.4653 31
62 Army 3 1 -0.0399 0.492 0.2101 123
63 Akron 2 2 -0.0428 0.489 0.4572 33
64 California 2 2 -0.0515 0.482 0.4485 36
65 East Carolina 2 2 -0.0521 0.482 0.4479 38
66 Oregon 2 2 -0.0580 0.477 0.4420 39
67 LSU 2 2 -0.0583 0.477 0.4417 40
68 Iowa 3 1 -0.0670 0.470 0.1830 125
69 Oklahoma State 2 2 -0.0712 0.467 0.4288 42
70 Vanderbilt 2 2 -0.0726 0.466 0.4274 43
71 Old Dominion 2 2 -0.0772 0.462 0.4228 44
72 Arizona 2 1 -0.0810 0.459 0.2524 115
73 Indiana 2 1 -0.0825 0.458 0.2509 118
74 Pittsburgh 2 2 -0.0837 0.457 0.4163 45
75 Colorado State 2 2 -0.0876 0.454 0.4124 47
76 USC 1 3 -0.0957 0.447 0.6543 3
77 Boston College 2 2 -0.1003 0.444 0.3997 53
78 Duke 2 2 -0.1113 0.435 0.3887 57
79 Wyoming 2 2 -0.1122 0.434 0.3878 58
80 Western Kentucky 2 2 -0.1163 0.431 0.3837 60
81 LA-Lafayette 2 2 -0.1203 0.428 0.3797 63
82 UCF 2 2 -0.1331 0.418 0.3669 69
83 SMU 2 2 -0.1394 0.413 0.3606 76
84 Ohio 2 2 -0.1471 0.407 0.3529 80
85 Kentucky 2 2 -0.1558 0.400 0.3442 84
86 South Alabama 2 2 -0.1561 0.399 0.3439 85
87 LA-Monroe 1 2 -0.1562 0.399 0.5105 16
88 Rutgers 2 2 -0.1623 0.395 0.3377 89
89 Missouri 2 2 -0.1654 0.392 0.3346 90
90 Purdue 2 1 -0.1677 0.390 0.1657 128
91 Utah State 2 2 -0.1754 0.384 0.3246 94
92 Tulane 2 2 -0.1846 0.377 0.3154 98
93 Marshall 1 2 -0.1948 0.369 0.4719 27
94 Mississippi State 2 2 -0.2029 0.362 0.2971 104
95 Oregon State 1 2 -0.2067 0.359 0.4600 32
96 Connecticut 2 2 -0.2073 0.359 0.2927 107
97 Nevada 2 2 -0.2190 0.350 0.2810 109
98 BYU 1 3 -0.2318 0.339 0.5182 12
99 Bowling Green 1 3 -0.2350 0.337 0.5150 14
100 North Texas 2 2 -0.2417 0.332 0.2583 114
101 Louisiana Tech 1 3 -0.2458 0.328 0.5042 17
102 Hawaii 1 3 -0.2508 0.324 0.4992 20
103 Fresno State 1 3 -0.2550 0.321 0.4950 21
104 Florida Atlantic 1 3 -0.2555 0.321 0.4945 22
105 Temple 2 2 -0.2565 0.320 0.2435 120
106 Charlotte 1 3 -0.2960 0.289 0.4540 34
107 Illinois 1 2 -0.3013 0.284 0.3654 72
108 Kansas 1 2 -0.3095 0.278 0.3572 77
109 Other 10 84 -0.3290 0.262 0.5646 8
110 New Mexico State 1 3 -0.3450 0.250 0.4050 49
111 UTSA 1 3 -0.3475 0.248 0.4025 51
112 New Mexico 1 2 -0.3617 0.236 0.3049 103
113 Washington State 1 2 -0.3810 0.221 0.2856 108
114 San Jose State 1 3 -0.3833 0.219 0.3667 70
115 UNLV 1 3 -0.3845 0.218 0.3655 71
116 Virginia 1 3 -0.3883 0.215 0.3617 74
117 Northwestern 1 3 -0.3961 0.209 0.3539 79
118 Kent State 1 3 -0.4116 0.197 0.3384 88
119 Massachusetts 1 3 -0.4380 0.176 0.3120 100
120 Georgia State 0 3 -0.4428 0.172 0.5572 9
121 Iowa State 1 3 -0.4444 0.171 0.3056 101
122 UTEP 1 3 -0.4549 0.162 0.2951 105
123 Notre Dame 1 3 -0.4567 0.161 0.2933 106
124 Buffalo 1 2 -0.4775 0.145 0.1892 124
125 Rice 0 4 -0.5940 0.052 0.4060 48
126 Arkansas State 0 4 -0.6055 0.043 0.3945 54
127 FIU 0 4 -0.6226 0.029 0.3774 64
128 Northern Illinois 0 4 -0.6456 0.011 0.3544 78
129 Miami-OH 0 4 -0.6597 0.000 0.3403 86

To turn these into playoff berths – we look at the six champs:

  • SEC – Texas A&M (4)
  • ACC – Clemson (3)
  • Big 12 – West Virginia (16)
  • Big Ten – Ohio State (2)
  • Pac 12 – Stanford (1)
  • Group of Five – Boise State (7) (Boise State wins with more true road wins right now)

Notably we can credibly identify a Top 4, so Stanford, Ohio State, Clemson and Texas A&M are in the playoffs.  We fill the other spots accordingly- remember, this is based on if the season ended right now.

  • Fiesta Bowl (National Semifinal #1): Stanford v Texas A&M
  • Peach Bowl (National Semifinal #2): Ohio State v Clemson
  • Sugar Bowl: Alabama v West Virginia
  • Rose Bowl: Wisconsin v Arizona State
  • Orange Bowl: Louisville v Tennessee
  • Cotton Bowl: Boise State v Nebraska

2016 NCAA Football Standings #1 – (post-Week 3)

Another year is another set of NCAA rankings.  If you want to look at the methodology, it’s here.  Basically we use point margins to determine opponent “strength”, and then use those to adjust win/loss total.

Week 3 – our first week with real SoS data (each team has played two games so there each opponent has played).  The highlights of the show this past week was essentially the Big XII being voted off the playoff island.  (Texas seems like the only possible winner – it’s early but hard for Oklahoma to live that down)  You also saw Alabama, Ohio State and Louisville significantly throwing down.  The first standings are:

W L Pts Scale SOS Rank
1 Alabama 3 0 0.6216 1.000 0.6216 8
2 Ohio State 3 0 0.5543 0.953 0.5543 17
3 Houston 3 0 0.5347 0.939 0.5347 25
4 Stanford 2 0 0.5203 0.929 0.5203 27
5 Georgia 3 0 0.5025 0.916 0.5025 30
6 Central Michigan 3 0 0.4807 0.901 0.4807 35
7 Texas A&M 3 0 0.4619 0.888 0.4619 42
8 Louisville 3 0 0.4456 0.876 0.4456 46
9 Clemson 3 0 0.4395 0.872 0.4395 48
10 Arkansas 3 0 0.4044 0.847 0.4044 58
11 Tennessee 3 0 0.3992 0.843 0.3992 60
12 Michigan State 2 0 0.3972 0.842 0.3972 61
13 Miami-FL 3 0 0.3681 0.822 0.3681 71
14 Wisconsin 3 0 0.3658 0.820 0.3658 75
15 Maryland 3 0 0.3641 0.819 0.3641 79
16 Western Michigan 3 0 0.3624 0.818 0.3624 81
17 Michigan 3 0 0.3432 0.804 0.3432 92
18 Arizona State 3 0 0.3424 0.803 0.3424 93
19 South Florida 3 0 0.3313 0.796 0.3313 97
20 San Diego State 3 0 0.3285 0.794 0.3285 98
21 Navy 3 0 0.3236 0.790 0.3236 99
22 Wake Forest 3 0 0.3184 0.787 0.3184 100
23 Utah 3 0 0.3170 0.786 0.3170 101
24 UCLA 2 1 0.3140 0.783 0.6474 4
25 Boise State 2 0 0.3063 0.778 0.3063 103
26 Indiana 2 0 0.2997 0.773 0.2997 106
27 Baylor 3 0 0.2868 0.764 0.2868 108
28 Georgia Southern 3 0 0.2843 0.763 0.2843 109
29 West Virginia 2 0 0.2825 0.761 0.2825 110
30 Nebraska 3 0 0.2806 0.760 0.2806 111
31 Georgia Tech 3 0 0.2780 0.758 0.2780 112
32 Army 3 0 0.2774 0.758 0.2774 113
33 Minnesota 2 0 0.2545 0.742 0.2545 117
34 Toledo 3 0 0.2361 0.729 0.2361 121
35 Florida State 2 1 0.2359 0.728 0.5692 15
36 South Carolina 2 1 0.2106 0.711 0.5439 23
37 Air Force 2 0 0.2028 0.705 0.2028 122
38 Texas State 1 1 0.1988 0.702 0.6988 2
39 Troy 2 1 0.1930 0.698 0.5264 26
40 Washington 3 0 0.1814 0.690 0.1814 126
41 Florida 3 0 0.1685 0.681 0.1685 127
42 Memphis 2 0 0.1635 0.678 0.1635 128
43 Eastern Michigan 2 1 0.1617 0.676 0.4951 32
44 Western Kentucky 2 1 0.1547 0.671 0.4880 34
45 Colorado 2 1 0.1423 0.663 0.4756 38
46 Ball State 2 1 0.1286 0.653 0.4620 41
47 Kansas State 1 1 0.1234 0.649 0.6234 7
48 Tulsa 2 1 0.1147 0.643 0.4481 44
49 California 2 1 0.1053 0.637 0.4386 49
50 Akron 2 1 0.0989 0.632 0.4323 51
51 SMU 2 1 0.0911 0.627 0.4245 53
52 Oklahoma State 2 1 0.0869 0.624 0.4203 54
53 Texas Tech 2 1 0.0787 0.618 0.4120 55
54 Cincinnati 2 1 0.0782 0.617 0.4115 56
55 MTSU 2 1 0.0671 0.610 0.4005 59
56 East Carolina 2 1 0.0634 0.607 0.3967 62
57 USC 1 2 0.0559 0.602 0.7226 1
58 Wyoming 2 1 0.0546 0.601 0.3879 63
59 Penn State 2 1 0.0418 0.592 0.3751 67
60 Texas 2 1 0.0392 0.590 0.3725 68
61 Utah State 2 1 0.0347 0.587 0.3680 72
62 Colorado State 2 1 0.0322 0.585 0.3655 77
63 Pittsburgh 2 1 0.0287 0.583 0.3621 82
64 North Carolina 2 1 0.0273 0.582 0.3606 83
65 Oregon 2 1 0.0256 0.580 0.3589 84
66 LSU 2 1 0.0230 0.579 0.3564 85
67 Rutgers 2 1 0.0221 0.578 0.3554 86
68 NC State 2 1 0.0204 0.577 0.3537 87
69 Oklahoma 1 2 0.0169 0.574 0.6836 3
70 Virginia Tech 2 1 0.0160 0.574 0.3494 91
71 Southern Miss 2 1 0.0079 0.568 0.3413 94
72 Connecticut 2 1 -0.0181 0.550 0.3153 102
73 Arizona 2 1 -0.0297 0.542 0.3036 104
74 Florida Atlantic 1 2 -0.0471 0.529 0.6195 9
75 LA-Lafayette 2 1 -0.0562 0.523 0.2771 114
76 Nevada 2 1 -0.0673 0.515 0.2661 116
77 Oregon State 1 1 -0.0698 0.513 0.4302 52
78 UNLV 1 2 -0.0722 0.512 0.5944 11
79 TCU 2 1 -0.0798 0.506 0.2536 118
80 BYU 1 2 -0.0887 0.500 0.5779 12
81 Ole Miss 1 2 -0.1020 0.491 0.5647 16
82 LA-Monroe 1 2 -0.1168 0.480 0.5499 18
83 Louisiana Tech 1 2 -0.1178 0.480 0.5489 20
84 Fresno State 1 2 -0.1178 0.479 0.5488 21
85 Appalachian State 1 2 -0.1181 0.479 0.5485 22
86 Syracuse 1 2 -0.1231 0.476 0.5435 24
87 Idaho 1 2 -0.1497 0.457 0.5170 28
88 Old Dominion 1 2 -0.1502 0.457 0.5165 29
89 Boston College 1 2 -0.1654 0.446 0.5013 31
90 UCF 1 2 -0.1754 0.439 0.4913 33
91 Missouri 1 2 -0.1893 0.429 0.4773 36
92 Charlotte 1 2 -0.1895 0.429 0.4771 37
93 South Alabama 1 2 -0.1965 0.424 0.4702 39
94 Hawaii 1 3 -0.2002 0.421 0.5498 19
95 Ohio 1 2 -0.2005 0.421 0.4661 40
96 Bowling Green 1 2 -0.2135 0.412 0.4531 43
97 Auburn 1 2 -0.2194 0.408 0.4473 45
98 Vanderbilt 1 2 -0.2295 0.401 0.4372 50
99 Purdue 1 1 -0.2547 0.383 0.2453 119
100 Marshall 1 1 -0.2556 0.383 0.2444 120
101 San Jose State 1 2 -0.2586 0.380 0.4081 57
102 UTSA 1 2 -0.2810 0.365 0.3856 64
103 Other 8 79 -0.2836 0.363 0.6245 6
104 Iowa 2 1 -0.2857 0.361 0.0476 129
105 Notre Dame 1 2 -0.2895 0.359 0.3771 66
106 New Mexico State 1 2 -0.2943 0.355 0.3723 69
107 New Mexico 1 2 -0.2967 0.354 0.3699 70
108 Tulane 1 2 -0.2993 0.352 0.3674 73
109 Mississippi State 1 2 -0.3009 0.351 0.3657 76
110 UTEP 1 2 -0.3014 0.350 0.3653 78
111 Kansas 1 2 -0.3033 0.349 0.3634 80
112 North Texas 1 2 -0.3137 0.342 0.3530 88
113 Kentucky 1 2 -0.3139 0.341 0.3528 89
114 Duke 1 2 -0.3168 0.339 0.3499 90
115 Temple 1 2 -0.3275 0.332 0.3392 95
116 Massachusetts 1 2 -0.3334 0.328 0.3333 96
117 Rice 0 3 -0.3531 0.314 0.6469 5
118 Illinois 1 2 -0.3670 0.304 0.2997 105
119 Georgia State 0 3 -0.3978 0.282 0.6022 10
120 Washington State 1 2 -0.3988 0.282 0.2679 115
121 Northern Illinois 0 3 -0.4260 0.263 0.5740 13
122 Arkansas State 0 3 -0.4265 0.262 0.5735 14
123 Northwestern 1 2 -0.4660 0.234 0.2007 124
124 Kent State 1 2 -0.4842 0.222 0.1825 125
125 FIU 0 3 -0.5591 0.169 0.4409 47
126 Virginia 0 3 -0.6149 0.130 0.3851 65
127 Iowa State 0 3 -0.6330 0.117 0.3670 74
128 Miami-OH 0 3 -0.7071 0.065 0.2929 107
129 Buffalo 0 2 -0.7990 0.000 0.2010 123

So, with two years of data, we can project the playoff field thusly:

  • The conference champs
    • SEC: Alabama (1)
    • ACC: Louisville (8)
    • Big Ten: Ohio State (2)
    • Big XII: Baylor (27)
    • Pac 12: Stanford (4)
    • REST: Houston (3)
  • Louisville is probably better than Houston – duh.  At the same time, Houston – with a true road and neutral site win have edges in schedule quality for now – especially with so little data on Florida State.  But anyway, there you go.
  • The New Year’s Six
    • Peach Bowl (national semifinal): Alabama v Stanford
    • Fiesta Bowl (national semifinal): Ohio State v Houston
    • Sugar Bowl (Big 12 v SEC): Baylor v Georgia
    • Rose Bowl (Big Ten v Pac-12): Michigan State v Utah
    • Cotton Bowl (at-large): Clemson v Arkansas
    • Orange Bowl (ACC v ND, SEC, Big Ten): Louisville v Texas A&M

Everything I Never Told You

I find myself thinking about the life partner.  I try to avoid biography, and bringing in people into these posts who did not volunteer for such a job, but it still turns over in my mind.  The life partner is one of the the most thoughtful, intelligent, people I know – and had a deep education in the humanities.  She is also a wonderful, thoughtful mother to the children, and this latter vocation has been the full time gig.  There were sound reasons for doing so (aren’t there always), but it is hard not to think of opportunity costs, dreams deferred.  It is not like this has not been discussed and resolved – including assurances that this life is working out well. (even while staring at the Pollock installation our son left on his high chair)  But when (for whatever reason), I am inspired to brood, things like this pop up.

The children also come to mind.  They are too young to have Dreams, and Ideas, and Hopes yet.  But it is not hard to see the future – and hope we don’t push them away, or project some of my own dreams and insecurities onto them.  A bit of this is inevitable I guess – they have to live with me all the time – but that does not mean I don’t fret.  Now these sorts of thoughts do not happen often – but every so often something can stir that up.

Celeste Ng’s Everything I Never Told You is one of those sorts of stories, an autopsy of a tragedy, and how a family is torn apart.  The people here are James and Marilyn Lee, a biracial couple who live in Ohio in 1977, raising three children (Nath, Lydia and Hannah).  On the surface, things are well.  Nath is going to Harvard, Lydia, 15 is fawned over by her parents (and the siblings are not unaware) and Hannah seems pleasant enough.  (this sounds like she’s not as present – which happens a lot)  Mom is a housewife, and Dad is a professor of American Studies at the local university.  When we happen upon the family, we are told that nobody can find Lydia .  It seems innocuous enough, but she is gone for too long.  The family gets worried as the hours turns into days – they report her missing.  And then, suddenly, the local police officer comes to ask them about whether she boated on the lake.  James tells them no, that Lydia did not know how to swim.  But why would the police ask that?

Lydia’s death floors her parents.  She seemed so happy, and popular.  She was on the way to medical school!  She had everything to live for.  The family frantically is trying to figure out what happened.  Nath noticed she hung out with Jack from the neighborhood.  Jack knew a lot of girls – he looks like trouble.  The police are not getting anywhere with leads – and it seems that not many people had talked to Lydia much lately.

Now in a sense, the book proceeds trying to figure out what happened on the lake – but the way Ng presents it, we know, certainly before James and Marilyn do.  But where it really shines is as it goes back in time – all the way back to where James and Marilyn met.  Both of them are outsiders, separately and together.  James is Chinese-American, son of immigrants who lied and snuck into jobs (the way Asian-Americans had to back in the post-war era) determined to make a life for their child.  His father got a custodian job at a boarding school because he read that employees children could attend for free if they qualified.  James was the Asian in a whitebread boarding school, a poor kid among the very definition of entitlement.  James would excel and then go to Harvard and face the same thing.  Indeed it was there as a grad student that he would meet Marilyn, who went to Radcliffe, wanting to become a doctor.  She was fighting, determined to excel is a very very male discipline, and raised by a single mother, a home-ec teacher who never left the house without gloves and studied the Betty Crocker cookbook intently to be able to cook ably for her man.  The two fell in love, perhaps seeing comfort in a fellow outsider – life goes on and when Marilyn gets pregnant, the medical careers gets scuttled to begin life as a mom and housewife.

We see the challenges they face from the start in their own pursuits, and then as an interracial couple in the pre-Loving late 1950s.  Marilyn’s mother at the wedding expresses the sort of sentiment we suspected she had all along about this “Oriental” that Marilyn chose for life.  Ng in particular shows the hurt – and how these incidents shape everything.  For instance, Marilyn’s mother confronts Marilyn – and obviously the exchange is unpleasant, and so Marilyn would never speak to her again.  Could there have been closure if somebody softened up over time?  But also, Marilyn thought the incident occurred out of earshot – but as it turns out, James and the wedding group could hear most everything.  What did he think of it?  How did that sort of snippet of conversation impact how he felt about the whole deal?

The misunderstandings are everywhere.  We see Marilyn’s ambitions to do something in science, and we also see James desperately afraid of losing status when peers think she HAS to work for them to make ends meet.  We see it in the chain of events that are spawned by Marilyn wanting to go back to school.  It’s there with the kids when Nath meets Jack for the first time at the swimming pool, or in Hannah’s habit of taking things.  What Ng does is show each of these misunderstandings – words not said, people not leveling – and how the imperfect knowledge would impact how people though of everything forward.  When we finally get to the scene where Lydia gets on the boat and looks into the lake – it’s hard to see how any of these specific characters in that time and place, could have prevented it from happening.

The effect is an emotional plane crash viewed in slow motion from all sides – in a third person omniscient PoV which takes some getting used to (it felt like there was a lot of foreshadowing, perhaps too much).  When a death occurs, the first instinct is to try to assign blame.  If it is a homicide, who was the killer – in other cases, how did the fire get started, why was she so miserable, etc.  What Ng does so heartbreakingly here is to get close to all of the principals – who all act perfectly reasonably and decently – and show clearly how it all went so wrong, and how the family can possibly bounce back.  The book ends on a tentatively hopeful with the family looking like they might be okay – at least trying – but Ng does not seem certain it will all be fine, and neither do we.

 

The Three Body Problem

Liu Cixin’s The Three Body Problem, the winner of the 2014 Hugo Award for Best Novel, is a novel about Earth’s contact with alien life, as well as the scars of China’s Cultural Revolution in the 1960s, as well as an exploration of the fundamental nature of physics and science.  Cixin’s work bounces between generations, and between solar systems (not always successfully) and weaves a complex, rich, dizzying tale about Us finding Them.

The masterwork in setting up the communique is Ye Wentjie, the daughter of a famous astrophysicist who was killed during a student riot during the Cultural Revolution.  Ye’s father was accused of teaching the theory of relativity, which was seen as dangerous propaganda projecting capitalist values.  The novel opens in 1967, at the scene of the protest where her own mother and sister, assimilated and re-educated by the communists, would hold up the professor as this sort of heretic and ultimately actually do the deed.  Ye is then exiled to the countryside, where she is given the book Silent Spring considered dangerous by Mao’s Communists, and she escapes punishment by agreeing to work at the Red Coast Base on a secret project.

The novel then hops to the present day (or near future), and Wang Miao, an accomplished scientist who runs a nanometrics lab (developing nanomaterial, essentially super strong threads and such), ends up on the radar of the police and army as they want him to infiltrate a special gathering of science elite, a sort of secret society.  This is due to a rash of suicides in the scientific community.  While doing this work, Wang is struck when he sees a countdown timer which would not stop showing in his eyes until he paused his research.  Pulling on strings and he tries to get questions answered, Wang happens onto “The Three Body Problem”, an online virtual reality game about a world where sunrise and sunset cannot be predicted with any sort of accuracy.  In this world, the sun can be in the air for a while, it can burn too hot, or it can disappear, and nobody can figure out how it works.  Wang starts to get into the game and its world, and when he figures out the game’s secret – it leads to a group who has given up on humanity’s ability to save itself at all.

Liu very effectively bounces back and forth between these threads, as we reveals what the Red Coast project was, and its results – and how it led to the Earth-Trisolar Organization.  In his portrayals of the Earth-Trisolar Organization, an organization which has given up on humanity has interesting parallels with Ye giving up on the sorts of things we take for granted within our family and from our society.  The Cultural Revolution destroyed a lot of those receptors – and Cixin is not subtle in pointing this out.  When the story gets into the nuances of the physics, and the devices used by the aliens (devices which operate at the subatomic level) – the idea is fascinating in an old school sci-fi way, but it also does drag.  There are multiple chapters of flashback and straight exposition which brings a very interesting sci-fi story to a halt.  These things are necessary of course, but it is an occupational risk.

Overall, The Three Body Problem is an engaging, fascinating look at a classic sci-fi story.  In a genre where a lot of what you get exposed to is straight white-bread, a Chinese sci-fi story is a welcome change, even translated as this is.

The Boys on the Bus

It is discouraging that despite being a fixture in political and journalism syllabi, not much seems to have been learned in the 44 years since Timothy Crouse’s seminal The Boys on the the Bus took place.  Crouse’s book-length study of the press covering the 1972 presidential election highlights issues with campaign and White House journalism which has largely remained the same (and perhaps gotten worse) since.  While the technological innovations have made things different, and the proliferation of the 24-hour news has made the demands of journalists for content greater – what Crouse discovers has not dated in any meaningful way.  It paints a grim picture of the press, but a sympathetic one.  What has devolved was inevitable.

Crouse at the time worked for Rolling Stone in its fledgling political department.  The big hitter in the politics department was Hunter S. Thompson (who wrote a notable book on the election himself), but for lots of reasons (all quite obvious if you know anything about Thompson) he was not writing factually heavy, meaty “reporting”.  That was Crouse’s bag (along with presumably cleaning up Thompson’s vomit).  While covering the campaign, Crouse decided to turn the eyes towards the press covering the events, to uncover the tendencies and challenges for these (largely) men who had a very very thankless job.

The 1972 Presidential election happened to be a very good election to look at if you were going to study this sort of thing – as Richard Nixon was running for re-election against South Dakota Senator George McGovern.  Nixon, who was elected in 1968 after a remarkable political comeback – was deeply suspicious of the press whom he accused (not without merit) of favoring John F. Kennedy in the 1960 election.  In his 1968 incarnation, Nixon’s strategy – was to rely on statements and news releases and photo ops to announce policy while more or less eliminating access to the press.  He held one of the lowest number of press conferences in history throughout his tenure as president.  Indeed, he apparently never actually campaigned as a candidate and bristled at the notion that he was – there were no debates.  On the other hand, George McGovern’s campaign had it all – McGovern’s aides were former journalists and broke bread with them, he was an upstart candidate who stunned the establishment to get the primary nod, and then fell apart with a Vice Presidential Nominee scandal.

Against this backdrop, Crouse shows a press corps in its tiers and cliques – the national writers, the large papers who do the dailies – the wire services who set the tone for the coverage (more below), the magazine writers and the television reporters.  With the sort of concentrated coverage a candidate – let alone the President – receives, each campaign becomes a very insular bubble.  When combined with the competitive pressures of day to day journalism and actually fairly well intentioned notions of journalistic integrity – what results is a press corps which – in 1972 totally neglected Watergate while covering McGovern much more harshly than they ever covered Nixon.  Crouse explores a lot of themes here which still resonate today:

  • Copying off of the popular kids – in 1972, while most people got their news from newspapers, most towns got their news from the wire.  As such, the Associated Press and UPI reporters had inordinate editorial influence.  Editors were deeply suspicious of ledes that did not align with the AP (and indeed, the AP stories were usually the most immediate ones).
  •  Faux objectivity – From Crouse’s research, most of the reporters actually did like McGovern more.  However, to reconcile this with their sense of objectivity, many reporters were much harder on McGovern.  Additionally, McGovern gave so much more access – there was just more to say.  By comparison, reporters covering Nixon were almost admiring of the professionalism with which Ziegler browbeat them.
  • Pack journalism – You’re not going to get much good information from the folks following a campaign – but the editorial pressure to not be left behind almost forces the reporters to follow and write down the same stuff.  So we get coverage about what the candidates ate – and photo ops.  It is easier to cover the personalities than the issues – and the editors did not want that anyway.  Indeed it seems like the editors were happy to have inside dish, but not for public consumption.
  • The White House Correspondent Capture – The White House Correspondents Association existed in 1972 – according to Crouse almost exclusively to put on the Nerd Prom.  Crouse’s coverage here is particular harsh as he talks of a White House corps which saw themselves as part of the White House itself.  Of course, this describes DC reporting perfectly.  All of these reporters live in town and are so intertwined with the folks they cover – you are left with conventional wisdom because that is all anyone hears.

These themes are infuriating – and Crouse’s coverage of folks readers know (like RW Apple, David Broder) reveal a sort of collective abdication of real reporting in such a way that he vapidity of stuff Chuck Todd says almost seems natural.  They don’t discuss issues because they can’t (even Watergate was broken by folks on the city desk – before Woodward and Bernstein were assimilated by the DC press borg).  At the same time, the book is a pleasure to read throughout – and going behind the scenes about how all this stuff works is consistently engaging, even if it is a bit disspiriting.

 

Mock Tournament – 2015/16 NCAA Men’s Basketball (results thru March 11)

For the whole season I’ve been fitting Bradley-Terry results, and that still holds.  But another consideration is “HOW” you play – and nothing captures that better in a simple way than Ken Pomeroy (and schedule adjusted also).  Giving them equal weight?  I used the “Bradley-Terry” winning percentage as one scale and KenPom’s pythag ratings as another.  Averaging them, how do things change?  We’ll track this the rest of the way.  Automatics in CAPS

REGION A:

  • (1) Kansas v (16) SOUTHERN/FAIRLEIGH DICKINSON
  • (8) Wisconsin v (9) Notre Dame
  • (4) Utah v (13) SOUTH DAKOTA STATE
  • (5) SETON HALL v (12) UNC-WILMINGTON
  • (2) OREGON v (15) GREEN BAY
  • (7) Wichita State v (10) Colorado
  • (3) Xavier v (14) MIDDLE TENNESSEE
  • (6) Texas v (11) USC

REGION B:

  • (1) Villanova v (16) AUSTIN PEAY/HOLY CROSS
  • (8) Texas Tech v (9) Saint Mary’s
  • (4) Indiana v (13) CHATTANOOGA
  • (5) Arizona v (12) STEPHEN F AUSTIN
  • (2) West Virginia v (15) Buffalo
  • (7) Connecticut v (10) Pittsburgh
  • (3) Miami-FL v (14) CAL STATE BAKERSFIELD
  • (6) Iowa v (11) Michigan/Oregon State

REGION C:

  • (1) Virginia v (16) HAMPTON
  • (8) Providence v (9) Vanderbilt
  • (4) Texas A&M v (13) NORTHERN IOWA
  • (5) Baylor v (12) YALE
  • (2) Oklahoma v (15) UNC-ASHEVILLE
  • (7) Gonzaga v (10) VCU
  • (3) Purdue v (14) IONA
  • (6) Duke v (11) South Carolina/Syracuse

REGION D:

  • (1) NORTH CAROLINA v (16) FLORIDA GULF COAST
  • (8) Saint Joseph’s v (9) Cincinnati
  • (4) Iowa State v (13) FRESNO STATE
  • (5) California v (12) HAWAII
  • (2) Michigan State v (15) WEBER STATE
  • (7) Butler v (10) Dayton
  • (3) Kentucky v (14) STONY BROOK
  • (6) Maryland v (11) AR-Little Rock

LAST FOUR IN FIELD OF 64: Pittsburgh, Michigan, VCU, USC

LAST FOUR IN FIELD OF 68: Colorado, South Carolina, Syracuse, Oregon State

FIRST FOUR OUT: Florida, Valparaiso, Kansas State, Florida State

NEXT FOUR OUT: Creighton, Virginia Tech, Georgia Tech, Washington

Mock Tournament – 2015/16 NCAA Men’s Basketball (results thru March 11)

For the whole season I’ve been fitting Bradley-Terry results, and that still holds.  But another consideration is “HOW” you play – and nothing captures that better in a simple way than Ken Pomeroy (and schedule adjusted also).  Giving them equal weight?  I used the “Bradley-Terry” winning percentage as one scale and KenPom’s pythag ratings as another.  Averaging them, how do things change?  We’ll track this the rest of the way.  Automatics in CAPS

REGION A:

  • (1) Kansas v (16) SOUTHERN/FAIRLEIGH DICKINSON
  • (8) Notre Dame v (9) Dayton
  • (4) Arizona v (13) UNC-WILMINGTON
  • (5) Texas A&M v (12) Stephen F Austin
  • (2) Xavier v (15) GREEN BAY
  • (7) WICHITA STATE v (10) San Diego State
  • (3) Oregon v (14) New Mexico State
  • (6) Texas v (11) VCU

REGION B:

  • (1) Villanova v (16) HAMPTON/HOLY CROSS
  • (8) Wisconsin v (9) Saint Mary’s
  • (4) Indiana v (13) Akron
  • (5) Baylor v (12) YALE
  • (2) Michigan State v (15) Middle Tennessee
  • (7) GONZAGA v (10) Michigan
  • (3) Miami-FL v (14) IONA
  • (6) Iowa v (11) USC

REGION C:

  • (1) Virginia v (16) AUSTIN PEAY
  • (8) Texas Tech v (9) Saint Joseph’s
  • (4) Iowa State v (13) SOUTH DAKOTA STATE
  • (5) California v (12) Hawaii
  • (2) Oklahoma v (15) UNC-ASHEVILLE
  • (7) Butler v (10) Pittsburgh
  • (3) Utah v (14) Stony Brook
  • (6) Duke v (11) Colorado/Oregon State

REGION D:

  • (1) North Carolina v (16) FLORIDA GULF COAST
  • (8) Connecticut v (9) Cincinnati
  • (4) Kentucky v (13) CHATTANOOGA
  • (5) Maryland v (12) Arkansas-Little Rock
  • (2) West Virginia v (15) Weber State
  • (7) Providence v (10) Vanderbilt
  • (3) Purdue v (14) NORTHERN IOWA
  • (6) Seton Hall v (11) South Carolina/Syracuse

LAST FOUR IN FIELD OF 64: Pittsburgh, Michigan, VCU, USC

LAST FOUR IN FIELD OF 68: Colorado, South Carolina, Syracuse, Oregon State

FIRST FOUR OUT: Florida, Valparaiso, Kansas State, Florida State

NEXT FOUR OUT: Creighton, Virginia Tech, Georgia Tech, Washington