HFA is great but I think they lose those games anyway (partly because NU doesn't really have much "HFA" anyway). Having tOSU and UW at home is likely a curse disguised as a blessing. That schedule looks like an out-and-out nightmare to me. I know that Northwestern has an odd knack for following up a terrible season (like last year) with a great one but I just don't see it this year. If they can pull that off then 4-2 in divisional games will get the job done for them provided that the other teams are equal enough to each absorb a couple losses inter-divisionally. I think that is a big advantage because they are the only B1G-W team with a pretty good chance to go 3-0 against the B1G-E.
Purdue: vsPSU, vsUNL, vsIA, Wisconsin: vsPU, vsMN, vsIL, is the only B1G-W team not visiting Ann Arbor, Columbus, or State College this year.Northwestern: vstOSU, vsUW, vsUNL, vsIL.Nebraska: vsUW, vsMN, vsIL, vsIU, vsNU.Illinois: vsMSU, vsIA, vsPU, vsMN, Iowa: vsM, vsUW, vsUNL, Minnesota: vsIA, vsPU, vsRU, vsNU.I've organized this in roughly what I preliminarily think will be the order of difficulty to win (taking both opponent and H/A into account) but the teams are simply organized alphabetically: So, without further ado here are all seven B1G-W teams' league schedules with their five away games and four home games. As soon as next year they could all be thrown in with the B1G-E which would undoubtedly diminish their chances of making it. With the impending end of divisions, 2022 might be the best chance that several B1G-W teams ever have of getting to the CG.
Read an excerpt and interview with Andrew Guthrie Ferguson in The Economist.Since I already launched into this in another thread I thought I'd expand on it here. The Rise of Big Data Policingis a must read for anyone concerned with how technology will revolutionize law enforcement and its potential threat to the security, privacy, and constitutional rights of citizens. These new technologies also offer data-driven methods to improve police accountability and to remedy the underlying socio-economic risk factors that encourage crime.
In this first book on big data policing, Ferguson offers an examination of how new technologies will alter the who, where, when and how we police.
#RACR DIVISION SERIES#
After a series of high-profile police shootings and federal investigations into systemic police misconduct, and in an era of law enforcement budget cutbacks, data-driven policing has been billed as a way to "turn the page" on racial bias.īut behind the data are real people, and difficult questions remain about racial discrimination and the potential to distort constitutional protections. The Rise of Big Data Policingintroduces the cutting-edge technology that is changing how the police do their jobs and shows why it is more important than ever that citizens understand the far-reaching consequences of big data surveillance as a law enforcement tool.Īndrew Guthrie Ferguson reveals how these new technologies -viewed as race-neutral and objective-have been eagerly adopted by police departments hoping to distance themselves from claims of racial bias and unconstitutional practices.
#RACR DIVISION SOFTWARE#
This is just a glimpse into a future where software predicts future crimes, algorithms generate virtual "most-wanted" lists, and databanks collect personal and biometric information. In a high-tech command center in downtown Los Angeles, a digital map lights up with 911 calls, television monitors track breaking news stories, surveillance cameras sweep the streets, and rows of networked computers link analysts and police officers to a wealth of law enforcement intelligence. The consequences of big data and algorithm-driven policing and its impact on law enforcement Winner, 2018 Law & Legal Studies PROSE Award
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