James d. mccaffrey software research, development, testing, and education

I think there could be a connection between Fantasy Football and machine learning, but I’m not sure. I am sure that tens of millions of people play fantasy sports. To investigate, I created a Fantasy Football league using the ESPN system. I really don’t like ESPN as a company (they push an obnoxious political-racial agenda on several of their shows) but they’re one of the major providers along with Yahoo and NFL. And I used the free version so I’m not giving ESPN any money.

I used all the default settings. Each team has 16 players. For a given week you set 9 players as starters and put 7 players on the bench. Each Fantasy Team is matched against another in the league. Each team get points depending on the performance of the players in real NFL games played that week.

I used Standard Scoring which gives 6 points for a quarterback who throws a touchdown pass, 1 point for every 25 yard gained by a running back, etc. etc.

To select the 16 players for each team, I used the system’s “Autopick” feature. I set up rules for each team for what player to pick in each round/turn. For example, for one team I specified: round 1 = best quarterback available, round 2 = best running back available, round 3 = best kicker available, rounds 4 to 16 = best available player, any position. The rules have minimum and maximum number of players at each position.

1. Zoltar suggests a bet on the Steelers against the Browns. The early Vegas line has the Steelers as 6-point favorites over the Browns. Zoltar thinks the Steelers are 11 points better than the Browns. A bet on the Steelers will pay off only if the Steelers win by more than 6 points (in other words, 7 points or more). If the Steelers win by exactly 6 points, the bet is a push.

In all these games, Zoltar likes the favored team, thinking the favorite will cover the spread as the saying goes — win by more than the point spread. I suspect this is a consequence that hope springs eternal, meaning that fans of a bad team are overly optimistic that personnel changes that occurred during the off-season will improve their team more than what will actually occur. So these optimistic fans bet on their teams, which skews the point spread. Later in the season, Zoltar shows a bias towards picking Vegas underdog teams, where a bet wins if the underdog wins outright or if the favored team fails to cover the spread.

6. Microsoft Ready – Internal Microsoft and by-invitation-only. Intended for people in sales, support, and other customer-facing roles. About 28,000 attendees. Current incarnation dates from 2017. Combined earlier TechReady (2005-2017), S4 (Solution Specialist Sales Summit), MGX (Microsoft Global Exchange), and Inspire (formerly Microsoft Worldwide Partner Conference, 2002-2017).

Years ago (say, before 1995), physically attending conferences was a critically important way to get technical information. Realistically, the Internet can now deliver any content. But in my opinion physically attending a conference has at last three advantages over the Internet. First, at a conference you can get very valuable information that emerges from impromptu conversations with other attendees. Second, you can often infer subjective trends, not from what people say, but rather, how they say it. Third, attending a conference recharges your mental batteries and when you return to your workplace, you have renewed enthusiasm and energy, which translates to increased productivity and creativity.

For me personally, staying ahead of trends in machine learning is extremely important. One of the things I do at my company is review project proposals. Accepted projects then get a lot of support, in terms of time and money. Not too surprisingly, picking good project ideas is critical for success. There have been many times where some information I gained while at a conference helped me select a project proposal that wasn’t impressive at first thought, but one that eventually turned out to be very successful.