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Different Ways to Create (Notes from June 10 – June 16, 2019) July 3, 2019

Posted by Anthony in Digital, experience, finance, Founders, global, Hiring, Leadership, NFL, questions, social, Strategy, training, Uncategorized, WomenInWork.
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3 fantastic sounding women to start. One in VC and finance, discussing the difference between NYC and SF for her. The second compared in-house marketing strategy and outside influence. What’s that look like? How much control is there? Last, but certainly not least, was an author who discusses something that I’ve seen with family and my sister – the challenge of raising a child while balancing some semblance of normalcy in work. What’s expected from yourself? What should be reasonably expected from work? What’s a balance?

Those women: Erin Glenn, Julie Scelzo and Lauren Smith Brody.

A few sportsmen discussed data and capital. Sixers Innovation Lab and former exec for And1 mentioned how they think about growth in Philadelphia and the brand, who can they support in the community that can also help with the team. John Urschel, former Baltimore Raven, is a published mathematician now who discussed the influx of data collection and analysis among all sports and teams. What they can do makes a great athlete experience, fan experience and overall performance improves.

A plethora of rising stars followed, from Kanyi of Collaborative Fund to Sofia Colucci of Coors and the co-founders for SHINE text. Hope you enjoy my notes and you check out the podcast episodes!

  • Erin Glenn (@leeeringlenn), CEO of Quire (20min VC FF025)
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    • Entrepreneur as kid – day business for summer camps, then management consulting, IB and took a company public (econ consulting firm)
    • Got bug to start own thing in 2010 – joined KIXEYE in SF for 4 years, video game company
    • Wanted to go to NYC (as kid in OK) – went to meet w Betaworks, fell in love with Quire
      • Mutual conv to join Quire – loved it – equity crowdfund co
      • Venture-back co’s enabling portion to raise for community & mission
        • Min. investment is $2500 – supporting larger investments as well, up to $250k
    • Likelihood for investors to get taken advantage of – Title III discussion (investors with <$100k income/net worth can invest up to $2k or 5% of income)
    • Mattermark study on investor bases that exist and why people do invest
      • Investor and diversity – minority, gender, big differences in those that follow Mattermark or others
    • Crowd won’t provide scaling / grow money (the $50mil+ rounds), but community can help participation at a lower level
    • Motivation to invest, other than financial incentive – supporting company’s mission + founders, spurring economic growth + innovation
      • Real commitment to realize dreams, grow economy
    • Benefits with crowd investing for company – moral and psychological
      • Supporters of the company can invest, which is reinforcing for doing it – customers that are owners of the business spend more, loyal, etc
    • SF vs NY startup ecosystems and CEO role
      • Had joined Quire with 2 suitcases, dog and air mattress after 2 days there
      • CEO role – really fun and exhilarating with challenges daily, gained confidence at eliciting feedback from ideas
        • Coming up with better solutions and getting them to help because we don’t have all answers
      • Intensity and vibrancy, competitive spirit in NY even though it’s smaller-feeling
        • Want to take on SV and not give up the competitiveness
        • More female founders in NY – fashion, finance, media in senior executives trying new things
    • Favorite book: Magic Mountain ahead of WWII in Europe, Switzerland
    • Favorite blog: Fred Wilson’s and Tim Cook as favorite innovator
    • Gimlet Media (first investment), Kano, Duel as others
  • Julie Scelzo, executive creative director at McGarryBowen (Wharton XM)
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    • Talking about marketing difference between in house and outside
      • Going from Creative MD for Pandora to take on MGB AMEX
    • Moving from agency to internal at Facebook – not even a salary bump, but just felt right
      • Worked helping clients was rewarding but she missed creating
  • Lauren Smith Brody, author of The Fifth Trimester (Wharton XM)
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    • Discussion of parental leave in the workplace – if uneven with your partner, mixing it up or staggering
    • First 6 months as crucial for development – how to best alleviate this
      • Every person is different and has different attitudes
      • Nobody can generally be told how something may feel for them
    • Having the partner available in the first 6-9 months provides evidence that they’re capable, and can understand some of processes
    • First day of work being scary – moreso as a parent – train whole life to be in workplace
      • Can be comforting back at work, not so much for first days as a parent
  • Dilip Goswami, Molekule Air Filters (Wharton XM)
    • Being his father’s son, a typical engineer
    • Developing and deciding what part of product to have in house vs outside
      • Hybrid model
    • Having customer support and knowing it worked – shipping and using that as validation
  • Seth Berger, founder and CEO of And1, Sixers Innovation Lab (Wharton XM)
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    • Discussing how coaching basketball to young adults was so helpful
    • Marrying And1 with his passion for basketball and teaching and being around it
    • Sixers Innovation Lab – knew Josh from the 90s working on a failed internet co originally
      • Helping with capital up to $1mn and seeing 10x returns so far
  • John Urschel (@johnCurschel), Former lineman with Ravens, MIT mathematician (Wharton XM)
    • Talking about the lifelong balance of math / football from his memoir
    • Thinking about where analytics may be super exciting in sports – real-time strategy if they’re allowed the computers / data on-field/court
      • Tracking data is so strong, it’d be interesting to see what coaches may do to get there
  • Nathan Furr, Curtis Lefrandt, Innovation Capital author (Wharton XM)
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    • Author discussing how innovation costs resources
    • Talking with Marc Benioff and others for the most innovative leaders

 

 

 

 

  • Sofia Colucci, VP Innovation of Miller Coors (Measured Thoughts, Wharton)
    • Introducing a new brand, Cape Line, into the world
      • Usually a 1.5 – 2 year process for a corp this size
      • Cut it down and released in 2019, dropped the other project (Project Sprint)
    • Had already done market research, wanted a more healthy, alternative to beer for women – cocktails in a can
      • Packaging and what that would look like after tasting
  • Jennifer Pryce (@jennpryce), President CEO of Calvert Impact Capital (Wharton XM)
    • Impact capital and how they grade different companies on the degrees for investment
    • Infrastructure, seeing them surpass $1bn
  • Marah Lidey (@marahml), Naomi Hirabayashi, co-founders of SHINE app (Wharton XM)
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    • SHINE as a wellness app for meditation
      • Gaining ground with their superusers – seeking feedback
    • Self-care platform, weren’t sure how they attracted so many men – but it’s definitely catered to their experiecne
      • Reached out to one of the first superusers that was male to get his input and to have influencers help
    • Product-market fit and development was always based on how they wanted the app to be- what they were searching for
  • Kanyi Maqubela (@km), Partner @ Collaborative Fund (20min VC 094)
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    • From South Africa originally, investments into CodeAcademy, Reddit, AngelList, AltSchool, TaskRabbit
    • Founding employee of Doostang, attended Stanford Uni & worked on Obama campaign in 2008, as well
      • Dropped out of Stanford, compelled by interest to see other part of world – did a startup, $20mil of VC funding for a couple startups
        • Being young, decision to leave was easy but once he’d left, it was tough
        • Making friendships and lasting connections easily in college – some communities outside, in pro world, was rough
      • Met his partner, Craig, while finishing school and doing work in design – convinced him to help him with CF
    • Investors are those that believe in collaborative economy – nodes, peer-to-peer and nodes for networking
      • Every consumer/employee/companies have obligation to align interests and value sets
      • Looking at companies to focus on impact and values – aspirational culture as outcome of collaboration
    • For the fund – stage specialization or theme?
      • Theme may be time-efficient-oriented. Reminder that many of most successful people have skipped on massive wins multiple times over.
        • Altman mentioned about having a point of view and heuristic to drive decisions (whether it’s stage or theme)
    • Being a partner at 30 – GPs with skin in the game
      • As young, have to have been very successful early or came from money to get into the fund
      • Needs to prove himself but as younger, may have been very risk adverse in the sense he wasn’t free-swinging
        • Facebook went public 7 years (quick for industry, but not necessarily quick for a fund) – feedback loop timeframes
      • Million ways to market as investor, drive value as portfolio, data, theme or stage specific
        • Blog as high leverage marketing for himself, writing is how he clarifies his ideas to himself and the public
    • Limits and is very prescriptive for the networking aspect of VC, conferences – wife in medical school so when she’s free, he makes himself free
    • Accelerator / demo days as good for investing – he likes being first institutional round, but thinks demo day to discover is not their best way
      • Sometimes the due diligence for demo days of seeing what’s out there
      • He uses them to talk to other VCs, see source and deal flow – coopetition – high leverage, high marketing channel
      • His best way in is likely the portfolio companies under them – he looks for connections for new places and vouch for them
    • Naming Fidelity markdown of a bunch of companies – saying that private companies are being treated like they’re public companies
      • Realtime prospects that are valued – can go up or down, financing or not
      • Private crowdfunding to create liquidity, getting to cash flows and thinking about dividends, debt, crowdfunding – IPO bar is so painful
    • Fav book: Brothers Karamazov – Dostoevsky as “fiction bible”
    • Union Square Ventures as the one he looks up to – Benchmark, also (Read ebooks)
    • Concept of Founder-friendly – agency from founders holding them responsible, but becomes messy / complicated
    • Most recent investment at that time: CircleUp was series C, crowdfunding platform for CPG – other forms of financing for orgs will be transformed
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Innovative Investing (Notes from June 3 – June 9, 2019) June 25, 2019

Posted by Anthony in Automation, cannabis, Digital, education, experience, finance, Founders, global, Leadership, medicine, NFL, questions, social, Strategy, training, Uncategorized, WomenInWork.
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The primary theme of the week seemed to be how data can get pooled together to determine a signal and how to learn to seek the best way we, as individuals or teams, can discern valuable content to motivate actions on that information. Data is plenty – it’s a matter of gathering, curation, analysis and testing before putting it into action. This is done by any number and types of companies nowadays – this is a source of advantage seeking that forward-thinking ones make, in my opinion.

Since my notes were more detailed, I’ll try to keep this brief. The wonder people below hailed from banks (First Republic Bank), funds like Emerson Collective and Womens VCFund, marketing company like BEN or LikeFolio and then David Epstein’s Range, Sinead O’Sullivan’s work on space or the data Rohan Kumar collects with Azure Data.

Create a hypothesis. Test the hypothesis. Put into action, or iterate. Rinse, repeat. Good luck!

  • Samir Kaji, (@samirkaji) MD @ First Republic Bank (20min VC 093)
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    • Leading private bank and wealth management, before at SVB
    • 1999 – “anyone with a pulse could get a job” but he was working selling vacuum cleaners at dept store
      • Was told by family to get a real job – applied to first business SVB, got resume in and interview immediately before starting
      • First couple years were tough – learned a lot, but was 2004 until companies had scaled and were getting bigger
    • First 10 years were tech companies, series A and B and venture debt – post 2009 Lehman / Bear, went to venture group at SVB for 4 years
      • Made the move with a few others from SVB to First Republic, now leading team in micro-VC and early-stage tech co’s
    • Says the micro-VC is more entrepreneurial & collegial compared to extended stage VC’s
      • First fund is that you can get traction for a second or third one, fees as pressure – most likely why many people come from some wealth
        • Writing large checks as GP, as well
      • 2-2.5% management fees initially vs 1 / 25 or 1/30 model
      • 1999 – 2002 distribution was 0.9x and you’d get 10x return (whoops) – very difficult for funds to get 2-3x for LPs
    • Barriers to entry much smaller for $20-25million as compared to $500mln – institutional, etc — he can go to family friends and high net worth
    • Seed over next 5 years: contraction in space (wrong), but said there isn’t enough returns for funds to max it
      • 1100 in the 2000 year and burst
      • Continued prominence of Angelist platforms, maybe an integral part of the ecosystem
      • Starting to see use of data (Mattermark, CBInsights, SignalFire) to more efficiently identify and action at this level
    • Favorite book is Phil Jackson’s – behavioral psychology, Give and Take is another one
    • Really respects the pioneers of the industry and first-time fund-raisers
      • Mike Maples, Michael Deering, Steve Anderson, Jeff Clavier when it wasn’t a thought
    • Habit – reading book or blog post for 20min in the morning before email
      • Disconnect from audio / video devices and reflect for an hour
      • 2 hours a day for family/friends and disconnecting, as well
    • Thomas Redpoint, Mark Suster, Brad Feld, Strictly VC, Ezra at Chicago Ventures
    • Knows awesome fundraisers but terrible at returning capital – didn’t mention any
  • Collectively Driving Change, Laurene Powell Jobs and Ben Horowitz (a16z 5/27/2019)
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    • LPJ – founder, president of Emerson Collective
    • Grew up in NJ – father passed away in a plane accident when she was 3 – 3 children.
      • Mom remarried so there were 6 of them. Wooded area of NJ.
      • Core values and dedication to education to get out of the area.
      • She went to Upenn – first student from her high school that went to Ivy League – ~20% went on to more schools
    • Addressing East Palo Alto school as a volunteer to help – 1st talk, 0 had taken SATs
      • What happens when you’re first to graduate high school? What’s it mean to the information from family?
      • What happens to be first to want to go to college, thrive&complete it?
        • To have the aspiration, can be a leader in the family – translator, get sucked into all problems
      • Started with 25 freshmen – would have to come with friends for responsibility mechanisms – for College Track
        • 3000 high school students, 1000 college, 550 grads
    • Collective of leaders, innovators – education inequities, access and need for enhanced/robust curriculum
    • 10 year time horizons – getting them together is scheduled with Monday all-staff meetings (3×3 matrix of videos)
      • 5 cities, sometimes philanthropic speakers or reports
      • Discussion of reading as you fall behind through third grade before switching to reading to learn – already behind
    • XQ as SuperSchool dream – 17 of 19 will open in August
    • Caring about impact and solving problems, not wealth increasing – wants access to policy or money and not taxes
      • Judged Giving Pledge for not wanting to be more philanthropic
      • Environmental, edtech portfolio, cancer / oncology investments, immigration incubator, new thinking to old problems
    • How do you know when you’re succeeding? Collecting data on everything they do.
      • Example: XQ – schools and districts, state of RI as switching to statewide competition
      • Chicago has good data for fatal/nonfatal deaths (I disagree)
    • Imperiled or important institutions like journalism and media need to be sustained, how many join?
      • Concentrating and following where IQ is migrating (hahaha – what a joke)
  • Data Infrastructure in the Cloud, Rohan Kumar at BUILD conference (Data Skeptic, 5/18/19)
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    • Corp VP of Eng of Azure Data Team at Microsoft – SQL and data services, open source, analytics, etc
    • Trends in data engineering in the cloud, serverless and hyperscale
      • ML and AI and enabling applications – shifting to edge vs cloud – analysts predict 70% will be on edge devices
      • Solutions and private edges – training in the cloud and deploy them on the edge applications
        • Data platform needs to be the right foundation
    • Highlight for him from conference: work they’ve done on relational databases in the cloud – as volumes grow, scalability challenges
      • Hyperscale for Azure and PostgreSQL, as well as MS SQL soon enough – system scales with needs (they’ve tested <= 100TB)
    • Acquired Citus Data, support scaling out the compute layer – strong team, great product, matches in Azure and open-source
    • Releasing serverless option for Azure database – costs designed to stay low and optimized
    • Analytics side: customers wanted to do real-time operational analytics – didn’t want to move them outside of their core product
      • How is data distributed and having compute be co-located with the data to gain Spark efficiency being nearest to node
      • Support Jupyter notebooks across all APIs to modernize to do more predictive analytics
      • Attempting to build out pipelines requires too much scripts, instead have Data Flows in Azure Data Factory – no-code and UI
      • Wrangling data visually and seeing if something can be recognized or learned to repeat across other columns/tables
    • Latency won’t be ideal if compute nodes occur nonlocal to the data changes – can’t do 50,000 nodes all at once
    • Excited for the future: Horizon 1 (next 8-12 months), Horizon 2 (~3 years), Horizon 3 (moonshots)
      • H2: Hardware trends, what do customers want? Pushing boundaries of AI and ML, healthcare, gaming, financial services, retail
  • Wide or Deep? David Epstein, author of Range (Invest like the Best, 5/28/19, ep. 133)
    • First book’s research lead him to get into specialization and finding kernel for next
      • Some countries: turning around national sports teams – why don’t we try other sports? Contrary to 10,000 hour rule.
      • SSAC – debating Gladwell – athletes have a sampling period instead of first gene – delay specialization
        • Used Tiger vs Roger – Roger had tried a ton of sports vs Tiger who was born and was playing golf
    • He was not good at predicting what people/public would attach themselves on to – 10,000 hour rule – race/gender as most talked (but weren’t)
      • 10,000 hour rule were based on 30 violinists in world famous music academy (restriction of range)
      • Height in American population vs points scored in NBA (positive correlation) but if you restrict height to NBA players, negative
    • Finnish cross country skier who has genetic mutation similar to Lance’s boosted
      • Sensitivity to pain and modification to your environment – also sudden cardiac arrest in athletes (what pushed his interests)
      • Book as opposition to Outliers and Talent Code – interpreted a lack of evidence as evidence of absence (genetics matter)
        • First year he read 10 journal articles a day and not writing – they were making conclusions they could not make based on their data
      • Differential responses to training – best talent were missed because we don’t know about training responses
    • Collection and exploration phase – competitive advantage for expansive search function to connect sources or topics
      • Has a statistician on retainer, essentially, to check models or surveys
      • Wanted to know what he was missing – “how come I broke the 800m women’s world record after 2 years of practice? – genetic difference”
        • Racing whippets – 40% had a genetic defect that gave them more muscle and oxygen
    • All of sports as a limited analogy (problem after Sports Gene; now, more tempered)
      • Robin Hogarth addressed “When do people get better with experience?” Don’t know rules, can try to deduce them but can’t know for sure.
      • Kind learning environment: feedback immediate, steps clear, information, goal ahead
      • Wicked learning environment: can’t see all information, don’t wait for others, feedback delayed/inaccurate
    • Study at Air Force on “Impact of Teacher Quality on Cadets”
      • Have to take 3 maths – calc I, II, III (20 kids randomized) – professors best at causing kids to do well (overperforming) systematically undermined their performance thereafter
        • 6th in performance and 7th in student evaluations was dead last in deep learning
        • Narrow curricula were better at the test that they had at the end would be negatively correlated with going forward in performance
      • Teachers that ignored what was on the test taught a broader curriculum (making connections vs procedures)
    • Learning hacks: Testing (wonderful – primed to test ahead of learning), Spacing (deliberate not-practicing, Spanish ex spread 4 hour twice, 8 hours), Mixed practice
      • Ease is bad – known time horizon for when you have forgotten again – interleaving and spacing mixed
    • Passion vs Grit (“Trouble with Too Much Grit” – Angela Duckworth’s research)
      • Duckworth did a study at West Point for East Barracks cadets – candidates score (test + leadership + athletic) was not good prediction of doing this (overall it was good)
        • Grit was a better predictor for making it through East Barracks – she questioned whether it had an independent aspect
        • Variance for grit was probably 1-6%, especially after “flattening” groups – looking at people that had a narrowly defined goal for short periods (cadets or spellers)
      • Cadets were scoring lower on grit at late 20s vs earlier – tried some things, learned others about what they want – grit is poorly constructed
        • Look holistically – if, then signatures (giant rave – introvert, small team – extroverts) right fit looks like grit – developmental trajectory as explosion matching spot
    • Choosing a match for a future them who they don’t know in a world they can’t comprehend – people that find good fits (in practice, not theory)
      • Paul Graham’s “Commencement Speech” that he wrote “Most will tell you to predict what you want in 20 years and march toward it.” (premature optimization)
        • Everything you know is constrained by our previous experiences – limited as a teenager – just expanding and learning as you go forward
    • Gameboy example – with so much specialized information that can be disseminated easier – can take from all types of domains and recombine them
      • System of parallel trenches – can be broader much easier now – hired people for Japanese and German translations
      • Japanese man profiled in his book – technology was changing faster than sun melts ice – didn’t get Tokyo interviews
        • When he got to Kyoto company making playing cards, he was a tinkerer who was maintaining machines – started to mess with them (arms)
        • Turned them into a toy, and it was Nintendo – cartoon-branded noodles (failed), and had toy development
          • Lateral thinking with withered technology – stuff that’s cheap, easily available – takes into other areas
            • Remote control, more features – wanted to democratize this and strips it down – LeftyRX only left-turns
        • Sees calculator from Sharp and Casio and thinks he can do a screen and handheld game – small games
          • Had issues with Newton’s rings so he found other small tech (credit cards embossed) to fix small pieces
      • What it lacked in color, graphics and durability (could dry it out, batteries would be fine, split it up, “app” developers because it was super easy to understand)
      • In areas that next steps were clear, specialists were much better – less clear, generalists were more impactful – depends on the specificity of the problem
        • 3M had a lot of areas for this, “Periodic Table of Technology” – post-it note came from reusable adhesive that had no use for
        • Only Chinese national woman to win Nobel – “Three No’s” (No post-grad, foreign research, membership in academy)
          • Interest in science, history – Chinese medicine for treatments of malaria – world’s most effective treatment from ancient text
  • Greg Isaacs, BEN (Branded Entertainment Network) (Wharton XM, Marketing)
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    • Discussion of getting data from Netflix / Amazon / Hulu / tv to better match brands and advertising
      • Dirty data via a wharton grad who set up a survey style
      • Cohorts and demographics, along with psychographics
    • After getting data, attempting to approach Youtubers / social media influencers, tv spots and channels or shows to get their brands in front of the right people
      • More pointed, depending on what interests are for their cohorts
      • Creative storytelling as the change of cultural mind shift has increased
  • Understanding the Space Economy, Sinead O’Sullivan (@sineados1), entrepreneur fellow at HBS (HBR IdeaCast #684, 5/28/19)
    • Facebook, Amazon (3000), SpaceX (12,000) and other funding like Blue Origin / SpaceX / asteroid mining or travel
    • Global space economy as $1tn by 20 years – currently $325bn so it would need to 3x
      • Breaking apart space resources and otherwise – earth-focused (delivering or existing in space that helps earth)
        • Exploration or creating interplanetary existence
    • Running out of space in space for satellites – comparing to airplane docking / loading
      • $2500 per kg now to launch, used to be $50k / kg
    • Reliance had been on unilateral agreement for space policy – one tech startup launched a satellite that didn’t have permission (but no fall-out)
      • Food / grocery stores, wifi, phone, insurance pricing due to satellite data – reliance on services are increasing as the market increases
      • Thinks that we’re close to seeing the cheapest cost of launching – cites SpaceX, but won’t allow everyone to participate
    • Ultrahigh accuracy will require higher powered satellites – GPS, nonmilitary grade is ~0.5 m – thinks it will prevent autonomous vehicles solution
    • Ton of money going into asteroid mining but thinks it’s better for testing missions to Mars and figuring out the problems for future
      • Looking at Uber at start and say “people won’t get into a stranger’s car” or other cases as how we see the future – going to Mars, etc
    • Earth-focused space technology – 100+ launched satellite start-ups, micronano satellites, relay companies, downstream analytics
      • More touchpoints for everything in this manner
      • SpaceX will increase public and government intervention and within 50 years, maybe see a human launched there
  • Investing w Twitter Sentiment, Andy Swan (@andyswan), LikeFolio (Standard Deviations, 4/25/19)
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    • 1700+ tweets examined per minute in LikeFolio – discovering consumer behavior shifts before news
      • Direct partnership with Twitter to create massive database and how they’re talked about to look for mentions
      • Purchase intent, sentiment mentions – trends across product categories or brands
    • Example – Delta (as host is a loyalist) – making adjustments
      • Expectations are the relative part – comparison to the baselines (metrics compared to itself as baseline)
    • Put out a comprehensive report on Apple day after keynote event – September 14, 2018
      • Consumers were unimpressed with iPhone lineup – more price sensitive than maybe they’d considered
      • Apple Watch was the silver lining – stock / sales may struggle over 3-9 months (upgrade cycles)
    • WTW version of keynotes – NYE resolutions – subscribing early to drive revenues the rest of the way
      • Purchasing mentions were only up 30-40% compared to 5 or 7x weekly mentions (big difference)
    • Shelf-life and how to consider the sentiment data – lead time may be binary corp event (same store sales or year)
      • Couple months with Apple, for instance, but with Crocs – resurgence that persisted to current time
    • Set up keyword structure and brand database – “I’m eating an apple” as opposed to an Apple mention – human eyes to ‘label’
      • “Closed my 3 rings” – apple watch but sarcasm / spam that wasn’t caught (estimates at 2-3% of data)
      • If spam / sarcasm are consistent portions of the data, doesn’t really have an effect
    • Twitter Mood Predicts Stock Market – Bollen, Mao, Zeng (88% and 5-6% predictions) – fund closed up shortly
    • Advantage being better than analysts or pricing and codifying sentiment behavior compared to past quarters, data
      • Some consumer trends analyzed as true tipping point or actual movements
      • Public prediction before productizing their modeling – made 40 and were 38-2 (confidence as highest)
      • Investing as very specific, concentrated and holding ammo compared to trading with option spreads and has risk profile built
    • https://arxiv.org/pdf/1010.3003.pdf
    • Diversification as 20-25 stocks, doing it over time and with conviction can be done
    • Starting in Louisville for his fintech company, host in Alabama, for instance
      • Talent can be more difficult to seek out but the world is globally flattening via the internet
      • 70% lower overhead cost than being in SF, for instance – developers would anyhow be in Slack channels / not a big deal
      • Reduction in cost maintains greater control of company since they don’t have to take reduction of equity to gather more
    • Network effects don’t matter if you don’t have a great product or product-market-fit
    • Free association game
      • grapenuts: best cereal (Co’s been around for 100+ years, branding and $ spent and they can’t figure it out)
      • Fintech Future: individualization and customization
      • Victory: most important thing in life, achieved what you set out to do – setting goals and achieving these
      • Bourbon: pappie von winkle – collecting for dust on shelf 10 years ago and now going for $3000
  • Jonathan Abrams, co-founder Nuzzel news (Launch Pad)
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    • Landing hedgehog as the mascot – animal as cute, 99designs and surveying 50 friends – 25 men/women
    • Discussing how VC’s don’t have great advice, especially when general – too hard to be an expert in such a wide range
      • Finds it easier to be very context-driven and providing solutions or action-oriented questions to founders
      • Investing now easier with YC and Angelist, etc…
    • Timing and other mistakes he made – out of control, losing equity part early (but depends on where you are / what you need)
  • Etan Green, professor at Wharton (Wharton Moneyball)
    • Discussion on paper of how sharp money comes in at horse racing tracks
      • Difference between sites – fairground action compared to tracks, and specific to region (New Orleans, Minnesota, for instance)
      • Big sharp money comes in very late, pushing the underdog prices to higher values
        • More expensive to bet while at the track than the APIs enabling higher volume bets
        • Books at the track are incentivized to bring in as much $ as possible, so $0.20 on $1 vs $0.15 rebate on $0.20 for volume
    • Value and differences in how people will bet
  • Edith Dorsen, Women’s VCFund founder, MD (Wharton XM)
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    • Talking about their focus on first fund, approach
    • Opportunity for finding diverse founders, 25% of their fund had a woman founder
    • Starting a second fund
    • Had consumer tech, enterprise and not so much b2b, but trying to increase
      • Hard to say or give advice if one of their partners don’t have expertise in the domain
  • Sophie Lanfear, Silverback Films producer on Netflix “Our Planet” (Wharton XM)
    • Species that are dying, going extinct
    • What we can do about it
  • Aliza Sherman, Ellementa co-founder, CEO (Wharton XM)
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    • Discussion of client talks when she made them aware of her cannabis endeavors
    • How friendly the community is
      • Then knocked the idea that ~30% was female to start before diving off a cliff
    • CBD to mask opioids – does it really do anything from a pain/treatment perspective, though?
      • Anti-chemo because of CBD – really?
    • Sounded too rehearsed – made it sound fake, not genuine
      • Passion/motivation/mission and kept repeating as the best advice she could give – painful

How to Humanize Data for Enhancement (Notes from May 20 – 26, 2019) June 12, 2019

Posted by Anthony in Automation, Blockchain, Digital, experience, finance, Founders, global, Hiring, Leadership, NFL, questions, social, Strategy, Uncategorized, WomenInWork.
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I’m going to keep this brief this week, as I’m trying out an added format of posting. I believe I’m going to test Nuzzel news to connect and share the links of articles I’ve read through the week (maybe once or twice – weekend one out on Monday, and another for the week through Thursday?). This post, concentrating on my week’s podcast or segment listens, will still go out. That’s my goal, though.

The week I listened to these, I was actually on my way to Monterrey with my family, though, so I had a solid 90 minutes each way to go through some longer episodes – thankfully, I found Doug’s take on culture and leading a community with Eat Club very insightful, as well as a blockchain discussion by the a16z squad particularly fun.

With the news and media focused on AI, Bias, Diversity and Ethics of ML and scariness of algorithms, it’s good to hear opinions that are focused, but thoughtful on the premise of what is being proposed. In a vacuum, yes, these can be dangerous. However, that’s not often the case when models are being deployed into production. Some are unintentional or started with a simple question of relationships (think Cambridge Analytica and how it started via Likes research on music at Facebook). That’s not necessarily justification for something that clearly had a large impact, but we’d like to know that teams are improving and have that awareness now more than ever before. That’s a positive.

I believe that these episodes, though, take a bit more of a nuanced approach of mathematics and numbers and attributes a human eye that has acquired the necessary expertise to design better models or come up with a better framework for action. We hear that with Dan Waterhouse of Balderton Capital (of a delightful Applied Math degree), who had to learn to apply more of an operational and human/market behavior investor since he had the metrics focus while learning. Then, a fascinating segment with Laura Edell, a sports fan, who struggled to believe that the metrics that were widely accepted as ‘most accurate’ (re: not necessarily max accuracy) included all components of what could be measurable – made some assumptions to test based on twitter/media analysis and coupled it with the data that was widely acceptable to come up with an excellent Final 4 Model.

To continue the theme, not to be outdone, Geoffrey Batt and Nikos Moraitakis each spoke of differing aspects of metrics that they honed in on and ignored the common threads of why those weren’t valid, despite what they saw as opportunities. Geoffrey as it pertained to Iraq investing and Nikos in the form of starting and building a company in Greece, not exactly the traditional hotbed. However, each persisted and are successful today – so there’s a lesson in doing the things that we want to do.

Remember, ultimately, numbers and averages usually take the aggregate, collection of those that may not have had the timing, willingness or ability to push but with enough persistence and support, some will certainly persevere.

Hope you enjoy!

  • Doug Leeds (@leedsdoug), CEO at Eat Club (Dot Complicated, Wharton XM)
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    • Talking about going from Ask.com to Eat Club – other companies, as well
    • Quiz leading in was on different likes/dislikes
      • Harry Potter-themed eating pop-ups
      • Anti-spoiler pin (digital, season and episode to avoid conflict)
        • Anything was good that brings community together
        • Said that there were employees at work that took off Monday after GoT finale since they hadn’t watched
    • Delivery people are employees, not contractors – become regulars at corporate events and a part of the culture
      • Help build the culture of the locations – food and how they match
      • Building culture of Eat Club with improv – ability to improve skills there, as well
    • Eat Club numbers – 1000+ companies served, about 25k lunches provided
      • Regional difference of Indian focus in NorCal, Mexican focus in SoCal
        • Acquired an Indian food provider for new techniques – Intero?
        • Acquired another, as well
  • Five Open Problems Toward Building Blockchain Computer (a16z 5/16/19)
    ah-logo-sm

    • Ali Yahya (@ali01), Frank Chen and looking at crypto
    • New paradigm has to improve upon one or two particular ways for new applications, but likely sucks in most others
      • Mobile phone as enabling behaviors for instagram/uber and such with camera and gps in the phones
      • Have to trust the company currently to do what they claim to be doing – trust Google with so much to have the interactions
      • Now, have a computational fabric that separates the control of human power, self-policing and security bottom-up
    • Difference in communication cost – bounded on the end by speed of light
    • Trying to make networking efficient – miners propogating to other miners – blockchain distribution network
      • 1 MB vs 2 MB blocks but can kill some small miners
      • Agreeing on blocks or updates are final
    • Non-probabilistic vs fast – need to be faster than 60 minutes, for instance
      • Improvements on networking layer with Ethereum 2.0, Cosmo and cost or Proof of Stake (vs Of Work)
        • Who gets to participate? PoW requires everyone to compute an expensive proof of work.
        • PoS – intrinsic token that you have to own in order to buy participation, 2% ownership says 2% of the say to say yay or nay
        • Cost of participating is less expensive because it’s intrinsic
      • Practical for everyday use, small interactions between people and machines or people
      • Trust as the bottleneck to scale
    • 3 Pillars of Computation/Scalability: Throughput, latency, cost per instruction
  • Daniel Waterhouse (@wanderingvc), GP at Balderton Capital (20min VC 091)
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    • Sits on boards of Top10, ROLI, Lovecrafts, TrademarkNow etc
    • Was 5 year partner at Wellington Partners and invested in EyeEm, Hailo, Yplan, Bookatable, SumAll, Readmill (sold to DropBox), Qype (sold to Yelp)
    • Break in 1999 by getting to work at Yahoo for about 10 years before getting to venture in 2009
    • Applied Math background, tend to understand complexity and appreciate solutions in technology – different experience for entrepreneurs
      • Learned to be less metric-driven – less obsessed on numbers and data, more human and market dynamics
    • Operators vs career VCs – successful firms take different skills at different times
      • Exit, raising money, portfolio management, scaling, growing
      • Important to watch how a business is grown, whether it’s yourself or by being a long-term investor or close in other ways
    • Entrepreneurship as a career path and as a global one, investors in similar mindset and ambition – can take it anywhere
    • More seed capital and smaller checks than later in Europe at this time – maybe more competition higher stages
    • Thinks that consumerizing SMB software has a lot of room to grow, as well as enterprise software – easier UI-driven tools
      • Developments in AI – mentioned real-time trademark analysis (TradeMarkNow, for instance)
      • How to give great recommendations after gathering consumer tastes and insights
    • Book: The Brain That Teaches Itself – neuroplasticity of the brain
    • The first $10mln you invest, you’ll lose – advice
    • Overhyped sector: food delivery; Neglected: apply behavioral science to tech problems
    • Favorite blog/sector: longs for better content – thought TC was great when it was started, but now it’s Medium individual articles
    • Most recent investment Curious.ai – made it in 40 minutes & ambition was compelling
  • Geoffrey Batt (@geoffreysbatt), Nature of Transformational Returns (Invest Like the Best, 4/9/19)
    • Iraqi equities – history of asset classes
      • Time and patience is a big factor for how you look for results
      • Japan, for instance, 1950 – 1989 100,000% return but now is still below the peak from 1980
    • May have a decade of not working out return-wise
      • Nothing to show for investments, incredibly challenging, especially now – hedge funds or LPs
        • Reporting weekly or daily basis, long-term investment could be 6 months or 1 year – pulling money after first issue
      • Hard to ride out periods of long-term returns (think: re-rating countries)
    • LPs as agreeing to the time horizon – maybe investment committees that are making decisions on career-risk for institutions
      • Iraq to one of those – not likely to get paid off if it works, but if it doesn’t, get demoted or fired
      • Had to approach HNW and family funds – adjacency risk for people next to seed investors (if one is weighted on fund)
    • As student, he majored in psychology – said there was a guy in the seminar class that was a unique thinker
      • Daniel Cloud had co-founded a fund that invested in post-Soviet Russia before doing his PhD
      • Asked Geoffrey to come work for him and learn investment markets
    • Wanted to find next big thing – first, find a place that everyone thinks is awful (in 2007, this was Iraq)
      • Does perception meet reality? How many people dying in the war every month?
      • Country portrayed as “failed state” but oil production was increasing, CPI was 75% yoy but now 5-10%
        • Currency appreciating against the dollar, now civilian casualties in a month were down to 200 from thousands
      • Normal visit to Baghdad – mundane here, out-of-place was that 2 guys in middle of afternoon were playing tennis, kicking soccer
        • Visit companies, stock exchange, meet executives, go to a restaurant, how easy is it to hail a cab, get around
        • Critical process of infrastructure – are people paying in dollars (bad sign), local currency?
    • News media is just not set up to convey complexity to the audience – alienate, progressivism as a service, readers change
      • Experts don’t have skin in the game so they don’t face career risk – betrayal if you suggest otherwise, likely (even if true)
    • On his first trip, mentions Berkshire – early 1990s where they first invest in Wells Fargo
      • Managerial skill in banking is paramount if levered 20:1 (make 5% mistake and you’re done)
        • Don’t want average banks at great prices – want great banks at slightly unreasonable prices (thought about this in Iraq)
      • CEO of first Iraqi bank – unsecured loans to taxi drivers – less likely to take out the loan “between you and I, I’m a cowboy”
      • Entrepreneurs in these areas have to be better than others because of the instability vs the stable environments
    • Stock and capital guys – stock may trade at 3x earnings or 4-5x FCF, top and bottom lines growing at 20% per year
      • Usually just put there as knowing someone powerful but they can be bigger as allocators
      • 2008-09: Size at the time of the stock market – traded 3 days a week, 10am – 12pm on a white board
        • 60-70 companies, maybe 20 suspended from trading because 0 annual report – $1.8bn, smaller than Palestinian market
      • High growth company that is super opaque – can’t meet or won’t meet with CEO, maybe some others that state-owned enterprises that just want to keep paying salaries; maybe 5-10 companies that are investable
        • Equally weighted these companies initially and was still learning – now, he developed relationships and is on the board for companies
      • Does he want to put more $ and concentrate on the companies that he trusts and follows the guide
    • Largest holding for them – Baghdad Soft Drinks (Pepsi bottling and distribution for Iraq) – mixed-owned enterprise in the 90s
      • Local businessman (Pepsi is the dominating market share – ~70-80% vs elsewhere where it’s split) saw it was mismanaged
      • By 2008-09, were going to default on the loan they were floated – businessman bought the loan, fired management & 2000 ee’s, switched equity
        • Within a year, it was fully certified, tripled production, profitable business
    • Now, 5 days a week but still 2 days a week – had foreign investor interest, $5-6bn, couple IPOs successful
      • One telecom has about $1bn market cap, 14.5% dividend yield, 33%+ FCF yield
      • Foreign money came in 2013 but ISIS scared them off – coming back and interest from banks – arranging trips and momentum
      • Key problem – no 3rd party custodians (compared to Jamaica or even in Africa, HSBC or anything) – working on getting one
        • Makes it difficult to bring in foreign money – exchange is the custodian (which is actually safe)
        • No margins, cash-based market and settlements of t+0, no short selling (can’t sell unless have stock)
      • Oil collapse depressed prices and ISIS issue but has been up over last 2-3+ years, cheaper today than when he invested 11 years ago
    • Multiple expansion is the question for returns – 1x to 25x or 4x to 15x – depends on what they are as compounding
    • Kobe Bryant complimented him after a junior year game in high school – already looked at as a superstar – saw Geoffrey was dejected
  • Nikos Moraitakis (@moraitakis), Founder, CEO Workable (20min VC FF024)
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    • VP of BD at Upstream, enterprise sales in 40 countries in 4 continents
    • Wanted to start a company with type of what they wanted – centered around product, engineering company, starting in Greece
    • SMB over Fortune 500 because of product-focused and not corporation or enterprise-based
    • Applicant-tracking systems (ATS) – keep track of arcane process, don’t want to touch things – collaborative processes
      • Simple interface to solve problem of recruiting model (which is still 50+ years old)
    • Problems aren’t location-based – they’re conceptual – designing product, PMF
      • Opening with $500k or 50-200k if needing to get started, not necessarily $5-10mln like other markets or tech hubs, industry
      • Hiring engineers that are good in Greece isn’t so much a problem if you have a good company and network to attract talent
      • Moved to US not for VCs (doing good business, VCs pay attention) but they had 50% of customers without having anyone in US
        • Wanted to start customer support infrastructure, services and otherwise
        • Talked about marketing or accounting businesses on tech that taught companies that it may be worth it to update
    • Metrics that he pays attention to: month-to-month above $2mln annual revenue, ratio of new biz and lost biz
      • Not celebrating fundraising – few drinks but says it’s like having new shoes at the start of a marathon
      • Talking about investors and the relationships built to work together
  • Jaz Banga (@jsbanga), cofounder, CEO of Airspace Systems (Wharton XM)
    airspace-metal-crest2x

    • Meeting Earl, cofounder and maker, at Burning Man – drone being annoying above him while he did tai-chi
    • Prototyping the interceptor drones after seeing military request proposals – had an issue with drone over nuclear subs
    • Can place thermal scans and other security or rescue methods
  • The Transformer (Data Skeptic 5/3/19)
    • Encoder/decoder architecture of vector embeddings word2vec into a more contextual use case
    • Keyword lookup may not work (using ex of bank – river bank vs financial)
      • Humans at 95%+ accuracy, computer maybe around 50%
      • Encoding as correct interpretations and weights for context – emulating process
  • Laura Edell (@laura_e_edell) from MS Build 2019, NCAA predictions on Spark (Data Skeptic 5/9/19)
    build-2019-intro

    • Been at Microsoft for 3 years, supporting Azure for all their customers – quantum physics and statistics background from school
    • ML in cloud for customers – don’t know why they want it, just think it will be useful
      • Ex: image recognition (on techs with bodycams), HVAC documentation and augmentation or signal processing in anomalies of wave patterns
        • holoLENS use case
      • Played 2 sounds for Build presentation – her son blowing on her arm vs HVAC system custom sound – training sets and transfer learning
    • Can take a few real image and do a bunch for training: rotating, zoom, Gaussian blur, cut out background
      • Sound – same: take out environment, pauses and silence
      • Can turn 10 images / sounds into 30-50 per class
    • Active learning: model over time that can train itself and then retrain itself
    • Business domain expertise – her Final 4 model
      • #1 feature was wins, 2nd SoS, 3rd home court advantage / location – let machine validate the expertise
      • Validation of revenue drivers from machine – more importantly, if the opposite occurs – revenue doesn’t agree with data features
        • Used statistics to train data from the start in football, sports data – ncaa – teams, tourneys, prior history
          • Brought in her assumption of player-social index where they scraped sentiment and video analysis for team effects
        • Chose to use Azure Databricks (Spark background), store it in Blob and only retraining on Just-in-time in a Docker image
      • ML Flow, set of score for model – training set and .py and score.py or source data gets grouped together in Azure
        • Docker pulls them together easily and image is built, Azure DevOps can do VC

Data + Opportunities for Masses (Notes March 4 – March 10, 2019) March 28, 2019

Posted by Anthony in education, experience, finance, Founders, Hiring, medicine, NFL, questions, training, Uncategorized.
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This week was all about different types of people chasing and building what they wanted to build. What drives people – what are they drawn to? Passion, energy and asking the questions to further the quenching of thirst for the next step. Reading the notes I had for this had me down a rabbit hole for each one – thus the delay.

Interestingly enough, these founders, presidents, authors and data scientists / explorers are in different industries. We had digital tech and marketing, strategy, data science as it applied to healthcare, NFLPA / financial literacy, and education of cs and tech stacks through ISA’s.

Believe that you can learn from others to further what you do to progress forward.

Steve Mast, President and CIO at Delvinia (Measured Thoughts, Wharton XM)
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    • Using Methodify for geolocation data / surveys
    • Digital tech to help marketers, researchers and leaders collect, visualize and enable data
    • Educated as an architect, then video game designer and producer in the 1990s
    • Joined Delvinia in 2000 to build interactive design and digital marketing
      • Talked about doing events where they get volunteers to sign up for brand / marketing analysis
      • Ask 2-3 questions that are pointed, geo-enabled for brand / important points at the event
      • Makes sure not to have personal identifiers
  • Joseph Jaffe (@jaffejuice), author Built to Suck (Wharton XM)
    • Admiral, co-founder at HMS Beagle, strategy consulting for surviving
    • Talked about how Harley Davidson is in every marketing book but what are they doing now? Floundering
    • Nike ads – never talked about the product (shoes), but call to action – Just Do It
      • Nike as providing the tools for which you act
      • Used their stores as ex of environments for their product – having treadmills
        • Each employee was a runner, wearing Nike and touting the products, experts
    • Remembers asking his class if they knew the first bank to implement ATMs
      • Didn’t provide the answer – jumped into 4 P’s – one student asked what the answer was
        • Answer was that it didn’t matter because every single bank mentioned had ATMs
      • Only thing that mattered – first-mover’s “advantage” if you can keep it
      • “What are you doing now?”
  • Chris Albon (@chrisalbon), Getting First Data Science Job (DataFramed #55)
    2672ecf4-b76e-478c-9407-fc48877479bf-1515514797324

    • Data Scientist at Devoted Health, helping to fix healthcare system
    • Co-host of podcast Partially Derivative, since stopped, and had a kid / moved
    • Humanitarian non-profits, working on team for building companies with a soul
      • Devoted – health insurance company started by Todd (CTO of US) & Ed Park (CEO of health company)
        • Creating company that you’d want family members be a part of
        • Make healthcare that works (primarily senior citizens, Medicare)
    • His background is from quantitative political science – politics and civil wars
      • Perspective of research, experimental, statistics – PhD with these fellows
      • Meeting friends with a ton of amazing, applied projects (LinkedIn, etc…)
      • He needed to be applied vs research in order to get out of academia – joint Kenyan nonprofits (election monitoring and disaster relief)
      • Real data or fake reports, safety, ethic and morals come up – threat models aren’t the same
    • First hire at Brick (free wifi to Kenyan homeless, etc…)
      • Using established tools to provide others data / analysis – for a team to not know that going in, it was impressive (wizardry)
    • As a team, you can hire and absorb senior data scientists
      • People who got first time jobs at Facebook or something, got to see scale and experience that they can move on easily
      • At a Facebook/Google, end up doing heavy data analyses for the massive scale and is a big role
        • Hard, analytical challenges
      • Smaller companies may ask someone to do a ‘full stack’ / general data scientist that has to build everything on their own
    • Early on in hiring process – ex with Master’s in ML, and that’s what you want to do
      • Generalist builders at Devoted, but not strictly ML or other thing
      • Heavy AI or ML would be theory-based, dissertation level technical discussion (obvious focus)
    • Doing data science generally – many other problems – Bayesian analysis, RF, etc…
      • Far more jobs for those that are generalists at companies for business data – predicting drones watering crops, customers churn, illnesses
    • With different backgrounds, should figure out how to feature yourself & experience
      • Side projects, blog posts, portfolio, visualizations in a way that’s easy – testing, GitHub, versioning
    • Talked about his first meeting at Devoted Health – 4 data scientists in the room with a doctor, discussing the coding of health / diagnosis
      • Said he was fascinated in the meeting as he wanted to know that side, new business
    • He genuinely enjoys new techniques, analysis that he doesn’t know and learning about it – passionate about what they are and learning
      • Not hiring for junior – it’s because you will want to grow into senior
    • RF > SVM since it works out of the box, but said SVM is an awesome mathematical tool
      • Used it as a teaching point and visual – but in production, he’d never seen it
  • Eric Winston (@ericwinston), President of NFLPA (Wharton XM, Leadership in Action)
    • Talked about how important relationships and the soft skills were
    • Financial literacy as a passion of his – talked about how little players know going in, especially after college
      • College finance doesn’t teach it, either
  • Austen Allred, Founder/CEO at Lambda School (20min VC 3/8/19, FF)
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    • Bedrock, GGV, GV, Stripe and Ashton Kutcher as investors – $48M so far
    • Prior, Senior Manager for Growth at LendUp and co-founded Grasswire
      • Income inequality, financial health thoughts – nothing was moving incomes
      • Was in a small town in middle of nowhere, Utah
    • Had to live in his car in SV for a while and figured out how to schedule – during summer, would get hurt obviously
    • Raised $500k initially, couple months of cash left, due diligence – investor decided to not continuing Dec 23 (daughter was born soon after)
      • Never wanted to be in that position again – thought it would’ve been VC but it was more about a successful business
      • At YC, wasn’t focused on demo day – modeled 2 scenarios: 1 with VC money vs otherwise going wrong and seeing no VC money didn’t work
    • About the right time to raise: $1 today would be $3 or $4 later, still had much of their series A – getting dozens of VC emails and say no
      • No goal to raise B at that point, walked through the numbers with Jeff (one of investors) over dinner
      • So Good They Can’t Ignore You (Steve Martin quote, but Cal Newport book)
    • Looking at product-market fit – people would pay whatever to get to the job / signal
      • Incentives aligning, job and person – $1000 to start and pay after getting a job: Got into YC and thought no upfront deposit, etc…
      • List of 7k people, trying to refine and make sustainable
    • Training people online was tough, free upfront / no SITG – no Bay Area / NY, online engineering students
    • Iterating on all facets of business so quickly: had to do it, quickly and concurrently
      • Each 5 weeks do a project, roll people together and do an app – if they can’t, roll it back
      • “Insane” – but more people just can’t fathom DOING, the ACTION
      • Before running the experiment, they determined the metrics for success and failure (if it doesn’t happen, fail)
      • Career coaches / meetups / staff bonuses for people trying to get people hired – success of those 8 trials
    • Wright Brothers biography book and Les Miserables (humanity)
    • Changing SV – fundamental human problems, he wants them to build more, try more
    • 500k students in the year for 5 years goal

Off to the Super Bowl!! January 25, 2016

Posted by Anthony in experience, NFL, Uncategorized.
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As what feels like a displaced fan at times, the highs and lows can be lonely! Thankfully, social media and the few like-minded friends make it a bit easier to spread the passion. Sports make us go through the whole spectrum of emotions – there is a brutal honesty in sports. At the same time, there can be a sweetness, a euphoric cry. Games that send you into an abyss (Super Bowl XLVIII) where the whole world melted away along with my Broncos’ chances. Luckily, it was quick. Seattle pummeled them from the first kick and the initial safety. It was like preparing for a slow band-aid but someone yanked it off once they grabbed enough.

Last year, it was revenge. Anything to see the Seahawks have their joy ripped from their hands. I remember the interception vividly. I surrounded myself by a good friend, new friends and strangers at a home. Consolation was that I won squares (moneys!) and a comeback for the ages in cornhole at half-time. Down 4-19 and had to cancel to keep going. It only seemed right that things continued to go my way. I recall only 1 or 2 Seahawks fans that were really only cheering against the Patriots. The other 28-30 people? New England fans for the day (I remember fans of the Vikings, 49ers, Packers, Broncos, Panthers) all watching intensely. Sports are rewarding for the quick, deep connections that are established – our brains groove the moments forever – people, plays, players, teams, date & time melded together for future versions of us to recall at the mention of a play, name, even a commercial!

I am spoiled. I have deep connections to generally winning franchises in the form of the Duke Blue Devils, Detroit Red Wings, Atlanta Braves, Denver Broncos, Bayern Munich. The Sacramento Kings are my lone-championship-less squad. But guess what? If it’s that great of a year, they’ll go all “We Believe” on the exact team that started it, and if I’m blindly biased (as all great fans should be), that will charge them to a title in just 7 few years! The Braves have won 1 title but were so good for so many years. The Red Wings during the 90s and start of 00s were dynastic. The Broncos had the late 80s and finally got over the hump with back-to-back titles in 97-98. Duke has spread their titles out since 2000 – doing their best when not thought of as the consensus favorite – hmmm out of the top 15 this year??

The Broncos, this year, have followed a similar pattern. Last year felt like a lot of pressure after the wipeout in the Super Bowl. New pattern – defense! 6-0 start with a sorry offense. A faux resurgence with Brock until that came crashing down during ugly second halves. Then the Peyton energy boost in the playoffs. So far, I’m just crossing my fingers. Health. A healthy defense for the first time in 4-5 years (as long as Wolfe is fine).
I couldn’t watch the 3rd Patriots drive inside our 20. Didn’t want to blow it. The offense looked so bad. The defense was the one that deserved to win it. Brady did a fantastic job of avoiding 4…5…6 sacks? Any of which could have ended the game. Gronk is a beast – and that truly worries me for Greg Olsen. But they got it done – big INT on the 2-pt conversion. Lots of pressure.

We go through a lot as fans. I won’t pretend to know what it feels like to be on the field experiencing it. But that’s the player’s jobs. For fans – it can be life. Luckily, I like to think that it’s just a joyful privilege that we can experience so much from watching a game.

Thank you, sports. Thank you, Broncos! Let’s go on this last, little ride with Peyton.

Let’s go Denver! Let’s go Broncos Country! #OrangeCrush #NoFlyZone #OutonTop

Week 2 NFL DFS Recap September 23, 2015

Posted by Anthony in Daily fantasy football, DFS, experience, NFL, Week 2.
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I woke up this morning to news from the lineup optimizer on FantasyPros: “CONGRATS! You came in 14th out of 1,728 players in our DraftKings Lineup Contest. Claim your $20 DraftKings Prize: You’re all set. The $20 prize will be credited to the DraftKings use”

Great news! I only entered 2 lineups since I had forgot about it, and my Ravens stack did very well.

QB Flacco, RB Forsett, RB Lynch, FLEX Hyde (two weaknesses), WR A Brown, WR A Robinson, WR J Landry, TE Gillmore, D Ravens

I have really enjoyed fantasypros – found them last year before the season so I have a pro subscription for seasonal fantasy and have found their optimizer one of my favorites. Nearly all of the data is pooled from experts across the industry.
First, let’s speak of Fanduel, where I played 3 lineups in a total of 6 contests. I had 2 H2H (one was free, other for $2), 1 50/50 league at $1, 1 DoubleUp for $2, another for $10, and a $4k tourney for $1. I won both H2H and the $10 double up. Something like $16.00 in fees for a simple winnings of $23, +$7 (~38%). The TeamRankings Football Championship Week 2 was my best scoring lineup – 123.2, good for 83 of 535. Lineup was saved by Antonio Brown (32) and Larry Fitz (33.2), Jordan Matthews garbage time TD (17), and consistent scoring from Bailey (8) and Texans D (6), but dragged by Brees, Abdullah, Lynch, ASJ.
99.9 was enough to win a the $2 and free H2H’s, rolling with Carson Palmer (22.2), John Brown (7), L Miller (6.7), Lynch (7.7), Garcon (11.3), ODB (24.1), Eifert (12.9), Josh Brown (9) and Ravens D (-1). RB’s didn’t end up haunting me in the H2H, thankfully.
With DraftKings, I had a lineup go for 188.66, one for 180.36, one for 171.96, 129.9, 122, 89.36, 80.26, 115.9, or 126.3.
  • I played 5 H2H’s – one lost on Monday night. I went 1-1 in $5 H2H (net -$1), 1-2 in $1 H2H (net -$1.20).
  • I played 3 freerolls and went winless.
  • Where I did make my money was in $0.25 arcades, $1 and $3 tourneys.
    • I placed 1405 of 115k for $7 on a $1 entry (net $6) with 180.36
    • I played 5 quarter arcades (3-2) for 3 entries won (net $3.75) – 188.66, 180.36 and 171.96.
    • I played 2 $1 entry to $10k gpp and finished 149 and 151 of 11.5k entries (180.36 and 180.26) for (net $8)
  • I found great success with stacking Pitt (Big Ben, Deangelo, ABrown, Heath) as well as mixing in Woodhead, TWill, and the Cardinals D.
  • Flacco, Forsett (eh), Gillmore and Ravens D (eh) with receivers ABrown, Allen Robinson, and Jarvis. Marshawn was not a success but needed a big horse to anchor the RB spots.
  • I had Saints and Eagles stacks that did not perform very well. Luckily, they were good enough in h2h games, saved by other receiver plays.

Until next week, see you!

Daily Fantasy NFL Week 1 Results September 15, 2015

Posted by Anthony in Daily fantasy football, DFS, NFL, Week 1.
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So, after 1 week I am in the black quite a bit, despite an overall losing record! Who doesn’t like those tournaments?!

Last year I was going more off of a feel for playing and breaking even. This year, I will look for tournament opportunities for overlay and pad with a better performance on h2h, triple ups or 50/50s. Fortunately, for overlays (where value is much higher per entry because the guaranteed money does not meet the number of entries), I stumbled upon a number of sites that aid in finding these. Namely, Super Lobby! which combines Draftkings and Fanduel (among others) to show overlay in tournaments. Incredibly useful for the people who are trying to be smart about entry fees.

For those that are curious how I did this past week, continue reading. Otherwise, I will post who I’m looking at and what I’m doing for Week 2 in the coming days! Again, if you’re looking to play or take a shot: Draftkings link! – Remember to search for a promo code on your favorite fantasy / insider website to valuable premium subscriptions (Rotogrinders, 4for4, fantasypros, teamrankings). Fanduel if you prefer .5 ppr and Kickers

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