Oct 15, 2018 · 59m · capital-allocators

Michael Schwimer – Moneyball as an Investment Strategy (Capital Allocators, EP.72)

Michael Schwimer · 44m spoken Ted Seides · 10m spoken
0:00 / 0:00

gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

Former Major League pitcher and Big League Advance founder Michael Schwimer discusses applying quantitative modeling, biomechanical data, and venture capital principles to invest in minor league baseball players.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Ted holds 19.2% of the talking time here. How this is scored →

Ted as informed peer 4.3 Guest teaching 6.1 Guest disagreement 0.6 Ted pushing back 0.0
05100:0015:0030:0045:005:18–9:15 · Ted as informed peer 4/10 Athletic Beginnings, College Pitching, and Hedge Fund Roots Ted guides Michael into his backstory and prompts him about his multi-sport athletic background and hedge fund internship. Michael explains his rational self-assessment choosing baseball over basketball and his early exposure to finance.9:18–12:52 · Ted as informed peer 3/10 Minor League Economic Realities and Making the Majors Michael educates Ted on the harsh financial realities and living conditions of minor league baseball players. Ted mostly listens and prompts Michael with light questions about big league milestones and hazing.12:52–15:43 · Ted as informed peer 4/10 Applying Quantitative Modeling and Pitch Sequencing on the Mound Ted asks how Michael used his intellect to gain an advantage on the mound. Michael breaks down how he built bespoke matchup models and pitch sequencing to compensate for below-average velocity.15:43–19:09 · Ted as informed peer 4/10 Minor League Advocacy and the Conception of Big League Advance Michael recounts pitching a revenue-share plan to union head Michael Weiner and describes the aftermath of his career-ending labrum injury. Ted asks targeted follow-ups about Michael's transition to founding Big League Advance.19:09–22:22 · Ted as informed peer 5/10 Developing Process-Based Predictive Metrics for Baseball Ted brings up basic Moneyball metrics, and Michael explains why traditional minor league stats are unhelpful compared to process-based, contextual data. Michael details how he spent 14-16 hours a day building predictive models.22:22–25:52 · Ted as informed peer 4/10 Initial Fund Formation and Partnering with Paul DePodesta Michael walks Ted through his early pitch meetings, equity trade-offs with initial investors, and his serendipitous partnership with Paul DePodesta. Ted acts as an attentive sounding board.25:53–29:54 · Ted as informed peer 4/10 Player Outreach, Transparency Protocols, and Agent Conflicts Michael details the player outreach model, legal safeguards, and the hidden structural agency conflict that led him to bypass agents to talk directly with players. Ted engages with clarifying prompts.29:54–33:01 · Ted as informed peer 5/10 Outperforming Base Rates and Initial Pitching Biomechanics Ted inquires about fund hit rates and the underlying alpha of the strategy. Michael explains that over 75% of signees are outside the top 300 prospects and describes his early attempt to model pitching biomechanics and injury risk.33:03–38:25 · Ted as informed peer 3/10 Sponsor: Ridgeline AI-Native Investment Technology Following a sponsor read, Ted asks how Michael turned 12,000 video files into actionable metrics. Michael explains how hiring top analytics talent like Jason Rosenfeld and Zach Bradshaw cracked nonlinear biomechanics modeling.38:25–42:07 · Ted as informed peer 4/10 Competitive Landscape, Bad Actors, and the Francisco Mejia Lawsuit Ted asks about competitors and the Francisco Mejia lawsuit. Michael discusses predatory practices by imitators, regulatory efforts in Delaware, and the resolution of the Mejia litigation.42:07–46:10 · Ted as informed peer 5/10 Symbiotic Front-Office Scouting and Trade Deadline Analytics Ted probes potential conflict of interest between advising MLB front offices and investing in players. Michael explains the symbiotic information-sharing dynamic during the trade deadline and recruitment across other sports.46:10–49:16 · Ted as informed peer 5/10 Venture Capital Dynamics, Misconceptions, and Management Lessons Ted connects BLA's business model to venture capital power laws. Michael vents frustration with institutional pushback from the MLBPA and shares management mistakes regarding unstructured communication.49:16–52:04 · Ted as informed peer 6/10 Portfolio Construction, Bet Sizing, and Skill Versus Luck Ted frames portfolio construction using financial terminology like conviction weighting and high/low beta. Michael affirms this framing, explaining how BLA manages long-shot upside versus high-probability major leaguers.52:04–53:33 · Ted as informed peer 4/10 Playoff Perspective and Data-Backed World Series Prediction Ted asks about Michael's perspective heading into the MLB postseason. Michael breaks down why his data model favors the Astros over the Red Sox due to performance against playoff-caliber pitching.5:18–9:15 · Guest teaching 5/10 Athletic Beginnings, College Pitching, and Hedge Fund Roots Ted guides Michael into his backstory and prompts him about his multi-sport athletic background and hedge fund internship. Michael explains his rational self-assessment choosing baseball over basketball and his early exposure to finance.9:18–12:52 · Guest teaching 6/10 Minor League Economic Realities and Making the Majors Michael educates Ted on the harsh financial realities and living conditions of minor league baseball players. Ted mostly listens and prompts Michael with light questions about big league milestones and hazing.12:52–15:43 · Guest teaching 6/10 Applying Quantitative Modeling and Pitch Sequencing on the Mound Ted asks how Michael used his intellect to gain an advantage on the mound. Michael breaks down how he built bespoke matchup models and pitch sequencing to compensate for below-average velocity.15:43–19:09 · Guest teaching 6/10 Minor League Advocacy and the Conception of Big League Advance Michael recounts pitching a revenue-share plan to union head Michael Weiner and describes the aftermath of his career-ending labrum injury. Ted asks targeted follow-ups about Michael's transition to founding Big League Advance.19:09–22:22 · Guest teaching 7/10 Developing Process-Based Predictive Metrics for Baseball Ted brings up basic Moneyball metrics, and Michael explains why traditional minor league stats are unhelpful compared to process-based, contextual data. Michael details how he spent 14-16 hours a day building predictive models.22:22–25:52 · Guest teaching 6/10 Initial Fund Formation and Partnering with Paul DePodesta Michael walks Ted through his early pitch meetings, equity trade-offs with initial investors, and his serendipitous partnership with Paul DePodesta. Ted acts as an attentive sounding board.25:53–29:54 · Guest teaching 7/10 Player Outreach, Transparency Protocols, and Agent Conflicts Michael details the player outreach model, legal safeguards, and the hidden structural agency conflict that led him to bypass agents to talk directly with players. Ted engages with clarifying prompts.29:54–33:01 · Guest teaching 7/10 Outperforming Base Rates and Initial Pitching Biomechanics Ted inquires about fund hit rates and the underlying alpha of the strategy. Michael explains that over 75% of signees are outside the top 300 prospects and describes his early attempt to model pitching biomechanics and injury risk.33:03–38:25 · Guest teaching 7/10 Sponsor: Ridgeline AI-Native Investment Technology Following a sponsor read, Ted asks how Michael turned 12,000 video files into actionable metrics. Michael explains how hiring top analytics talent like Jason Rosenfeld and Zach Bradshaw cracked nonlinear biomechanics modeling.38:25–42:07 · Guest teaching 6/10 Competitive Landscape, Bad Actors, and the Francisco Mejia Lawsuit Ted asks about competitors and the Francisco Mejia lawsuit. Michael discusses predatory practices by imitators, regulatory efforts in Delaware, and the resolution of the Mejia litigation.42:07–46:10 · Guest teaching 6/10 Symbiotic Front-Office Scouting and Trade Deadline Analytics Ted probes potential conflict of interest between advising MLB front offices and investing in players. Michael explains the symbiotic information-sharing dynamic during the trade deadline and recruitment across other sports.46:10–49:16 · Guest teaching 6/10 Venture Capital Dynamics, Misconceptions, and Management Lessons Ted connects BLA's business model to venture capital power laws. Michael vents frustration with institutional pushback from the MLBPA and shares management mistakes regarding unstructured communication.49:16–52:04 · Guest teaching 5/10 Portfolio Construction, Bet Sizing, and Skill Versus Luck Ted frames portfolio construction using financial terminology like conviction weighting and high/low beta. Michael affirms this framing, explaining how BLA manages long-shot upside versus high-probability major leaguers.52:04–53:33 · Guest teaching 5/10 Playoff Perspective and Data-Backed World Series Prediction Ted asks about Michael's perspective heading into the MLB postseason. Michael breaks down why his data model favors the Astros over the Red Sox due to performance against playoff-caliber pitching.5:18–9:15 · Guest disagreement 0/10 Athletic Beginnings, College Pitching, and Hedge Fund Roots Ted guides Michael into his backstory and prompts him about his multi-sport athletic background and hedge fund internship. Michael explains his rational self-assessment choosing baseball over basketball and his early exposure to finance.9:18–12:52 · Guest disagreement 0/10 Minor League Economic Realities and Making the Majors Michael educates Ted on the harsh financial realities and living conditions of minor league baseball players. Ted mostly listens and prompts Michael with light questions about big league milestones and hazing.12:52–15:43 · Guest disagreement 1/10 Applying Quantitative Modeling and Pitch Sequencing on the Mound Ted asks how Michael used his intellect to gain an advantage on the mound. Michael breaks down how he built bespoke matchup models and pitch sequencing to compensate for below-average velocity.15:43–19:09 · Guest disagreement 1/10 Minor League Advocacy and the Conception of Big League Advance Michael recounts pitching a revenue-share plan to union head Michael Weiner and describes the aftermath of his career-ending labrum injury. Ted asks targeted follow-ups about Michael's transition to founding Big League Advance.19:09–22:22 · Guest disagreement 1/10 Developing Process-Based Predictive Metrics for Baseball Ted brings up basic Moneyball metrics, and Michael explains why traditional minor league stats are unhelpful compared to process-based, contextual data. Michael details how he spent 14-16 hours a day building predictive models.22:22–25:52 · Guest disagreement 0/10 Initial Fund Formation and Partnering with Paul DePodesta Michael walks Ted through his early pitch meetings, equity trade-offs with initial investors, and his serendipitous partnership with Paul DePodesta. Ted acts as an attentive sounding board.25:53–29:54 · Guest disagreement 1/10 Player Outreach, Transparency Protocols, and Agent Conflicts Michael details the player outreach model, legal safeguards, and the hidden structural agency conflict that led him to bypass agents to talk directly with players. Ted engages with clarifying prompts.29:54–33:01 · Guest disagreement 0/10 Outperforming Base Rates and Initial Pitching Biomechanics Ted inquires about fund hit rates and the underlying alpha of the strategy. Michael explains that over 75% of signees are outside the top 300 prospects and describes his early attempt to model pitching biomechanics and injury risk.33:03–38:25 · Guest disagreement 0/10 Sponsor: Ridgeline AI-Native Investment Technology Following a sponsor read, Ted asks how Michael turned 12,000 video files into actionable metrics. Michael explains how hiring top analytics talent like Jason Rosenfeld and Zach Bradshaw cracked nonlinear biomechanics modeling.38:25–42:07 · Guest disagreement 2/10 Competitive Landscape, Bad Actors, and the Francisco Mejia Lawsuit Ted asks about competitors and the Francisco Mejia lawsuit. Michael discusses predatory practices by imitators, regulatory efforts in Delaware, and the resolution of the Mejia litigation.42:07–46:10 · Guest disagreement 0/10 Symbiotic Front-Office Scouting and Trade Deadline Analytics Ted probes potential conflict of interest between advising MLB front offices and investing in players. Michael explains the symbiotic information-sharing dynamic during the trade deadline and recruitment across other sports.46:10–49:16 · Guest disagreement 2/10 Venture Capital Dynamics, Misconceptions, and Management Lessons Ted connects BLA's business model to venture capital power laws. Michael vents frustration with institutional pushback from the MLBPA and shares management mistakes regarding unstructured communication.49:16–52:04 · Guest disagreement 0/10 Portfolio Construction, Bet Sizing, and Skill Versus Luck Ted frames portfolio construction using financial terminology like conviction weighting and high/low beta. Michael affirms this framing, explaining how BLA manages long-shot upside versus high-probability major leaguers.52:04–53:33 · Guest disagreement 0/10 Playoff Perspective and Data-Backed World Series Prediction Ted asks about Michael's perspective heading into the MLB postseason. Michael breaks down why his data model favors the Astros over the Red Sox due to performance against playoff-caliber pitching.5:18–9:15 · Ted pushing back 0/10 Athletic Beginnings, College Pitching, and Hedge Fund Roots Ted guides Michael into his backstory and prompts him about his multi-sport athletic background and hedge fund internship. Michael explains his rational self-assessment choosing baseball over basketball and his early exposure to finance.9:18–12:52 · Ted pushing back 0/10 Minor League Economic Realities and Making the Majors Michael educates Ted on the harsh financial realities and living conditions of minor league baseball players. Ted mostly listens and prompts Michael with light questions about big league milestones and hazing.12:52–15:43 · Ted pushing back 0/10 Applying Quantitative Modeling and Pitch Sequencing on the Mound Ted asks how Michael used his intellect to gain an advantage on the mound. Michael breaks down how he built bespoke matchup models and pitch sequencing to compensate for below-average velocity.15:43–19:09 · Ted pushing back 0/10 Minor League Advocacy and the Conception of Big League Advance Michael recounts pitching a revenue-share plan to union head Michael Weiner and describes the aftermath of his career-ending labrum injury. Ted asks targeted follow-ups about Michael's transition to founding Big League Advance.19:09–22:22 · Ted pushing back 0/10 Developing Process-Based Predictive Metrics for Baseball Ted brings up basic Moneyball metrics, and Michael explains why traditional minor league stats are unhelpful compared to process-based, contextual data. Michael details how he spent 14-16 hours a day building predictive models.22:22–25:52 · Ted pushing back 0/10 Initial Fund Formation and Partnering with Paul DePodesta Michael walks Ted through his early pitch meetings, equity trade-offs with initial investors, and his serendipitous partnership with Paul DePodesta. Ted acts as an attentive sounding board.25:53–29:54 · Ted pushing back 0/10 Player Outreach, Transparency Protocols, and Agent Conflicts Michael details the player outreach model, legal safeguards, and the hidden structural agency conflict that led him to bypass agents to talk directly with players. Ted engages with clarifying prompts.29:54–33:01 · Ted pushing back 0/10 Outperforming Base Rates and Initial Pitching Biomechanics Ted inquires about fund hit rates and the underlying alpha of the strategy. Michael explains that over 75% of signees are outside the top 300 prospects and describes his early attempt to model pitching biomechanics and injury risk.33:03–38:25 · Ted pushing back 0/10 Sponsor: Ridgeline AI-Native Investment Technology Following a sponsor read, Ted asks how Michael turned 12,000 video files into actionable metrics. Michael explains how hiring top analytics talent like Jason Rosenfeld and Zach Bradshaw cracked nonlinear biomechanics modeling.38:25–42:07 · Ted pushing back 0/10 Competitive Landscape, Bad Actors, and the Francisco Mejia Lawsuit Ted asks about competitors and the Francisco Mejia lawsuit. Michael discusses predatory practices by imitators, regulatory efforts in Delaware, and the resolution of the Mejia litigation.42:07–46:10 · Ted pushing back 0/10 Symbiotic Front-Office Scouting and Trade Deadline Analytics Ted probes potential conflict of interest between advising MLB front offices and investing in players. Michael explains the symbiotic information-sharing dynamic during the trade deadline and recruitment across other sports.46:10–49:16 · Ted pushing back 0/10 Venture Capital Dynamics, Misconceptions, and Management Lessons Ted connects BLA's business model to venture capital power laws. Michael vents frustration with institutional pushback from the MLBPA and shares management mistakes regarding unstructured communication.49:16–52:04 · Ted pushing back 0/10 Portfolio Construction, Bet Sizing, and Skill Versus Luck Ted frames portfolio construction using financial terminology like conviction weighting and high/low beta. Michael affirms this framing, explaining how BLA manages long-shot upside versus high-probability major leaguers.52:04–53:33 · Ted pushing back 0/10 Playoff Perspective and Data-Backed World Series Prediction Ted asks about Michael's perspective heading into the MLB postseason. Michael breaks down why his data model favors the Astros over the Red Sox due to performance against playoff-caliber pitching.

speaking balance: gold is Ted, purple is the guest (3 minute bins)

0:00 · Ted 100% · guest 0%0:00 · Ted 100% · guest 0%3:00 · Ted 84% · guest 16%3:00 · Ted 84% · guest 16%6:00 · Ted 0.7% · guest 99.3%6:00 · Ted 0.7% · guest 99.3%9:00 · Ted 5.9% · guest 94.1%9:00 · Ted 5.9% · guest 94.1%12:00 · Ted 4% · guest 96%12:00 · Ted 4% · guest 96%15:00 · Ted 6.3% · guest 93.7%15:00 · Ted 6.3% · guest 93.7%18:00 · Ted 7.8% · guest 92.2%18:00 · Ted 7.8% · guest 92.2%21:00 · Ted 3.2% · guest 96.8%21:00 · Ted 3.2% · guest 96.8%24:00 · Ted 8.6% · guest 91.4%24:00 · Ted 8.6% · guest 91.4%27:00 · Ted 3.6% · guest 96.4%27:00 · Ted 3.6% · guest 96.4%30:00 · Ted 12.4% · guest 87.6%30:00 · Ted 12.4% · guest 87.6%33:00 · Ted 42.3% · guest 57.7%33:00 · Ted 42.3% · guest 57.7%36:00 · Ted 7.3% · guest 92.7%36:00 · Ted 7.3% · guest 92.7%39:00 · Ted 6% · guest 94%39:00 · Ted 6% · guest 94%42:00 · Ted 14.8% · guest 85.2%42:00 · Ted 14.8% · guest 85.2%45:00 · Ted 6.7% · guest 93.3%45:00 · Ted 6.7% · guest 93.3%48:00 · Ted 12.3% · guest 87.7%48:00 · Ted 12.3% · guest 87.7%51:00 · Ted 31.2% · guest 68.8%51:00 · Ted 31.2% · guest 68.8%54:00 · Ted 5.5% · guest 94.5%54:00 · Ted 5.5% · guest 94.5%57:00 · Ted 21.9% · guest 78.1%57:00 · Ted 21.9% · guest 78.1%
Sharpest disagreement ▶ 46:51 Michael blasts MLBPA for ignoring minor leaguers

Michael strongly criticizes the Players Association for opposing BLA deals by focusing strictly on the rare high earner rather than the hundreds of minor leaguers who benefit from guaranteed downside protection.

Hardest push from Ted ▶ 42:28 Ted questions conflicting interests with MLB teams

Ted presses Michael on whether providing proprietary pitching injury analytics to MLB front offices creates a structural conflict of interest with his primary investment fund.

Biggest teaching moment ▶ 19:37 Michael explains process-based predictive metrics

Michael reframes standard Moneyball stats for Ted, demonstrating why a batter with a 0-for-100 stretch of deep line outs has vastly superior major league predictive value than one with a 100-for-100 stretch of broken-bat bloops.

Ted holds their own ▶ 50:35 Ted maps portfolio theory to player risk profiles

Ted demonstrates his institutional investment expertise by translating Michael's mixed-upside player selection process into clear financial concepts of beta sizing and conviction weighting.

the scores for every segment, with the reasoning behind each
ChapterTopicTed as informed peerGuest teachingGuest disagreementTed pushing backWhy
Athletic Beginnings, College Pitching, and Hedge Fund Roots 4500 Ted guides Michael into his backstory and prompts him about his multi-sport athletic background and hedge fund internship. Michael explains his rational self-assessment choosing baseball over basketball and his early exposure to finance.
Minor League Economic Realities and Making the Majors 3600 Michael educates Ted on the harsh financial realities and living conditions of minor league baseball players. Ted mostly listens and prompts Michael with light questions about big league milestones and hazing.
Applying Quantitative Modeling and Pitch Sequencing on the Mound 4610 Ted asks how Michael used his intellect to gain an advantage on the mound. Michael breaks down how he built bespoke matchup models and pitch sequencing to compensate for below-average velocity.
Minor League Advocacy and the Conception of Big League Advance 4610 Michael recounts pitching a revenue-share plan to union head Michael Weiner and describes the aftermath of his career-ending labrum injury. Ted asks targeted follow-ups about Michael's transition to founding Big League Advance.
Developing Process-Based Predictive Metrics for Baseball 5710 Ted brings up basic Moneyball metrics, and Michael explains why traditional minor league stats are unhelpful compared to process-based, contextual data. Michael details how he spent 14-16 hours a day building predictive models.
Initial Fund Formation and Partnering with Paul DePodesta 4600 Michael walks Ted through his early pitch meetings, equity trade-offs with initial investors, and his serendipitous partnership with Paul DePodesta. Ted acts as an attentive sounding board.
Player Outreach, Transparency Protocols, and Agent Conflicts 4710 Michael details the player outreach model, legal safeguards, and the hidden structural agency conflict that led him to bypass agents to talk directly with players. Ted engages with clarifying prompts.
Outperforming Base Rates and Initial Pitching Biomechanics 5700 Ted inquires about fund hit rates and the underlying alpha of the strategy. Michael explains that over 75% of signees are outside the top 300 prospects and describes his early attempt to model pitching biomechanics and injury risk.
Sponsor: Ridgeline AI-Native Investment Technology 3700 Following a sponsor read, Ted asks how Michael turned 12,000 video files into actionable metrics. Michael explains how hiring top analytics talent like Jason Rosenfeld and Zach Bradshaw cracked nonlinear biomechanics modeling.
Competitive Landscape, Bad Actors, and the Francisco Mejia Lawsuit 4620 Ted asks about competitors and the Francisco Mejia lawsuit. Michael discusses predatory practices by imitators, regulatory efforts in Delaware, and the resolution of the Mejia litigation.
Symbiotic Front-Office Scouting and Trade Deadline Analytics 5600 Ted probes potential conflict of interest between advising MLB front offices and investing in players. Michael explains the symbiotic information-sharing dynamic during the trade deadline and recruitment across other sports.
Venture Capital Dynamics, Misconceptions, and Management Lessons 5620 Ted connects BLA's business model to venture capital power laws. Michael vents frustration with institutional pushback from the MLBPA and shares management mistakes regarding unstructured communication.
Portfolio Construction, Bet Sizing, and Skill Versus Luck 6500 Ted frames portfolio construction using financial terminology like conviction weighting and high/low beta. Michael affirms this framing, explaining how BLA manages long-shot upside versus high-probability major leaguers.
Playoff Perspective and Data-Backed World Series Prediction 4500 Ted asks about Michael's perspective heading into the MLB postseason. Michael breaks down why his data model favors the Astros over the Red Sox due to performance against playoff-caliber pitching.

Statements from this episode (25)

Assertion Supported
Schwimer: Drafted by Phillies in 2008 With $5,000 Bonus
“Fortunately for me, baseball did work out and I was drafted in 2008 by the Philadelphia Phillies in the 14th round. There's 40 rounds now in the baseball draft. And I was a 14th round pick. My signing bonus was 5000 dollars.”
Michael Schwimer Oct 15, 2018 ▶ 8:20
Assertion Supported
Schwimer: Less Than 10% of Minor Leaguers Reach Major League Baseball
“There's 7000 minor leaguers. And less than 10% will play one day in the major leagues, and less than three percent will actually get to arbitration and make, make big money.”
Michael Schwimer Oct 15, 2018 ▶ 9:21
Assertion Supported
Schwimer: Minor leaguers are not represented by the MLBPA
“Minor leaguers are actually not covered under the Major League Baseball Players Association. They're not represented at all.”
Michael Schwimer Oct 15, 2018 ▶ 16:02
Disclosure
Schwimer Explains Big League Advance's Upfront Earnings-Share Model for Minor Leaguers
“Can I invest in them? Give them money, hundreds of thousands, at some point, sometimes millions of dollars, in exchange for a future share of their earnings. If they don't make it, they keep all the money, and if they make it, we share in their success.”
Michael Schwimer Oct 15, 2018 ▶ 18:36
Insight
Schwimer: Process Metrics Predict MLB Success Better Than Standard Moneyball Statistics
“The basic money ball stuff, exactly. And it really didn't matter in the minor leagues in terms of predicting major league success. And what I had to, the lesson I had to learn was it's not, the results are not predictive to future results. It's actually the pr…”
Michael Schwimer Oct 15, 2018 ▶ 19:37
Opinion
Schwimer Considers Paul DePodesta the Greatest General Manager in Baseball History
“And for those of you who don't know, Paul, he's the money ball guy. And I believe the best GM in baseball history for 20 years, took teams to the playoffs, winning records, and then tried to move on.”
Michael Schwimer Oct 15, 2018 ▶ 24:03
Disclosure
Schwimer: Paul DePodesta Is Big League Advance's Second-Largest Shareholder
“Skip to the end. He's a, he's the second largest shareholder besides myself and a partner.”
Michael Schwimer Oct 15, 2018 ▶ 25:34
Assertion Not checkable as stated
Schwimer: Big League Advance Has Signed 128 Minor League Players
“Of the 128 players we've signed now, and that probably 300 ish we've offered, or more”
Michael Schwimer Oct 15, 2018 ▶ 26:45
Disclosure
Big League Advance Videotapes Contract Signings With 20-Question Comprehension Checks
“We videotape the signing before the signing and ask them all these questions. Do you understand if you make five hundred million dollars, you will owe us twenty five million in your career? Assuming they do a deal for five percent. Do you understand if you nev…”
Michael Schwimer Oct 15, 2018 ▶ 27:07
Assertion Not checkable as stated
Schwimer: Over 75% of BLA Signees Were Outside Top 300 Prospects
“Over 75% of the players that we sign Aren't top 300 prospects in baseball when we sign them”
Michael Schwimer Oct 15, 2018 ▶ 30:00
Disclosure
Schwimer: Big League Advance Raised $130M for Second Fund
“We raised one hundred and thirty million dollars for the second fund in order to do it over a much longer period of time.”
Michael Schwimer Oct 15, 2018 ▶ 31:15
Prediction Not checkable as stated
Schwimer Projects Over 50% of Big League Advance Signees Reach the Majors
“We believe that over half the players we sign will play a day in the major leagues.”
Michael Schwimer Oct 15, 2018 ▶ 31:30
Disclosure
Schwimer: Sam Hinkie and Paul DePodesta Invested in BLA's Second Fund
“Sam Hinckley, who ran the 70 Sixers, is in our fund. Paul D. Podesta, obviously, and now here we are with the second fund.”
Michael Schwimer Oct 15, 2018 ▶ 34:48
Assertion Supported
Schwimer: Former Lakers analytics director Jason Rosenfeld joined Big League Advance
“Jason did leave the Lakers, came to work for big league advances, our chief strategy officer running the entire analytics team.”
Michael Schwimer Oct 15, 2018 ▶ 36:54
Assertion Not checkable as stated
Big League Advance Sells Highly Accurate Pitcher Injury Prediction Models to MLB
“They built a model that was truly revolutionary to where we can predict When a pitcher's gonna get hurt with incredible accuracy to the point where MLB teams are paying for our service now”
Michael Schwimer Oct 15, 2018 ▶ 38:11
Assertion Not checkable as stated
Schwimer: Former Goldman Sachs Employees Failed at Minor League Player Investing
“There were some Goldman guys that quit and tried to do it. They have a couple players, then they left, because they realized they couldn't do it.”
Michael Schwimer Oct 15, 2018 ▶ 38:50
Disclosure
Schwimer: Big League Advance is pushing for player protection laws in Delaware
“We're pushing for a law to make sure these players are protected. And so we are going to try to get that through Delaware this year.”
Michael Schwimer Oct 15, 2018 ▶ 39:20
Assertion Supported
Schwimer: Francisco Mejía Dropped Lawsuit and Paid Big League Advance's Legal Fees
“Francisco ended up dropping the case. We actually countersued him. We settled the countersuit. He paid a portion of our legal fees for the case, and then wrote a very long apology that was highlighted actually in the Sports Illustrated article that came out ab…”
Michael Schwimer Oct 15, 2018 ▶ 41:12
Assertion Not checkable as stated
Schwimer: All Big League Advance players in the majors have paid in full
“We have many, many players in the major leagues. They've all paid on time and in full.”
Michael Schwimer Oct 15, 2018 ▶ 41:54
Assertion Not checkable as stated
Schwimer: 24 MLB Teams Consulted Big League Advance at 2018 Trade Deadline
“Last year, the trade deadline, or, you know, in 2017, 17 teams called us. This year, 24 teams called us at the trade deadline asking our advice on who are the underrated prospects in this organization.”
Michael Schwimer Oct 15, 2018 ▶ 43:25
Assertion Not checkable as stated
Two Soccer Federations Offered BLA Multi-Million Dollar Contracts Before Qatar World Cup
“Two soccer federations have reached out to us. We have nobody that has any experience in soccer, by the way. Two soccer feders reached out to us, offering us multi-million dollar year contracts to help them in advance of the World Cup in Qatar using advanced a…”
Michael Schwimer Oct 15, 2018 ▶ 44:49
Assertion Not checkable as stated
Schwimer: Three NBA Teams Asked to Outsource Analytics to Big League Advance
“And two NBA, actually three NBA teams now called us and wanted to fire their entire advanced analytics department and have us be the analytics department for those teams remotely.”
Michael Schwimer Oct 15, 2018 ▶ 45:12
Disclosure
Schwimer: Big League Advance Projects Losing Money on 80% of Player Investments
“Just because I said over half the players will make it, we're still projecting 20% to be profitable. Keep in mind, they had to play three years. Even if they do 10%, they're returning 150,000, because they make 500,000 dollars a year. In order to be successful…”
Michael Schwimer Oct 15, 2018 ▶ 46:32
Opinion
Schwimer Claims MLBPA and Agents Oppose BLA Because They Ignore Minor Leaguers
“The MLBPA looks at is players just lost ten million dollars because they don't care. About the minor leaguers. And to see the amount of pushback we're getting from them and from agents that obviously don't care about their players and care more about them keep…”
Michael Schwimer Oct 15, 2018 ▶ 47:10
Disclosure
Schwimer: BLA's second fund will invest in 500 players
“You know, we're going to have 500 players in that fund.”
Michael Schwimer Oct 15, 2018 ▶ 49:49
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