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Raw Talent Acquired Through Crowdsourcing on the Ball Diamond Wiki Prospect: FOUTS Jason Powers MBA Presentations April & December 2013 The A’s Need

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  • Slide 1
  • Raw Talent Acquired Through Crowdsourcing on the Ball Diamond Jason PowersMBA PresentationsApril & December 2013 The As Need
  • Slide 2
  • People MGMT Money (Players Salaries) Macrosabermetric Models Financial Model Fan Model Graphs that fuel both models Wiki Prospect: FOUTS Program
  • Slide 3
  • Billionaire OwnersMillionaire PlayersSports AgentsGM/Field Managers Coaches/ScoutsMedia: Cynical, DivisiveFans: Obsessive
  • Slide 4
  • MLB Players Salaries Profile (2010)
  • Slide 5
  • Two Models: Finances & Fans Graphs of Revenue Model Graphs of Exponential Talent Acquisition
  • Slide 6
  • Financial Model in MLB Total Revenues /Asset Forming Gate Receipts* Local TV Market (Media Contracts) MLB National Media Deals Concessions* Advertising Signage Parking Fees* Merchandising* Sponsorship Deals Fan-base Size Popularity Predicts Revenues Attendance-driven Non-baseball Events* Business /Baseball Expenses Pooled Revenue Sharing (34%) MLB Player Salaries Baseball FO Personnel 1 st Year Rookie Draft International Draft/Spending Scouting Player Development (Minors Staff) Ballpark Operations Facilities Maintenance Debt Service Marketing Public Relations Ticket Office Negotiated Contracts (CBA) Deferred Payments Deprec./Amort. Large Market Team Liability Small Market Team Asset Business FO Personnel Fan Model Park Naming Rights Minor League Prospects
  • Slide 7
  • Total Revenues /Asset Forming Gate Receipts 1 Advertising/Signage 1 Home Attendance, Popularity and Wins Park Naming Rights 2 Concessions 1 Parking Fees 1 Merchandising 1 Non-baseball Events 1 Local TV Market (Media Contracts) 2 MLB National Media Deals 2 Sponsorship Deals 2 2 Negotiated by MLB team or MLB Proper Over 85% of Revenues can be explained by Attendance, TV Market, and Popularity
  • Slide 8
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  • Slide 11
  • Fan Model : Just Win Baby WS Championships Season Win % Runs Allowed: Pitching/Defense R 2 >=.75 Runs Scored: Offense R 2
  • Contributes to winning via WAR: Wins Above Replacement player[7] Calculation is based on factors such as: Plate Appearances Innings Pitched Runs Created (Linear Weights of On-field Events) Positional Factors (SS >>>1B) Runs Allowed (Fielding Independent Pitching) Base Running (SB, CS, Advance to 3rd Base ) Fielding (Compared to LG% of Team Outs) Below 0 any minor league replacement 0.0 Minor league minimal 0.0. to 0.5 Bench/role player 0.5 to 1.5 Marginal starting player 1.5 to 2.5 Starter 2.5 to 4.0 Excellent starter Greater that 4.0 All-Star level Greater than 8.0 HOF level for a season
  • Slide 25
  • How often do teams draft well in the 1 st round of the draft? The players paid the most lucrative signing bonuses for the privilege to play baseball? Players that often take more than 3-5 years to reach the Majors? And underachieve projections?
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  • FOUTS Approach: Why Wiki Prospect? Problem Statement/Obstacles : The As, must find, and cultivate, cheaper talent [12] through the 1 st year player draft from the 1 st round, on down. Scouting evaluations done; professional department is of limited size Old-school scouts are antagonistic to current trends (sabermetric field) Old-school scouts see new ways as a threat to their traditional methods [10] Saber-guys: sarcastic; and arrogant quips have not help them sell their cause Recent Conflict Example [3]: Seattle Mariners GM (Jack Zduriencik) & ownership (Nintendo of America /Lincoln) were at cross-purposes with their scouting department, field managers decisions, and direct assistants over player acquisitions and development. One assistant (Blengino) wrote his GMs application for Seattle job. But Jack never has understood one iota about statistical analysis. To this day, he evaluates hitters by homers, RBI and batting average and pitchers by wins and ERA. Statistical analysis was foreign to him. But he knew he needed it to get in the door.
  • Slide 28
  • 3 rd Alternative:Wiki Prospect System Use Fan-Scouts (FOUTS) Fan Oriented Underlying Talent System A crowdsourcing mechanism to address this conflict creatively. Crowdsourcing Definition (Merriam)[9] the practice of obtaining needed services, ideas, or content by soliciting contributions from a large group of people and especially from the online community rather than from traditional employees or suppliers FOUTS will create more data points on young and raw players. VIDEOSTOPWATCH RADAR GUNGoogle Hangout UploadsAUDIO FILES Relevant Tech Example[13] Microsoft attempted to buy up a then profitable encyclopedia market (Funk&Wagnalls, Colliers, Britannica (failed)) to improve on MS Encarta. 2001, Wikipedia was formally launched. Wiki used 43 million plus users to create a product than is the 7 th most popular website. Encarta is DEAD. Approach: What Is Wiki Prospect?
  • Slide 29
  • Approach: FOUTS Prospecting Cycle Recruit Passion Train Scout Skills Assign Area Evaluate Prospects Data Collect Data Analysis New Draft Method Recruits: Degree-seeking people/biz majors; intense passion for baseball (160 FOUTS) Training: 40-60 hours plus certification exam (held at spring training) Area: Based near several baseball talent mills (college, HS, or low-minors) Evaluate: Collect many times more observations on either random or assigned players Data: Database generates Wiki-like profile with detailed ratings/individuals scouted Draft: Clarified; due to more data seen; more accessible in sabermetric formats
  • Slide 30
  • FOUTS: Wiki Example Corey Seager, SS B:L T:R H:63 DOB 4/1994 Current Video Compilation Follow Up Schedule: 4/14, 4/21, 4/25, 5/12-14 Video Upload Audio Upload DB Upload Wiki Modify ToolsGradeTime(s)PotentialDate Arm6 6 12/13/2013 Glove4 5.5 Batting Average/Contact7 8 On-Base Patience6 7 Power (Gap)5 6 Power (Op. Field)5 5 Speed (1st-3rd)56.55 Speed (1st)54.15 Catching Pop-to-PopN-A Positions GradedSS, 3B Notes: Good carry on throws Fluid 1motion swing Scouting Personnel: Dan Fouts
  • Slide 31
  • Benefits: Wiki Prospect As Benefits Low investment vs. high reward (1 WAR = $6M on FA market 2013)[5] More data: quantity creates quality (Branch Rickey farm model did in 1920s-30s)[4] Supports traditional scouting, or: redesigns it for the As from the ground up Advantages technology and modernizes scouting FOUTS Hiring Benefits FOUTS will create/mold the new system Build a skill set (resume) that equals long-term job opportunities for them Pay commensurate with skill, level of accuracy, and decision-influencing information Project results: World Series participation and winning it all
  • Slide 32
  • Costs: Wiki Prospect Athletics Initial Costs/Projected 1 st Year Outlays: FOUTS Program Costs Total Games Leagues/ Conferences FOUTS Assigned $/Game scouted/ Course Total Cost /Season Max Earnings Per FOUT High School/Traveling Teams 35-96 $50 $168,000 $1,750 College: Div I NCAA 653264 $60 $249,600 $3,900 Scouting Coordinator/Trainer[8] $80,000 Data Entry Personnel (2) $80,000 Data Analyst $75,000 Training Course + Materials 160 $550 $88,000 FOUTS Tech (iPad, etc.) 160 $800 $128,000 Travel Expenses and Misc. 160 $350 $56,000 Total Costs $924,600
  • Slide 33
  • Competition/Opportunity Cost/ Weaknesses/Threats to Wiki Prospect: FOUTS Competitive Market & Emulation Can Reduce Gains: 29 other teams, looking for market inefficiencies Emulate or duplicate: once success is apparent success will last due to being: Dedicated to approach People-oriented, not just numbers-obsessed Seek next steps to improve the system (modeling with psychological factors explored) Expanded investment: after 2-4 year trial period ($6M =1 WAR) Initial money spent (about TWO replacement-level MLB salaries of $490,000) could be used for 10-12 top scouts salaries (Op Cost) FOUTS lack experience: requires a steep learning curve (Weakness) Advance/Area Scouts: may backlash and quit (Threat) Derision/lack support: media, fans, scouts, ownership (Weakness) If it fails, the As are no worse off than before
  • Slide 34
  • [1] Adams, Steve. 2013. Mariners to Sign Robinson Cano. Web. 9 December 2013.
  • Slide 35
  • [8] Kibilko, John. 2013. How much does an MLB scout make? Web. 12 December 2013. [9] Merriam Webster, Inc. 2013. Crowdsourcing. Web. 9 December 2013.