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A B C D E F G H K Player OBP LG Salary Index Difference Marginal Product MRP IF R2 CORRELL IN Gary Sanchez 0.292
A B C D E F G H K Player OBP LG Salary Index Difference Marginal Product MRP IF R2 CORRELL IN Gary Sanchez 0.292 0.5 $3,000,000 108.4 28.4 3.155555556 $13,157,222.22 undervalued 0.029437 0.171573 Mitch Garver 0.37 0.5 $10,500,000 124 44 4.888888889. $20,090,555.56 undervalued Rhys Hoskins 0.332 0.462 $12,000,000 112.6 32.6 3.622222222 $15,023,888.89 undervalued Carlos Santana 0.318 0.429 $5,250,000 106.5 26.5 2.944444444 $12,312,777.78 undervalued Elvis Andrus 0.304 0.358 $15,000,000 96.6 16.6 1.844444444 $7,912,777.78 overvalued Whit Merrifield 0.382 0.7 $4,062,500 146.4 66.4 7.377777778 $30,046,111.11 undervalued 8 Amed Rosario 0.305 0.378 $1,500,000 98.8 18.8 2.088888889 $8,890,555.56 undervalued 9 Brandon Crawford 0.273 0.315 $2,000,000 86.1 . 6.1 0.677777778 $3,246, 111.11 undervalued 10 Matt Chapman 0.33 0.424 $16,666,666 108.4 28.4 3. 155555556 $13,157,222.22 overvalued 11 Justin Turner 0.345 0.455 $13,000,000 114.5 34.4 3.822222222 $15,823,888.89 undervalued 12 Lourdes Gurriel Jr. 0.309 0.463 $10,000,000 108.1 28.1 3.122222222 $13,023,888.89 undervalued 13 Joc Pederson 0.348 0.416 $9,500,000 111.2 31.2 3.466666667 $14,401,666.67 undervalued 14 Cody Bellinger 0.356 0.525 $27,500,000 123.7 43.7 4.855555556 $19,957,222.22 overvalued 15 Kevin Kiermaier 0.322 0.419 $10,500,000 106.3 26.3 2.922222222 $12,223,888.89 undervalued 16 Teoscar Hemandez 0.305 0.435 $15,000,000 104.5 24.5 2.722222222 $11,423,888.89 overvalued 17 Hunter Renfroe 0.297 0.416 $5,500,000 101 21 2.333338333 $9,868,333.33 undervalued 18 Willy Adames 0.31 0.31 $12,250,000 93 13 1.444444444 $6,312,777.78 overvalued 19 J.D. Martinez 0.321 0.572 $4,500,000 121.4 41.4 4.6 $18,935,000.00 undervalued 20 Jorge Soler 0.341 0.512 $10,000,000 119.4 39.4 4.377777778 $18,046,111.11 undervalued 21 Jason Heyward 0.34 0.473 $9,000,000 115.3 35.3 3.922222222 $16,223,888.89 undervalued 22 Michael A. Taylor 0.278 0.442 $4,000,000 99.8 19.8 2.2 $9,335,000.00 undervalued 23 Tommy Pham 0.328 0.446 $6,000,000 110.2 30.2 3.355555556 $13,957,222.22 undervalued 24 Jeimer Candelario 0.336 0.471 $15,000,000 114,3 34.3 3.811111111 $15,779,444.44 undervalued 25 Isiah Kiner-Falefa 0.306 0.34 $7,500,000 95.2 15.2 1.688888889 $7,290,555.56 overvalued 26 Tony Kemp 0.303 0.304 $3,725,000 91 11 1.222222222 $5,423,888.89 undervalued 27 Brandon Belt 0.369 0.49 $9,300,000 122.8 42.8 4.755555556 $19,557,222.22 undervalued 28 Victor Caratini 0.327 0.383 $6,000,000 103.7 23.7 2.633333333 $11,068,333.33 undervalued 29 Tom Murphy 0.335 0.538 $4,000,000 120.8 40.8 4.533333333 $18,668,333.33 undervalued 30 Donovan Solano 0.369 0.391 $2,000,000 1 12.9 32.9 3.655555556 . $15,157,222.22 undervalued 31 32 Mendoza Player .25 0.3 80 33 34 MRP - A - ! y- 0.1662x + 1E+07 R2 CORRELL 35 $ 35,000,0 00.00 36 0.029437419 0.171573364 $30,000,000.00 37\f9,444.44 undervalu 25 Isiah Kiner-Falefa 0.306 0.34 $7,500,000 95.2 15.2 1.688888889 $7,290,555.56 overvalue 26 Tony Kemp 0.303 0.304 $3,725,000 91 11 1.222222222 $5,423,888.89 undervalu 27 Brandon Belt 0.369 0.49 $9,300,000 122.8 42.8 4.755555556 $19,557,222.22 undervalu 28 Victor Caratini 0.327 0.383 $6,000,000 103.7 23.7 2.633333333 $11,068,333.33 undervalu 29 Tom Murphy 0:335 0.538 $4,000,000 120.8 40.8 4.533333333 $18,668,333.33 undervalu 30 Donovan Solano 0.369 0.391 $2,000,000 112.9 32.9 3.655553556 $15,157,222.22 underval 31 32 Mendoza Player 0.25 0.3 80 33 34 MRP y = 0.1662x + 18+07 35 $35,000,000.00 R2 CORRELL 36 0.029437415 0.171573364 $30,000,000.00 37 38 $25,000,000.00 39 $20,000,000.00 Projected Salary 40 $15,000,000.00 41 42 $10,000,000.00 43 $5,000,000.00 44 $0.00 45 $0 $ 10,000,000 $20,000,000 $30,000,000 46 Actual Salary 47 48 49 50 Sheet1 Sheet2 + Ready Accessibility: InvestigateWhat to Turn In . Your data (in a spreadsheet or Google Sheet) . A writeup, in three to five double-spaced, typewritten pages: 1."What you did, including how you calculated the cells in your spreadsheets. 2. Why this process might be valuable to a professional baseball team, and how the information that you calculated should be used in order to make a baseball team more profitable. 3. Conclusions. Explain what this project tells you about the market for baseball players, and how this information could be applied to other markets.G H 31 Washington Nationals 0.314 0.381 700.9 43.8 1,865,832 44.78 $83,551,956.96 32 A y - 4E+06x - 48+08 B y = 1E+06x + 2E+07 33 $250,000,000.00 $250,000,000.00 34 35 $200,000,000.00 $200,000,000.00 36 $1 50,000,000. 00 $150,000,000.00 88 Team Revenue Team Revenue . ..... $1 00,000,00 0.00 $100,000,00 0. 00 $50, 00 0,000.00 $50, 000,000.00 $0.00 $0.00 50 70 0 20 40 80 100 120 140 10 20 30 40 60 Index Win Percentage C Ly - 1.1624x - 54.634 70 60 50 40 Win Percentage 30 20 Plot Area 10 65 0 56 80 85 90 95 100 105 110 115 120 125 Index 58 59 60 62 63 64
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