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6-6-9.9-12.4-6.5c-3.5%2C1.7-3%2C3.2-5.2%2C3c-9.4-1.1-24-2.2-29.5-2.5c-15.9-1.1-37.5-2.9-50.5-1.6c-4.1%2C0.3-21%2C3.3-21.4%2C16.4%0A%09%09%09c-0.5%2C7%2C4.4%2C13.5%2C12.1%2C14.5c12.4%2C1.9%2C19.7-9.9%2C30-12.5c11.4-2.9%2C33-5.4%2C53.8-3.2c-1.1%2C6.5%2C0.2%2C13.8%2C3%2C18.3c3.8%2C6.2%2C10%2C9.7%2C18.9%2C11%0A%09%09%09c21.3%2C2.9%2C33.3-14%2C37.5-22.9c4.8-10.3%2C7.5-20.5%2C7.5-20.5l2.2-9c8.4-0.5%2C18.9-5.9%2C29.2-19.8C462.1%2C118.1%2C463.4%2C114.3%2C465.2%2C110z%0A%09%09%09%20M204.7%2C137.8c-3.5%2C0.9-6-0.3-7-4c-0.6-2.2-1.7-6.7-5.9-9.2c-1.8-1-5.2-1.7-8.4-0.7c3.1-4.6%2C4.6-7.8%2C5.8-10.7%0A%09%09%09c7.9%2C7.2%2C19.5%2C12.3%2C19.7%2C17.6C209.1%2C134.6%2C207.5%2C137%2C204.7%2C137.8z%22%2F%3E%0A%09%09%3Cpath%20class%3D%22st2%22%20d%3D%22M589.9%2C158.3c-2.4-2.8-12.1%2C1.8-18.1-11.3c-0.3-0.7-0.6-1.4-0.9-2.1C558.7%2C115.5%2C550.8%2C47%2C549.7%2C30%0A%09%09%09c1-1.6%2C2.1-3.5%2C2.5-4.8c2.5-5.9-2.2-10.6-6.2-8.7c-6.5%2C2.4-3.2%2C4-24.1%2C9.8c-7.1%2C2.1-3.8%2C6.5-1.7%2C10.6c0%2C0.3%2C0.3%2C1.4%2C0.6%2C3%0A%09%09%09c-2.4%2C4-53.7%2C87.7-57.3%2C92.3c-2.1%2C2.9-4.1%2C3.5-6.5%2C5.7c-3.8%2C3.5-3.8%2C8.7%2C2.5%2C8.6c1.7%2C0%2C17.3%2C0%2C25.6%2C0c2.9%2C0%2C4.6-2.9%2C4-5.6%0A%09%09%09c-0.6-2.5-3.8-5.4-3.8-6.2c0-6.3%2C5.7-16.7%2C7.6-20c1.4-2.4%2C4.6-2.7%2C7.6-2.7c6.2%2C0.2%2C21.7%2C0.3%2C30.3%2C0.3c1.6%2C8.6%2C5.9%2C30.9%2C10.2%2C42.9%0A%09%09%09c2.1%2C5.7%2C5.2%2C11.3%2C10.3%2C14c3.4%2C1.8%2C6.9%2C2.7%2C10.5%2C3c10.2%2C1%2C20.3-2.7%2C24.5-5.3c0.5-0.3%2C0.8-0.6%2C1.2-0.9c3.2-2.3%2C4.1-5%2C2.7-7.5%0A%09%09%09C590.1%2C158.4%2C590%2C158.4%2C589.9%2C158.3z%20M523.7%2C58.5c2.7%2C22.2%2C3.5%2C28.7%2C4.8%2C39.9l-28.1%2C0.2C504.6%2C91.1%2C516.5%2C70.6%2C523.7%2C58.5z%22%2F%3E%0A%09%09%3Cpath%20class%3D%22st2%22%20d%3D%22M559.7%2C178.4c-2.6%2C7.8-4.5%2C13.4-4.8%2C14.4c-1.3%2C3.5%2C1.4%2C7.1%2C5.1%2C7.1h13c2.2%2C0%2C4.3-1.4%2C5.1-3.7%0A%09%09%09c2.3-7.2%2C4.4-14.2%2C6.6-21.2c-5.2%2C2.2-12%2C3.9-19.2%2C3.9C563.6%2C179.1%2C561.6%2C178.7%2C559.7%2C178.4z%22%2F%3E%0A%09%09%3Cpath%20class%3D%22st2%22%20d%3D%22M864.3%2C47.9c-3.8-10.3-10.8-21.4-28.1-32.1c-9.2-5.7-20.8-8.4-31.3-9.5C763.5%2C2%2C721.1%2C24.1%2C684.1%2C31.2%0A%09%09%09c-9.7%2C1.9-30.2%2C0.6-31.8-12.2c-0.6-5.4-1.4-11.1-4.8-14.8c-5.1-5.2-15.9-5.9-23.2-0.5c-16%2C11.9-5.6%2C34.9%2C11%2C44.6%0A%09%09%09c14.1%2C8.1%2C31.1%2C7%2C43.2%2C4.8c47.2-8.7%2C84-35.6%2C127.3-31.9c42.1%2C3.7%2C55.4%2C42.4%2C43.8%2C73.7c-4.4%2C10.8-10.9%2C20.2-20.2%2C26.7%0A%09%09%09c-5.2%2C3.5-11.6%2C6.2-19.1%2C5.6c-3.3-0.3-7.3-2.4-8.7-5.2c8.7-3.3%2C27.9-11.3%2C34.9-22.5c7.6-11.9%2C1.6-24.3-16-23.5%0A%09%09%09c-21.6%2C1-39%2C17.2-44.2%2C33.9c-3.7%2C8.2-8%2C18.3-14.6%2C17.6c-5.4-0.6-0.8-13.8-0.8-13.8c2.7-8.4%2C17.6-52.9%2C23.3-70.8%0A%09%09%09c1.4-4.6-2.1-8.1-5.9-7c-5.2%2C1.7-4.3%2C4.1-21.1%2C8.4c-5.7%2C1.4-3%2C4.8-1.4%2C7.8c0.8%2C1.6%2C0%2C5.4-0.8%2C8.1c-2.5%2C7.2-11%2C31.1-16%2C45.2%0A%09%09%09c-1.7%2C3.9-5.6%2C14.2-14.5%2C21.5c-1.6%2C1.3-5.4%2C3.6-8.3%2C3c3.5-4.1%2C5.7-7.1%2C8.7-13.8c3.3-7.3%2C4.9-14%2C3.5-22.1%0A%09%09%09c-1.3-7.9-8.4-15.4-17.6-15.9c-5.2-0.3-11.4%2C0.2-15.9%2C0.9c0-0.3%2C0.2-0.5%2C0.2-0.8c0.3-1.7-1-3-2.1-3.3c-3-0.6-4.9%2C1.6-9%2C2.2%0A%09%09%09c-5.4%2C1-14.3-1.1-14.8%2C2.2c-0.5%2C3-1.3%2C5.7-2.2%2C8.9c-0.2%2C0.7-2.9%2C8.6-6.6%2C19.7c-2.1%2C4.9-6%2C12.9-13.3%2C18.9c-1.6%2C1.3-5.4%2C3.6-8.3%2C3%0A%09%09%09c3.5-4.1%2C5.7-7.1%2C8.7-13.8c3.3-7.3%2C4.9-14%2C3.5-22.1c-1.3-7.9-8.4-15.4-17.6-15.9c-5.2-0.3-11.4%2C0.2-15.9%2C0.9%0A%09%09%09c0-0.3%2C0.2-0.5%2C0.2-0.8c0.3-1.7-1-3-2.1-3.3c-3-0.6-4.9%2C1.6-9%2C2.2c-5.4%2C1-14.3-1.1-14.8%2C2.2c-0.5%2C3-1.3%2C5.7-2.2%2C8.9%0A%09%09%09c-0.4%2C1.1-7.7%2C23.1-15.6%2C46.7c1.2%2C3.5%2C2.3%2C6.8%2C3.5%2C9.5c2.5%2C5.6%2C5.1%2C5.8%2C8.8%2C6.2c1.5%2C0.1%2C3.5%2C0.4%2C5.4%2C1.3c0.8-2.7%2C1.7-5.4%2C2.5-8.1%0A%09%09%09c3.8%2C1.6%2C7.8%2C2.9%2C12.1%2C3c5.1%2C0.3%2C10.2-0.6%2C14.1-2.4c10.4%2C4.8%2C20.9%2C1.3%2C29.5-4.9c-8.5%2C25.4-17%2C51.1-17.8%2C53.5%0A%09%09%09c-1.3%2C3.5%2C1.4%2C7.1%2C5.1%2C7.1h13c2.2%2C0%2C4.3-1.4%2C5.1-3.7c5.7-18.3%2C11-35.6%2C16.4-52.7c3.8%2C1.6%2C7.8%2C2.9%2C12.1%2C3%0A%09%09%09c5.1%2C0.3%2C10.2-0.6%2C14.1-2.4c13%2C6.1%2C26.1-0.9%2C35.6-10.1c0.5%2C2.3%2C1.1%2C4.3%2C1.9%2C5.3c6.7%2C9.2%2C23.5%2C11%2C40.4-7.9c2.9%2C9%2C10.2%2C14.8%2C22.7%2C15%0A%09%09%09c30%2C2.2%2C54.8-21%2C63.8-44.3C868.9%2C85.8%2C871.3%2C65.7%2C864.3%2C47.9z%20M623.2%2C115.5c-9.8-0.6-16%2C9-12.4%2C17.9c-3.6%2C2.2-8.1%2C3.6-10.9%2C1.1%0A%09%09%09c-1.7-1.4-0.6-4.4-0.3-6.8c2.7-8.6%2C5.6-16.5%2C7.6-23.3c6.7-15.6%2C13.2-18.3%2C15.6-18.4c3.5%2C0%2C7.1%2C1.7%2C6.8%2C8.2%0A%09%09%09C628.7%2C101.9%2C626.2%2C108.2%2C623.2%2C115.5z%20M700.5%2C115.5c-9.8-0.6-16%2C9-12.4%2C17.9c-3.6%2C2.2-8.1%2C3.6-10.9%2C1.1c-1.7-1.4-0.6-4.4-0.3-6.8%0A%09%09%09c2.7-8.6%2C5.6-16.5%2C7.6-23.3c6.7-15.6%2C13.2-18.3%2C15.6-18.4c3.5%2C0%2C7.1%2C1.7%2C6.8%2C8.2C706.1%2C101.9%2C703.5%2C108.2%2C700.5%2C115.5z%0A%09%09%09%20M810.8%2C88.1c5.4-4%2C12.4-4.1%2C12.6%2C1.3c0.3%2C10.8-15.6%2C19.5-24%2C23.5C799%2C104.9%2C801.7%2C94.4%2C810.8%2C88.1z%22%2F%3E%0A%09%3C%2Fg%3E%0A%3C%2Fg%3E%0A%3C%2Fsvg%3E%0A)
What kind of numbers will we see the New York Mets players put on the stat sheet in this 60-game season?
Back in mid-March, I was working on an article that showed and discussed my New York Mets projections for the 2020 season. I spent a few weeks crunching the numbers and using my predictive abilities to finalize what I thought the 2020 Mets season would become.
But then came the lockdowns, the suspension of spring training and I ended up putting the article on hold. What I have decided to do is to take those previous projections, make some modifications, and re-calculate the projections for the highly anticipated 60 game season.
Let’s start by first doing some comparison. Here were my initial projections back in February when the 162 game season was still in play (sorted by OPS):
Name             GP  AB   R   H  2B 3B HR  RBI  SB  AVG  OBP  SLG OPS
Jeff McNeil       149 563 102 184 37 7   21 104  14  .327 .399 .529 .929
Pete Alonso      153 553  94 157 31 1   38  114   3  .284 .367 .550 .917
Dom Smith         73  93  13  26   7  0   4   18   2  .280 .417 .484 .901
Brandon Nimmo   138 455 111 123 29  5  16  62  19  .270 .418 .462 .879
Michael Conforto  140 557  93 153 33  2  26  85   8  .275  .370 .481 .851
J.D. Davis          143 536  77  152 33  2  23  84   7  .284  .362  .481 .843
Robinson Cano    132  482 63 133  25  2  17  63   5  .276 .348  .442  .790
Wilson Ramos     112 434 45 118  22  0  16  63  0  .272  .328  .433 .761
Tomas Nido         54 134  21  32  8  0   6   22  0  .239  .315  .433  .748
Amed Rosario     146  547 75  148 24  4 17  69  17 .271  .323  .422  .745
Jed Lowrie          83 257 33  73  13  1   5  32  2  .284  .343  .401  .744
Jack Marisnick      94 235 33  55   14  2  8  21  8  .234  .323  .413  .736
Rene Rivera        38  85  11  20    4  0  4   12  0  .235  .301  .424  .725
Luis Guillome       66  78   13  18   4  1  1    9  1   .231  .333  .346  .679
Yoenis Cespedes     0   0   0   0    0   0  0   0  0  .000  .000  .000  .000
Name              GP GS  INN  H  W  L  R ER  SO BB CG SHO ERA SV WHIP
Jacob deGrom       33  33  205 144 16  6 61 54 261 44 2  2  2.37  0  0.917
Seth Lugo          46  5   96  88   9  4  33  28  106 31 0 0 2.63  0  1.240
Dellin Bentances    66  0   69  43   0  4  26  22  89  43  0  0 2.87 14 1.246
Edwin Diaz          57  0   66  48   2  3  28  23  94  24  0  0 3.14 22 1.091
Noah Syndergaard   33 33 207 172 13  9  83  73 222 54  2  1 3.35  0  1.092
Bill Brach           53  0   54  52  1  3  25 21  33  18  0  0  3.50  1  1.296
Steven Matz        38  8  104  97  8  7  47  41 92  33  0 0  3.55  4  1.250
Justin Wilson        49  0  55  57  3  2  25  23  48  19  0  0  3.76  2  1.382
Michael Wacha      30 20 146 152  9 7  72  63  127 52  0  0  3.88  0  1.397
Marcus Stroman     32 32 194 187 13 11 92 84 168 68 1  0  3.90  0  1.314
Rick Porcello        32 32 195 204 14 10 96 90 146 67 2 0  4.15  0  1.390
Robert Gsellman     37  0  47  53  2  4  24  22  36 18  0 0  4.21  0  1.511
Jeurys Familia        40  0  42  54  0  2  23  22  56 22 0 0  4.71  0  1.810
I have initially projected the Mets to go 90-72. I’m not sure if that was going to be enough wins to capture the NL East crown, but the offense was projecting to be extremely balanced and the pitching was projected to perform well, if not better than the offense. Here are some highlights:
–         Projected that Pete Alonso will have a sophomore slump, but is still productive with 114 rbi and .917 OPS.
–         Projected that Jeff McNeil takes the next step in his evolution and is the best overall hitter.
–         Projected that guys like Robinson Cano, Wilson Ramos, and Brandon Nimmo provide solid support for the middle of the order batters.
–         Projected the overall team OPS would be .827, the best in team history.
–         Projected that Jacob deGrom finally gets some run support and goes 16-6 / 2.37 / 0.917.
–         Projected that Edwin Diaz has a nice bounce back with a solid 3.14 / 1.091 / 22 saves.
–         Projected that Dellin Betances will provide solid 8th and 9th inning support to nicely complement Edwin Diaz.
–         Projected a team ERA of 3.47 and team WHIP of 1.246, which would be top 5 in the NL.
Over the past four months, some things have changed and now need to re-calculate the 2020 projections due to the following:
–         Yoenis Cespedes looking ready to play.
–         The Designated Hitter to be used during the 2020 National League season.
–         Jed Lowrie not looking ready for opening day with his mysterious injury.
–         Noah Syndergaard getting injured and having to miss the entire 2020 season.
–     The addition of Jared Hughes to the bullpen.
Here are the updated projections:
Name            GP  AB   R   H  2B 3B HR  RBI  SB  AVG  OBP  SLG OPS
Jeff McNeil         55  208 38  68  14  3   8   38  5  .327 .399 .529 .929
Pete Alonso        57  206 35  58  12  0   15   42  3  .284 .367 .550 .917
Dom Smith        33   93  13  26   7  0   4   18   2  .280  .417 .484 .901
Brandon Nimmo   51  168  41 45  11  2   6   23   8  .270  .418 .462 .879
Michael Conforto   57  207  35 57  12  1   10   32  3  .275  .370 .481 .851
J.D. Davis          53  199  29  56  13  0   9   31   2  .284  .362  .481 .843
Robinson Cano     49  179  23 49   9  1   6   23   2  .276 .348  .442 .790
Yoenis Cespedes    37  144  16  37   8  0  10   26   0  .256  .310 .463  .773
Wilson Ramos      41  159  16  43  8  0   6   23   0  .272  .328  .433 .761
Tomas Nido        27   67  11  16   4  0   3   11   0  .239  .315  .433  .748
Amed Rosario      54  202  28  55  9  2   6   26   8  .271  .323  .422  .745
Jack Marisnick       44 135 23  32   6  1   4   14   7  .234  .323  .413  .736
Rene Rivera         38  85  11  20    4  0  4   12  0  .235  .301  .424  .725
Luis Guillome        36  58   8  14   4  1  1    4  1  .231  .333  .346  .679
Jed Lowrie           33  67  10  14   5  1  2   10  2   .209  .299  .345  .644
Name               GP GS  INN  H  W  L  R ER  SO BB CG SO ERA SV WHIP
Jacob deGrom       12  12  75  52  6  2 24 20  95 16   2  2  2.37  0  0.917
Seth Lugo           17  0   36  33  4  2 12 10  39 11   0 0  2.63  0  1.240
Dellin Bentances     24  0   25  16  0  1  9  8  32 16   0  0 2.87  5  1.246
Edwin Diaz          21  0   24  18  1  1  10  8  35  9   0  0  3.14 10 1.091
Jared Hughes        20  0   23  19  1  0 11  9 18  7   0  0  3.52  1  1.131
Bill Brach            20  0   21  20  0  2 13  8 15  9   0  0  3.43  1  1.380
Steven Matz         12 12  70  66  4  5  33 31 72 24  0 0  3.99  0  1.285
Justin Wilson         18  0   20  22  2  0 12  8  19  9  0  0  3.60  2  1.550
Michael Wacha       12 12   71  68  6  3 31 28  65 26  0  0  3.55  0  1.366
Marcus Stroman      12 12   70  65  5  4 35 32  59 30  1  0  4.11  0  1.357
Rick Porcello          12 12   68  76  7  5 39 33  48 22  1 0  4.37  0  1.441
Robert Gsellman      15  0   15  18  0  1  9  7   12  7   0 0  4.20  0  1.666
Jeurys Familia         20  0   16  20  0  2  9  8   22  12  0 0  4.50  0  2.000
With the 60 game season now in play, I do predict the Mets will go 32-28.
Once again, I am not sure if that will be enough wins to make the playoffs. I do anticipate that the top four teams in the National League East will all be within a few games of each other and should lower the wins totals, giving the Mets a better chance at winning the division and making the playoffs.
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What are your projections for the 2020 Mets?