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Do MVP Voters Look at Some Stats Above Others?

The regression that I am going to run analyzes whether sabermetric statistics, more specifically WAR, have a greater impact on MVP voting than traditional statistics. This is important to the sport because MVP voting helps players garner a good reputation. It also affects how the front office of each major-league baseball team goes about acquiring specific players. In fact, the salaries of players can be affected by MVP voting, especially if that player is in the last year of his contract and is preparing to become a free agent. In turn, acquiring high-level or MVP-type players can potentially improve overall team performance, which would result in an increase in attendance, and therefore, the team would have an increase in revenue.

The data set that I have chosen to look at is the 2014 results for MVP voting for both the American and National Leagues. Also, I will look at the individual statistics for each of the players that received votes. From this relationship, the independent variables would be the player statistics (batting average, home runs, RBI, WAR) and the dependent variable would the number of votes that each player receives. This is because certain statistics are bound to affect whether one player receives more votes than another. Essentially, what I am trying to prove is that one set of statistics is a better indicator of player ability and player contribution than the other set. Bill James was one of the first to expound upon sabermetrics when he wrote a series of books known as Baseball Abstract in the 1980s. Many other baseball historians, such as Pete Palmer and John Thorn, have written books detailing and introducing the concept of sabermetric statistics. While many books have been written and studies have been done about sabermetrics, no one has really done a study about the accuracy and influence that sabermetrics can have on statisticians, writers, fans, and teams.

For this regression, I analyzed only position players (non-pitchers) to prevent confusion due to the use of different statistics which are required to analyze pitchers separately. After the running of the regression, it appears that the WAR has a greater impact on MVP voting than home runs, RBI, batting average, and stolen bases. However, the two statistics that seem to have the greatest impact on MVP voting are On-Base Percentage (OBP) and Slugging Percentage (SLG). WAR has a positive slope of 35.9 while SLG has a positive slope of 2,535.7. The coefficient of correlation (R) is 0.87 and this seems to indicate that the nature of the relationship in this regression is positive. Also, the fact that the coefficient of correlation is closer to 1 indicates that there is a significant relationship between respective statistics and their influence on MVP voting. The coefficient of determination (R^2) is 0.76. This shows that just about 76% of the MVP voting results can be attributed to the certain statistics of a specific player. For instance, in the American League, Mike Trout led the league in WAR and RBI, and was third in SLG. Since those two statistics were the most impactful, they definitely contributed to Mike Trout being named the MVP. Therefore, this relationship is positive, and some statistics have a significantly higher impact on MVP voting than others. Once again, based on the regression, SLG seems to be the most impactful statistic, and stolen bases were the least impactful.

After analyzing the results of the regression, I ran a hypothesis test to determine the population coefficient of correlation. The level of significance for this hypothesis test was 0.05. The null hypothesis was that p=0; in other words, there is no significant relationship between any statistic and MVP voting. The alternative hypothesis is that p>0, p<0 and that there is a significant relationship between certain statistics and MVP voting. The degrees of freedom for this hypothesis test was 21. The t-critical value turned out to be about 2.1. I tested each individual test statistic and discovered that there is a significant relationship between MVP voting and RBI, SLG, and WAR since the t-calc for those variables was greater than 2.1.

To further test this theory, I also did an ANOVA. I wanted to test the variation of MVP voting when compared to certain statistics at the 0.05 level of significance. The degrees of freedom1 was 7 and the degree of freedom 2 was 21. Therefore the f-critical value turned out to be 2.5. F-Calc from the ANOVA was 9.6. Since F-calc is greater than the critical value, we prove that, once again, there is a significant relationship between certain statistics and MVP voting.

Next, I did a test for the least squares regression. For the least squares regression you have to do a test for three separate things. They are normality, homoscedasticity, and independence. To test for normality, I looked at the normal probability plot. The points on this plot seemed to be curved slightly, therefore, the residuals are not normally distributed. To test for homoscedasticity, we look at the residual plots for each of the x variables. Since most of these variables neither increase nor decrease as x increases or decreases, these variables are homoscedastic. To test for independence, you would have to run another regression. This time, it would be a simple regression using the same x variables; however, each residual is the x variable for the next one. To test for independence, you would also have to do a hypothesis test. The null hypothesis would be that bi=0 and the alternative hypothesis would be that bi>0, bi<0. If bi is equal to 0 than the residuals are independent. The level of significance is 0.05 and the degrees of freedom would be 30. The t-critical value came out to be about 1.7. T-calc turned out to be greater, which means that the residual values are not independent.

In conclusion, the initial multiple regression that I ran showed a significant relationship between certain statistics and MVP voting. Despite the fact that the residuals were not independent, the other tests that I ran showed over and over again that the same statistics that the regression stated were impactful on MVP voting were still impactful after I ran other tests. Thus, it seems that the sabermetric statistic WAR did have more of an impact on MVP voting than most of the traditional statistics such as batting average and home runs. While sabermetric statistics are a new trend in baseball analytics, they will not replace the traditional statistics such as batting average, home runs, and runs batted in, simply because those statistics have been used since the early days of baseball. Fans and statisticians alike will continue to use both traditional and sabermetric statistics to analyze player performance.

There are many other statistics that I could’ve analyzed for this regression. In fact, pitching statistics are completely different from the statistics that I used in this regression for position players. However, the statistics that I did use proved to be effective in proving that, in fact, some statistics do have a considerably greater impact on MVP voting than some statistics that some people simply assume are not relevant or needed in order to analyze player performance and contributions. Also, for this regression, I only analyzed the offensive statistics for the position players. Defensive statistics such as defensive runs saved (DRS) and defensive WAR are also important statistics that many baseball statisticians look into when evaluating player performance. Overall, the possibilities for this regression are endless, and even though there may never be a definitive statistic that everyone agrees upon for analyzing player performance, all of the statistics that I used in this regression, as well as many others, will continue to remain relevant in the game of baseball for many years to come.

2014 American League MVP Voting Results

Player, Team 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th Voting Points
Mike Trout, Angels 30 420
Victor Martinez, Tigers 16 4 3 3 2 1 229
Michael Brantley, Indians 8 6 5 4 1 1 1 1 191
Jose Abreu, White Sox 1 6 3 1 6 5 2 2 1 145
Robinson Cano, Mariners 1 1 6 5 2 4 2 1 1 124
Jose Bautista, Blue Jays 1 1 3 8 4 1 5 3 122
Nelson Cruz, Orioles 6 3 2 2 2 1 1 102
Josh Donaldson, Athletics 1 2 2 3 3 6 5 2 96
Miguel Cabrera, Tigers 1 2 2 2 2 1 6 5 82
Alex Gordon, Royals 1 1 2 2 3 1 2 44
Jose Altuve, Astros 1 3 3 3 9 41
Adam Jones, Orioles 1 3 1 1 2 2 34
Adrian Beltre, Rangers 1 5 1 1 22
Albert Pujols, Angels 1 1 5



2014 National League MVP voting results

Player, Team 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th  Voting Points
Giancarlo Stanton, Marlins 8 10 12 298
Andrew McCutchen, Pirates 4 10 15 1 271
Jonathan Lucroy, Brewers 1 13 6 7 1 167
Anthony Rendon, Nationals 1 5 8 10 2 1 1 1 155
Buster Posey, Giants 1 6 9 6 3 1 1 1 152
Adrian Gonzalez, Dodgers 1 4 2 3 3 1 57
Josh Harrison, Pirates 1 2 5 1 4 4 52
Anthony Rizzo, Cubs 1 4 2 3 4 37
Hunter Pence, Giants 1 3 2 3 1 34
Russell Martin, Pirates 2 3 1 2 21
Matt Holliday, Cardinals 1 1 2 17
Jhonny Peralta, Cardinals 1 2 3 1 17
Carlos Gomez, Brewers 2 3 1 13
Justin Upton, Braves 1 1 4 10
Jayson Werth, Nationals 1 1 3 9

American League MVP Candidate statistics: (league ranks for respective statistics in parenthesis)

Mike Trout .287 (15) 36 (4) 111 (1) .561 (3) .377 (8) 16 (25) 7.9 (1)
Victor Martinez .335 (2) 32 (8) 103 (8) .565 (2) .409 (1) 3 (104) 5.3 (14)
Michael Brantley .327 (3) 20 (29) 97 (12) .506 (9) .385 (4) 23 (11) 7 (4)
Jose Abreu .317 (5) 36 (3) 107 (4) .581 (1) .383 (5) 3 (103) 5.5 (12)
Robinson Cano .314 (6) 14 (50) 82 (20) .454 (17) .382 (6) 10 (41) 6.4 (6)
Jose Bautista .286 (16) 35 (5) 103 (7) .524 (6) .403 (2) 6 (60) 6 (7)
Nelson Cruz .271 (38) 40 (1) 108 (3) .525 (5) .333 (35) 4 (87) 4.7 (23)
Josh Donaldson .255 (56) 29 (9) 98 (11) .456 (16) .342 (25) 8 (49) 7.4 (2)
Miguel Cabrera .313 (7) 25 (14) 109 (2) .524 (7) .371 (10) 1 (158) 4.9 (20)
Alex Gordon .266 (44) 19 (32) 74 (28) .432 (24) .351 (18) 12 (35) 6.6 (5)
Jose Altuve .341 (1) 7 (99) 59 (47) .453 (19) .377 (7) 56 (1) 6 (8)
Adam Jones .281 (21) 29 (10) 96 (13) .469 (13) .311 (58) 7 (54) 4.9 (19)
Adrian Beltre .324 (4) 19 (31) 77 (23) .492 (10) .388 (3) 1 (160) 7 (3)
Albert Pujols .272 (35) 28 (11) 105 (5) .466 (14) .324 (42) 5 (70) 3.9 (30)


National League MVP candidate statistics: (league ranks for respective statistics in parenthesis)

Giancarlo Stanton .288 (15) 37 (1) 105 (2) .555 (1) .395 (3) 13 (34) 6.5 (3)
Andrew McCutchen .314 (3) 25 (10) 83 (13) .542 (2) .410 (1) 18 (22) 6.4 (4)
Jonathan LuCroy .301 (7) 13 (53) 69 (36) .465 (15) .373 (9) 4 (91) 6.7 (1)
Anthony Rendon .287 (18) 21 (23) 83 (14) .473 (13) .351 (21) 17 (24) 6.5 (2)
Buster Posey .311 (4) 22 (20) 89 (10) .490 (7) .364 (14) 0 (539) 5.2 (13)
Adrian Gonzalez .276 (29) 27 (6) 116 (1) .482 (9) .335 (34) 1 (161) 3.9 (27)
Josh Harrison .315 (2) 13 (52) 52 (65) .490 (8) .347 (24) 18 (23) 5.3 (12)
Anthony Rizzo .286 (21) 32 (2) 78 (20) .527 (3) .386 (6) 5 (79) 5.1 (15)
Hunter Pence .277 (27) 20 (27) 74 (27) .445 (26) .332 (37) 13 (33) 3.6 (34)
Russell Martin .290 (12) 11 (68) 67 (39) .430 (35) .402 (2) 4 (90) 4.1 (8)
Matt Holliday .272 (32) 20 (26) 90 (8) .441 (29) .370 (10) 4 (88) 3.4 (39)
Jhonny Peralta .263 (44) 21 (22) 75 (26) .443 (28) .336 (32) 3 (118) 5.8 (6)
Carlos Gomez .284 (23) 23 (14) 73 (28) .477 (12) .356 (18) 34 (4) 4.8 (17)
Justin Upton .270 (36) 29 (5) 102 (3) .492 (6) .342 (27) 8 (55) 3.3 (41)
Jayson Werth .292 (9) 16 (41) 82 (16) .455 (20) .394 (4) 9 (46) 4 (23)                                    

Regression Statistics
Multiple R 0.872425
R Square 0.761125
Adjusted R Square 0.6815
Standard Error 57.61154
Observations 29
  df SS MS F Significance F
Regression 7 222087.3 31726.76 9.558873 2.52E-05
Residual 21 69700.89 3319.09
Total 28 291788.2
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -807.848 179.9347 -4.48967 0.000202 -1182.04 -433.653 -1182.04 -433.653
X Variable 1 -9.48922 4.745055 -1.99981 0.058622 -19.3571 0.378659 -19.3571 0.378659
X Variable 2 2.36734 1.153175 2.052889 0.052752 -0.03082 4.765499 -0.03082 4.765499
X Variable 3 1.520176 1.123229 1.353399 0.190318 -0.81571 3.856058 -0.81571 3.856058
X Variable 4 -2356.53 1163.345 -2.02565 0.055695 -4775.84 62.77839 -4775.84 62.77839
X Variable 5 461.8825 539.878 0.855531 0.401913 -660.855 1584.62 -660.855 1584.62
X Variable 6 2535.698 864.2199 2.934089 0.007927 738.4541 4332.941 738.4541 4332.941
X Variable 7 35.88267 9.544159 3.759648 0.001153 16.03451 55.73084 16.03451 55.73084
Observation Predicted Y Residuals Standard Residuals Percentile Y
1 341.4428 78.55718 1.574511 1.724138 5
2 159.2133 69.7867 1.398726 5.172414 9
3 208.4449 -17.4449 -0.34965 8.62069 10
4 208.8821 -63.8821 -1.28038 12.06897 13
5 85.97122 38.02878 0.762206 15.51724 17
6 169.1591 -47.1591 -0.9452 18.96552 17
7 89.41378 12.58622 0.252264 22.41379 21
8 139.984 -43.984 -0.88157 25.86207 22
9 152.777 -70.777 -1.41857 29.31034 34
10 72.81304 -28.813 -0.5775 32.75862 34
11 85.05055 -44.0505 -0.8829 36.2069 37
12 1.398422 32.60158 0.653429 39.65517 41
13 110.0989 -88.0989 -1.76576 43.10345 44
14 12.87683 -7.87683 -0.15787 46.55172 52
15 253.6965 44.30355 0.88797 50 57
16 232.1926 38.80738 0.777811 53.44828 82
17 120.6994 46.3006 0.927997 56.89655 96
18 133.6297 21.37027 0.428322 60.34483 102
19 58.40867 93.59133 1.875839 63.7931 122
20 78.55184 -21.5518 -0.43196 67.24138 124
21 69.89341 -17.8934 -0.35864 70.68966 145
22 104.3838 -67.3838 -1.35056 74.13793 152
23 -44.5376 78.53756 1.574118 77.58621 155
24 -7.78478 28.78478 0.57693 81.03448 167
25 -8.32685 25.32685 0.507623 84.48276 191
26 41.84824 -24.8482 -0.49803 87.93103 229
27 -0.7288 13.7288 0.275165 91.37931 271
28 58.2716 -48.2716 -0.9675 94.82759 298
29 39.27614 -30.2761 -0.60682 98.27586 420


2017 Awards Predictions

AL Comeback Player of the Year: There’s a case for many players who could potentially receive this award. For me personally, I would have to pick either Mike Moustakas, who has seen a resurgence after being plagued by injuries last season, or Ervin Santana, who has been the ace of the Twins’ staff and may help carry them to a playoff appearance.

NL Comeback Player of the Year: From a pitching standpoint, Zack Greinke would be a good choice, as he has pitched like the $206-million ace that Arizona thought he might be. Others such as Ryan Zimmerman and Michael Conforto should also be up for consideration.

AL Manager of the Year: This one is a bit tougher, because there are so many managers who have their teams performing beyond expectations for this season. If I could only pick one at the moment, it would be Mike Scioscia. Even with Mike Trout missing significant time due to injury and the rest of the roster mostly depleted of talent, it’s incredible to see that the Angels are just a couple games out of a Wild Card spot.

NL Manager of the Year: While Bud Black has the Rockies performing at their peak, I believe Torey Lovullo has to be the front-runner for this award, considering where the Diamondbacks were last season and how he has been able to unleash the maximum potential out of some players that the baseball community had previously written off, while overcoming injury woes that haunted the team last season.

AL Rookie of the Year: Aaron Judge. I know that he hasn’t been able to buy a hit since the All-Star break, but he has still out-performed other rookies above and beyond, and still has a good chance to break Mark McGwire’s record for most home runs by a rookie (48).

NL Rookie of the Year: Cody Bellinger. Just like with Judge, Cody Bellinger burst onto the scene and was crushing baseballs at an outrageous pace, much like Gary Sanchez did in 2016. Bellinger has out-performed other NL rookies, so this award should be his for the taking.

AL Cy Young: Chris Sale. So far, the Red Sox have been more than satisfied by the results of the trade they made last offseason. Their intimidating left-hander has been shutting down lineups just as Dave Dombrowski had hoped. An argument could also be made for Corey Kluber, but because he missed some time this season due to injury, I believe Sale should have no problem getting his first Cy Young, especially if he wins the pitching triple crown.

NL Cy Young: Despite both of these pitchers suffering from injuries, it would be hard to give the Cy Young to someone other than Clayton Kershaw or Max Scherzer. It’s hard to decide between the two of them at the moment, but the choice will probably be much more clear after the conclusion of the season.

AL MVP: If you had asked me this question before the All-Star break, I would have definitely picked Aaron Judge. However, due to his recent struggles, I would have to give this award to Jose Altuve. Altuve stands at the moment with an amazing .358 average while also leading in stolen bases. Altuve is often under-appreciated due to his small stature, but he has led the big leagues in hits since his arrival, and this season is his best opportunity to win a well-deserved MVP, especially since Trout also missed significant time with a thumb injury.

NL MVP: The answer out of many people’s mouths at the moment would be Giancarlo Stanton. However, despite the torrid pace at which he is hitting home runs, I believe someone like Nolan Arenado or Paul Goldschmidt is more deserving. I was also considering Bryce Harper before his injury, which could potentially sideline him for the season. If not for Kris Bryant, Nolan Arenado would have won the MVP last season, and now that both him and Goldschmidt have put their teams in positions to make deep playoff runs, it’s time in 2017 that all of these overlooked players finally get their well-deserved recognition.

Are the Yankees Following the Red Sox Blueprint For Success?

The Yankees and Red Sox are battling it out atop the AL East, which brings one back to the early 2000s, when these two teams were virtually competing solely against one another to crown a division champion, with the Yankees more often than not edging out Boston. However, the tables have turned, and since 2004 the Red Sox have three world titles while the Yankees have only had one. In the last two seasons in particular, the Red Sox have relied on the emergence of young prospects, veteran leadership, and savvy trades/free-agent signings to be successful. Are the 2017 Yankees an original creation of Cashman and Steinbrenner, or were they inspired by the strategy employed by other teams in more recent years, such as the Royals, Cubs, and even (in an ironic twist) their arch rivals, the Boston Red Sox?

The Red Sox recently called up highly-talented prospect Rafael Devers to fix their gaping hole at third base, and he has revitalized the lineup. He, along with Xander Bogaerts, can grow to be one of, if not the best 3B/SS combo in the majors, not to mention their presence at the plate, with Bogaerts being considered the best two-strike hitter in all of baseball. The Red Sox also have an outfield stocked with young talent. The Killer B’s (Benintendi, Bradley, and Betts) have each regressed slightly at the plate this season, but are still putting up respectable numbers. Bradley and Betts are also playing outstanding defense, as Betts leads the AL with 2.1 dWAR this season. However, one shouldn’t forget about Dustin Pedroia, who provides veteran leadership to help these young prospects adjust to life in the big leagues while remaining a staple at second base, as well as in the lineup.

One can’t say that the Red Sox rebuilding strategy has been perfect, as they currently have a revolving door at catcher, first base, and DH. They are clearly affected by the departure of David Ortiz’s intimidating reputation in the DH spot. Hanley Ramirez has been productive at the plate, but his defense is less than stellar, to put it mildly. Mitch Moreland and Christian Vazquez are just now getting hot bats after struggling at the onset of this season. More than anything, the Red Sox have been plagued by injuries to their starting pitching, as well as poor free-agent signings, most notably Pablo Sandoval, David Price, and even Rusney Castillo, who many forget is still in AAA-Pawtucket.

Overall, I believe the Yankees have learned a thing or two from the Red Sox. It’s important to give Dave Dombrowski credit for sticking with Devers at third, rather than trying to orchestrate a trade to acquire Josh Donaldson, as tempting as the idea was. The Yankees have groomed a host of young talent including Gary Sanchez, Aaron Judge, and now Clint Frazier. They also made good trades for Sonny Gray and others by not having to give up too many big names within their stacked farm system, and added Matt Holliday in the offseason to add some veteran leadership in the lineup at a low-risk contract. Like the Sox, the Yankees aren’t perfect, and are sitting on their hands with some expensive free-agent contracts (I think I hear Jacoby Ellsbury’s name somewhere). While the Red Sox rebuilding efforts have been more or less successful, I believe the Yankees should look at themselves when deciding how the team will shape out in the coming years. The Yankees from the mid to late 90s are one of the best examples of how teams can keep sustaining success. The Yankees in that era were built with a core group of prospects (the core four comes to mind), some established veterans such as Paul O’Neill and Tino Martinez, and other guys that helped create unbreakable clubhouse chemistry. All of these elements, and also a little bit of luck, are the keys to shaping the next great baseball dynasty, whomever that may be.

Thairo Estrada: A Yankees Prospect You May Not Have Heard Of

In 2017, the New York Yankees have one of the best minor-league farm systems in all of baseball along with others such as the Braves, White Sox, and Astros. As a result, there are some talented players who get lost among the shuffle, and one of them is Thairo Estrada. Estrada has been splitting his time between shortstop and second base this season in Double-A Trenton, but more recently has made second base his everyday position since top prospect Jorge Mateo was called up to play shortstop. Despite getting an All-Star nod for the Eastern League this season, Estrada still does not get talked about as much as other Yankees infield prospects including Gleyber Torres, Miguel Andujar, and even Mateo. Overall, Estrada is definitely worth taking a second look at alongside these other prospects, as someone who could be a solid middle infielder in the majors one day.

Estrada’s line of work speaks for itself this season. While the minor leagues do not have as much access to advanced stats, having seen Estrada play every day this season has given me a unique perspective into the facets of his game. Estrada has proven he can make adjustments, as evidenced by his strikeout percentage dropping roughly 4% from last season. As a result, his BABIP has skyrocketed to .344, and he has a slash line of .320/.375/.418. I attribute his lower slugging percentage as well as his low home-run total of 4 to the dimensions of the ballpark in Trenton. Not only is it 330 feet down each line, but the ballpark sits on the banks of the Delaware River, which as a result creates high winds that knock down potential home runs. If Estrada played in Yankee Stadium every day, he has the potential to hit 20 home runs, as evidenced by Brett Gardner, who in his two years in Trenton (2006-2007) hit as many home runs as I did (0).

Estrada also has a knack for base-running. This may come as a surprise to some given that he has only stolen three bases and been caught stealing nine times. However, on balls hit into the gap or down the line, Estrada has the ability to take the extra base, which has resulted in his wRC+ being 121 this season. Additionally, his spray chart shows that he has the ability to hit the ball to all fields, which makes it tougher for defenses to scout him, and gives him more opportunities for hits. There may not be many stats on Estrada’s defense, but after struggling somewhat at shortstop, he has become far more comfortable at second base, and has not made an error in 19 games.

If Estrada can continue this performance, we might see him in the majors soon, and he could potentially create a great middle-infield combo with Jorge Mateo if Torres’ recover from Tommy John surgery doesn’t go according to plan. So far through 14 games in Trenton, Mateo has a slash line of .396/.508/.755 and a BABIP of .486. The high OBP is a result of Mateo walking in 15.2% of his plate appearances. If Estrada does not play for the Yankees, then the Yankees should be smart enough to utilize his value and include him in a trade package for a big-name player (Sonny Gray, anyone?).

Are the Mets in Rebuilding Mode Once Again?

The Mets are the talk of the town…for all the wrong reasons. They currently sit at a 31-41 record and are 12 games behind the Washington Nationals in the NL East, which as of now seems to be theirs for the taking. The Mets boast one of the worst bullpens in the majors and have been plagued by injuries as well as underperformance from the bulk of their lineup. With the results of this season, many are beginning to wonder if it’s time to turn the page on this current pack of Mets players, many of whom were on the 2015 team that lost to the feisty Kansas City Royals in the World Series. I will attempt to go group by group in an effort to determine whether or not the Mets should begin a new rebuilding process, the most dreaded phrase in sports.

Starting with the outfield, Yoenis Cespedes is locked in for three more years in his current contract. It’s understandable why the Mets were looking to sign him in the offseason based on his performance in 2015 and 2016. However, injuries and poor performance have contributed to the current record that the Mets have. Cespedes still won’t lose his spot in left. Curtis Granderson, due to his age, will most likely not be re-signed, as well as Jay Bruce who, if he is not traded before the deadline, will most certainly test free agency. Juan Lagares has been injury-prone the last couple years but the one piece of good news is that Michael Conforto has seen a resurgence since coming back from Triple-A Las Vegas. Also, one of their top prospects, Brandon Nimmo, should receive regular playing time in the outfield, if not this season, then definitely in 2018.

Next, we have the infield, which has been decimated by injuries. Neil Walker and Asdrubal Cabrera have struggled through injuries (and who knows if/when David Wright will ever step on a baseball field again). Jose Reyes and Lucas Duda have mightily underperformed. The good news for the Mets is that Cabrera, Walker, and Reyes will be gone after the season, which means that the infield can get much younger. Top prospects Dominic Smith and Amed Rosario will be September call-ups and, if all goes well, can be regulars in the lineup next year. T.J. Rivera and Wilmer Flores have proven to be reliable pieces in the lineup. Despite some injuries from Flores, he has made up for it with his versatility in both the field and in the lineup, giving manager Terry Collins options to choose from. While Flores and Rivera may not be long-term solutions, they are the best options that the Mets have at the moment. As far as catching is concerned, Travis d’Arnaud is probably the Mets’ best option right now, although he has severely underperformed since being traded to them. The Mets should try to get another catcher in free agency.

Finally, the best pitching staff is a huge question mark, but also a big concern among scouts. Matt Harvey clearly no longer has any interest in remaining with the team and Noah Syndergaard, Zack Wheeler, and Steven Matz are just injuries waiting to happen. Even Jacob deGrom, who has been I believe the best starter this season, has a history of arm injuries that makes Mets front-office personnel nervous. Even Robert Gsellman and Seth Lugo are recovering from injuries sustained during this season. The bullpen has been just as bad. The bullpen so far has logged 257 innings to the tune of a 4.97 ERA. Not to mention they have not had a reliable closer since Jeurys Familia has been both suspended and injured this season, and the rest of the bullpen outside of Addison Reed and Jerry Blevins has been downright horrendous.

Overall, the Mets need to begin the next phase of the rebuilding process. With aging veterans and current players underperforming, it’s clear that the time for a championship has come and gone for this group. The Mets need to get younger and it starts with the old addition-by-subtraction technique. By dumping aging veterans with big contracts, the Mets will be able to allocate their resources and maybe pick up some pieces in free agency while simultaneously giving their top prospects playing time and allowing them to develop. As the great Cosmo Kramer once said on Seinfeld, “I think it’s time that we shut down and re-tool.”

The Free Agent Value of Michael Pineda

Michael Pineda is having by far the best season of his career ever since he broke into the big leagues with Seattle in 2011. This is good news for Pineda who is in a contract year and looking to earn a huge payday on the open market this winter. However, this is bad news for teams, especially the Yankees, who have many questions surrounding their starting rotation with CC Sabathia also in a contract year and Masahiro Tanaka having the chance to opt out of his current contract after the season (although the latter seems unlikely at the moment). Pineda reminds me of one player in particular: former Yankee Ivan Nova.

Like Pineda, Nova has a fastball in the mid-90s and good secondary pitches, including a nasty curve and a change-up which he has begun to develop under Pittsburgh Pirates pitching coach Ray Searage, aka “the pitcher whisperer”. While Nova’s strikeout numbers have gone down, he has learned to pitch rather than just throw, which has resulted in fewer guys getting on base against him as well as his K/BB ratio going down, which I believe have been key contributing factors to his success in Pittsburgh. Also like Pineda, Nova hit the ground running, going 16-4 with a 3.70 ERA in 2011, and he was arguably the Yankees’ second-best starter behind Sabathia. However, as teams began to expose tendencies, combined with mounting injuries, Nova was never able to maintain the same level of success in New York.

The same could be said for Pineda, who missed two full seasons and most of 2014. Even after coming back in 2015, Pineda still struggled to maintain any level of consistency, after posting respectable numbers as a rookie. Now, Pineda has harnessed the power of his wipe-out slider and has become a ground ball pitcher (51.5%) to cope with the home-run haven that is Yankee Stadium. His K/BB ratio has gone down and his WHIP has dropped from 1.35 to 1.13 this season. The formula is simple: the fewer baserunners there are, the better a team’s chances are of winning. Also, like Nova, Pineda is using a change-up more in his pitching repertoire, to complement his slider. As a result, he has generated a 43.3% swing and miss percentage on pitches outside the zone, a 7% increase from last season. Additionally, they are close in age, since Nova was 30 when he signed his new contract, and Pineda will be 29.

The Pirates ended up giving Nova a three-year, $26-million contract last offseason. As long as Pineda continues to have success this season, he will also end up getting a similar deal. I predict he will end up staying with the Yankees for three years for somewhere in the range of$36-39 million simply because the Yankees will be desperate for starting pitching and may even pay a little bit over his market value to keep him. These types of deals are always risky, and many look to the Dodgers signing Rich Hill. However, Pineda has proven that he has always had the talent to pitch in New York and it seems that he finally has his head in the right place to help him reach his full potential. I believe that the Yankees will also re-sign Sabathia to a one-year deal in the range of $5-10 million, considering he will be 37 next season. If the Yankees manage to acquire another lefty or even sign Jake Arrieta, the Yankees starting rotation could be something to look out for in 2018.