Since being activated from the IL, Brandon Nimmo has a .263/.531/.632 line in 32 PA. The Mets have played 10 games in that span and Nimmo has started seven of those. In those seven, the Mets are 5-2. And in one of the losses they had a six-run lead going to the bottom of the ninth inning.
The Mets have eased him back in, giving him some time off when the other team starts a lefty. But last night when the D’Backs started lefty Robbie Ray, it was Robinson Cano and Michael Conforto on the bench and Nimmo in the lineup. He responded with a homer in his only PA against Ray.
Obviously that OPS won’t remain that high the rest of the season. But we should keep in mind that in this stretch he has a .300 BABIP and all of his action has come against teams over .500 and in the hunt for the playoffs. He’s not taking advantage of a second division team’s starter just called up from the minors with the expanded rosters.
Nimmo is an offensive force with his ability to get on base at a high clip combined with enough power that they can’t just groove him pitches to get a strike. Everyone talks about the lousy bullpen as a reason the Mets struggled so much this season – and rightly so. But don’t forget that they essentially played without Nimmo from the middle of April (when he first missed time with the neck injury) until the beginning of September.
And the Keon Broxtons and Carlos Gomezes and Juan Lagareses that they used to replace him were terrible.
I’m having difficulty understanding why a manager has an issue with one of his top pitchers (THOR) because that pitcher prefers and performs better with a particular catcher? Maybe someone can explain to me why, especially in a race for the wildcard why this is an issue. Maybe that’s why I strongly support a new manager in 2020.
I found the following formula for FIP on BR:
FIP = (13*HR + 3*(BB+HBP) – 2*SO) + constant
Can anyone explain the nature/determination of the coefficients?
For example, why is a HR 6.5 times worse than a SO is good?
“It’s been used in a million different applications (like the Fangraphs WPA game graphs), but assigning average run values to events opened up hundreds of new avenues for sabermetrics analysis. The run vales pertinent here are in the table below. Click for a bigger version.
Fip_values_medium
These values give the average amount of runs scored from the point of the event occurring to the end of the inning (Tango calculated these averages from every game played from 1974 to 1990). If we take every event resulting from a ball hit in play and average them out with respect to how often they occur, the average ball in play results in a net loss of -0.04 runs. To simplify the formula, Tom Tango added +0.04 to each run value, which algebraically excised balls in play. Simply multiply each modified run value by 9 innings, and you have the coefficients used in FIP (13 for HR, 3 for BB, and 2 for K). FIP doesn’t actually ignore balls hit into play. Even though they don’t appear in the final formula, run values for balls hit in play live on in the coefficients.”
https://www.athleticsnation.com/2010/4/27/1446531/statistically-significant-fip
As usual, Brian, thanks for making me feel like part of your community. You’re a quality human being
Finally! A new podcast. Lifelong Dodger fan Bob Lowe dropped by to discuss this weekend’s Mets-Dodgers series.
Also, Bob is working for an Atlantic League team and we discuss the league’s implementation of a computerized strike zone.
Download and listen here — http://cast.rocks/hosting/13288/Bob-Lowe-91219.mp3