Category Archives: Career Ranking

Sandy Koufax

Sandy Koufax was trending on Twitter which often is not a good sign but thankfully it was just to celebrate his birthday.  Many made claims he was one of the greatest pitchers of all time.  Let’s look at his career cut short by injury.

Sandy Koufax

Year Rank WAA TeamID Pos
1956 XXXXX -1.24 LAN PITCH
1957 XXXXX -0.15 LAN PITCH
1958 -052- -2.18 LAN PITCH
1959 XXXXX -0.82 LAN PITCH
1960 XXXXX -0.48 LAN PITCH
1961 +043+ 3.65 LAN PITCH
1962 +022+ 5.65 LAN PITCH
1963 +002+ 11.21 LAN PITCH
1964 +005+ 9.26 LAN PITCH
1965 +001+ 11.13 LAN PITCH
1966 +001+ 13.42 LAN PITCH
Total 50.39 978

Koufax had arthritis in his elbow at the absolute peak of his career.  A greater than 13 WAA is an extraordinary season.  He won 3 Cy Young awards. You can guess from above which years those were.   Even though he ranked #2 in 1963,  he won NL MVP.   Some guy called Hank Aaron playing for the Milwaukee Braves was very slightly ahead of him that year according to this data model but it was close enough to be a toss up.

At ~50 WAA he is technically border line HOF solely based on that.  It’s probable Koufax could have doubled or more  that career WAA  had he not had a career ending injury.  That would have made him one of the best pitchers of all time based solely on career WAA.

There are many factors to consider for awards, HOF induction, player acquisitions, etc. other than raw WAA.    He pitched a bunch of no hitters and a perfect game and lots of strikeouts. .

Below is the most important other factor which gets him in HOF first ballot.

Rank WAA IP ERA Gs Gr Name_TeamID Pos
+013+ 3.49 57.0 0.95 7 1 Sandy_Koufax_LAN PITCH  post season

He pitched 57 innings with a sub 1.00 ERA in post season.  This compiles into a post season WAA value  ranked #13 among all MLB players ( both BAT and PITCH )  who played in playoffs from 1903-2018. This led to LAN winning 4 World Series trophies; the only trophy that matters. in baseball.  Update:  At the time Koufax was inducted into HOF (1972) he was ranked #4 best post season player behind Christy Mathewson, Babe Ruth, and Lou Gehrig according to this data model.  There are a lot more playoff games per year in modern baseball.

Happy Birthday Sandy Koufax.

That’s all for this first post of the 20s decade.  Minor leagues coming next .  Until then ….

Top 25 MLB players for 2010 decade

The other day there was an article going around showing the top ten NHL players for the 2010s which stirred some controversy as no Blackhawks were named despite having players winning 3 Stanley Cup trophies, a rather difficult feat.  We don’t have data models ranking hockey, football, or basketball but we do have one for baseball.  Let’s look at the top 25 MLB players for 2010 decade according to this data model and for baseball-reference value system WAR.

WAA 2010-2019

Rank 2019 Rank WAA Name_Teamid Pos
+001+ +025+ 80.95 Clayton_Kershaw_LAN PITCH
+002+ +043+ 50.86 Edwin_Encarnacion_TOT 3B-DH-1B
+003+ +001+ 49.62 Justin_Verlander_TOT PITCH
+004+ +012+ 48.82 Mike_Trout_ANA CF-RF-LF-DH
+005+ -020- 46.77 Miguel_Cabrera_DET 1B-3B-DH
+006+ +014+ 45.72 Nelson_Cruz_TOT RF-LF-DH
+007+ +017+ 45.72 Max_Scherzer_TOT PITCH
+008+ +129+ 42.19 Paul_Goldschmidt_TOT 1B
+009+ +009+ 41.10 Zack_Greinke_TOT PITCH
+010+ XXXXX 40.72 Jose_Bautista_TOT RF-3B-DH-1B-CF-BAT-LF
+011+ +160+ 39.86 Ryan_Braun_MIL LF-RF-1B
+012+ XXXXX 39.63 Giancarlo_Stanton_TOT RF-DH-LF
+013+ +003+ 39.14 Jacob_deGrom_NYN PITCH
+014+ XXXXX 39.04 Chris_Sale_TOT PITCH
+015+ +022+ 39.02 Nolan_Arenado_COL 3B
+016+ XXXXX 38.64 Carlos_Gonzalez_TOT LF-CF-RF
+017+ +133+ 38.47 Madison_Bumgarner_SFN PITCH
+018+ XXXXX 38.30 David_Ortiz_BOS DH
+019+ XXXXX 35.28 Adrian_Beltre_TOT 3B-DH
+020+ XXXXX 35.22 Albert_Pujols_TOT 1B-DH
+021+ +013+ 33.64 Freddie_Freeman_ATL 1B-3B
+022+ XXXXX 33.39 David_Price_TOT PITCH
+023+ XXXXX 33.26 Johnny_Cueto_TOT PITCH
+024+ -143- 33.20 Robinson_Cano_TOT 2B-1B
+025+ +041+ 33.03 J.D._Martinez_TOT LF-RF-DH

A list like this is rather arbitrary.  When people reflect on  decades they don’t ponder the decade between say 2008-2017.  These always occur when the odometer turns on earth like tonight and we go from 2019-2020.  Players who started and ended their careers mid decade lose many years to players who came into their prime around 2010 and are still playing like Clayton Kershaw.  Mike Trout had his first blow out year in 2012 but is still 30+ WAA behind Kershaw.

In 2019 Miguel Cabrera ranked #20 in the bottom 200, a list no one wants to be #1, which means he’s hemorrhaging value.  Robinson Cano also put up sub average numbers in 2019 but still in the top 25 of this decade.

The two highlighted players, Pujols and Ortiz were also in the top 4 players of the 2000-2009 decade.

Top MLB Players 2000-2009

Rank 2009 Rank WAA Name_Teamid Pos
+001+ +022+ 88.07 Alex_Rodriguez_TOT SS-3B
+002+ +003+ 77.26 Albert_Pujols_SLN 3B-1B-LF-RF
+003+ +112+ 69.47 Manny_Ramirez_TOT RF-DH-LF
+004+ +081+ 54.20 David_Ortiz_TOT DH-1B

Pujols and Ortiz were #2 and #4 MLB players in the 2000s and made it into the top 25 in the 2010s.  Ortiz retired after the 2016 season so he even missed three years.  Pujols is the only player still playing of the top 4 above.

It is clear from above that Clayton Kershaw is the baseball player of the decade according to this data model.  WAR may not agree but we’ll get to that later.  Edwin Encarnacion is listed as #2 in this model and #48 for the decade in WAR which represents the biggest difference between the two systems.  Whenever there is a discrepancy like this I check career numbers.  Here’s Edwin’s career according to this data model.


Year Rank WAA TeamID Pos
2005 XXXXX 0.23 CIN 3B
2006 +168+ 1.89 CIN 3B
2007 XXXXX 0.80 CIN 3B
2008 XXXXX 0.48 CIN 3B
2009 XXXXX -1.36 CIN 3B
2009 XXXXX 0.88 TOR 3B
2010 XXXXX 1.49 TOR 3B
2011 XXXXX 0.99 TOR DH-3B-1B
2012 +012+ 6.15 TOR DH-1B
2013 +009+ 6.40 TOR 1B-DH-3B
2014 +013+ 6.32 TOR 1B-DH
2015 +010+ 7.41 TOR DH-1B
2016 +008+ 6.97 TOR DH-1B
2017 +035+ 4.75 CLE DH-1B
2018 +023+ 5.42 CLE DH-1B
2019 +043+ 2.69 SEA 1B-DH
2019 +043+ 2.27 NYA DH-1B
Total 53.78 1636

Encarnacion had a pretty consistent decade with a relatively mediocre start to his career.  His career year was 2015 where he drove in 111 runs and scored 94.  In 2016 he drove in 127 and scored 99.  The numbers check out.  Unfortunately for him he played for Toronto which is home to a hitter friendly park.  WAR downgrades or upgrades players based upon the type of parks they play in.  The same phenomenon happened with Larry Walker who played much of his career in COL and Montreal.

The numbers above are correct and consistent with how this data model calculates value from Babe Ruth to Neifi Perez.  Edwin Encarnacion contributed each year to his team’s total WAA according to Pythagorean Estimation the amount listed above in the WAA column.  That he exceeds Mike Trout was surprising but he had two more productive years this decade to rack up numbers.  If we do a 10 year split next year Trout will clearly be #2 but it will take years for him to overtake Kershaw unless Kershaw tanks by putting up negative numbers and losing games for LAN.

Let’s see what WAR thinks of this decade.

WAR 2010-2019

Rank x Rank WAR oWAR dWAR Name_Teamid Pos
+001+ +003+ 73.2 71.1 3.7 Mike_Trout_ANA CF-RF-LF-DH
+002+ +095+ 57.2 X X Clayton_Kershaw_LAN PITCH
+003+ +022+ 55.4 X X Max_Scherzer_TOT PITCH
+004+ +005+ 54.9 X X Justin_Verlander_TOT PITCH
+005+ XXXXX 53.7 49.6 8 Robinson_Cano_TOT 2B-1B
+006+ XXXXX 51.8 46.9 -4.1 Joey_Votto_CIN 1B
+007+ +196+ 50.3 39.9 11.8 Adrian_Beltre_TOT 3B-DH
+008+ +121+ 47 X X Cole_Hamels_TOT PITCH
+009+ +176+ 46 X X Chris_Sale_TOT PITCH
+010+ +018+ 44.6 37.7 8.8 Josh_Donaldson_TOT BAT-3B-DH
+011+ +028+ 43.5 X X Zack_Greinke_TOT PITCH
+012+ XXXXX 43.1 47.1 -9.9 Miguel_Cabrera_DET 1B-3B-DH
+013+ +166+ 42.9 35.9 9.2 Evan_Longoria_TOT 3B-DH
+014+ +134+ 42.3 36.8 -2.3 Paul_Goldschmidt_TOT 1B
+015+ XXXXX 41.5 36.4 9.6 Buster_Posey_SFN CR-1B
+016+ +012+ 41.4 29.7 10.1 Mookie_Betts_BOS CF-2B-RF
+017+ XXXXX 41.4 47.7 -4.7 Andrew_McCutchen_TOT CF-RF-LF
+018+ XXXXX 40.2 29 14.8 Ian_Kinsler_TOT 2B-DH
+019+ XXXXX 39.4 33.5 0 Giancarlo_Stanton_TOT RF-DH-LF
+020+ XXXXX 38.9 32.8 5.8 Ben_Zobrist_TOT RF-2B-1B-CF-SS-LF
+021+ XXXXX 38.8 X X David_Price_TOT PITCH
+022+ +085+ 38.3 40 1.5 Jose_Altuve_HOU 2B-DH
+023+ +066+ 38 25.2 10.4 Brett_Gardner_NYA LF-CF
+024+ +023+ 37.8 25.7 13.7 Nolan_Arenado_COL 3B
+025+ XXXXX 37.8 20.2 12 Jason_Heyward_TOT RF-CF

Yikes!  Trout is so far ahead in #1 after only 8 productive years on mostly mediocre teams.  On reddit in r/baseball I have seen comments suggesting Trout’s recent contract is worth $600M+ based upon the above.  This data model does not have a salary component since finance and contracts are extremely complicated.

After building the TC simulator and running handicapping numbers these last few years it became obvious good baseball teams win based upon the sum of most their players playing well above average.  The lineups on winning playoff teams usually consist of 8 players all well above average.  Is it wise for a team to spend most their money on a single player then skimp on the rest?  How did that $30M/year Manny Machado contract work out for SDN last season?

The numbers above are used by teams to determine salary which means they mean millions of dollars to players .  Players learn to game WAR stats because of how important those numbers  are to their livelihood.  WAR undervalues relievers so relievers want to become starters unless they can close and rack up those valuable saves so important to Draft Kings teams.

Joey Votto is a big fan of wRC+ according to this article.  Let’s look at Joey’s 2019 stats according to both models.

Rank WAA BA OBP PA RBI R Name_TeamID Pos
-071- -2.79 0.261 0.357 608 47 79 Joey_Votto_CIN 1B

Joey Votto made the bottom 100 in 2019.  His batting average and OBP look OK though.  His run production highlighted in brown is very poor. He is 14th worst in MLB for run production in RISP situations last season.   An old, but still accurate, explanation of RISP according to this data model can be read here.

Bottom line: Joey Votto had a bad season.  The Reds went 75-87 in 2019 for a real team WAA of -12 .  Joey Votto’s contribution was -2.79 of that.  Let’s see what WAR thinks.

Rank WAR oWAR dWAR Name_TeamID Pos Year
XXXXX 1.6 1.1 -0.3 Joey_Votto_CIN 1B 2019

WAR have him underwater defensively with dWAR.  His cumulative WAR is respectable and shows no indication he had much of a bad season other than it’s lower than his usual and he’s unranked.   Not sure how he ended up with a 1.6 cumulative WAR when his oWAR is only 1.1 with a negative dWAR.

Joey Votto had his career year in 2010 ranking #8 and he’s ranked #49 for the decade according to this data model .  This is a reverse discrepancy from Edwin Encarnacion.  WAR rewards players who excel on their Draft Kings teams, this data model rewards players who excel on their real baseball teams; players who score runs or not let up runs.  Runs are the currency required for wins.

Jason Heyward somehow made the WAR list as well at #25.  There are no Cubbies or players who ever played with the Cubs on the WAA list.

The dWAR column was manually highlighted to show high and low values.  Looking at dWAR can be useful to determine who can field, who’s OK, and who should probably be DH.  The Cubs hired Jason Heyward for his defense which is second highest among the 25 in the WAR list.

Not much more to say about this last post of the decade.  I don’t care what WAR thinks, Clayton Kershaw is  the best player between 2010-2019.  He may not break top tens much anymore but he’s consistently a good well above average player every year.  He is what they call a generational player now.  Mike Trout is waiting in the wings and will soon be top dog.  He isn’t right now after only 8 years.  He is top dog for Draft Kings teams however and probably undisputed MVP of those leagues each season.

Minor leagues coming next year.  Happy New Decade.  Until then ….

Top 25 MLB Players for 2017, 2018, 2019

This post will show the top 25 mlb players for the last 3 years according to this data model like what was done last year.  WAR evaluations will be included for comparison and contrast.  It takes year to year consistency to make the top of a list like this.  All the players below are the elite of MLB.


Rank 2019 Rank WAA Name_Teamid Pos
+001+ +003+ 25.81 Jacob_deGrom_NYN PITCH
+002+ +017+ 23.33 Max_Scherzer_WAS PITCH
+003+ +001+ 22.72 Justin_Verlander_TOT PITCH
+004+ +041+ 22.70 J.D._Martinez_TOT RF-DH-LF
+005+ +022+ 19.74 Nolan_Arenado_COL 3B
+006+ +025+ 19.40 Clayton_Kershaw_LAN PITCH
+007+ +005+ 17.79 Anthony_Rendon_WAS 3B
+008+ +009+ 17.16 Zack_Greinke_TOT PITCH
+009+ +045+ 16.61 Bryce_Harper_TOT RF-CF
+010+ +039+ 16.55 Mookie_Betts_BOS RF-CF
+011+ +027+ 16.17 Christian_Yelich_TOT CF-LF-RF
+012+ +002+ 15.96 Gerrit_Cole_TOT PITCH
+013+ +014+ 15.81 Nelson_Cruz_TOT DH
+014+ +008+ 15.60 Cody_Bellinger_LAN 1B-LF-CF-RF
+015+ +012+ 15.54 Mike_Trout_ANA CF-DH
+016+ +043+ 15.12 Edwin_Encarnacion_TOT DH-1B
+017+ XXXXX 15.12 Corey_Kluber_CLE PITCH
+018+ +004+ 15.04 Hyun-Jin_Ryu_LAN PITCH
+019+ +049+ 15.01 Charlie_Blackmon_COL CF-RF
+020+ +117+ 14.89 Aaron_Nola_PHI PITCH
+021+ XXXXX 14.62 Giancarlo_Stanton_TOT RF-DH-LF
+022+ +023+ 14.62 George_Springer_HOU CF-RF-DH
+023+ +028+ 14.59 Stephen_Strasburg_WAS PITCH
+024+ +172+ 14.45 Aaron_Judge_NYA RF-DH
+025+ +072+ 14.26 Javier_Baez_CHN 2B-SS-3B

The above shows rank for this three year split as well as rank for the 2019 season.  The WAA column is the addition of all three years used to determine rank.  As always, pitchers and hitters, AL and NL, all ranked together like in one big bowl of soup.  Pitchers produce runs by not giving up runs, hitters produce runs by driving them in or by scampering around bases to score them.

In the past three years there have been almost 2000 players who made an MLB appearance making the above 25 players considered top 1%ers.   They all can be considered superstars these last three years.  That doesn’t make them superstars next season.  The above is a reflection upon the past.

Most of the above players are not free agents.  At 25.81 Jacob deGrom averaged a little above 8 WAA per year.  This means that each year, if the rest of each Mets team played completely average, the Mets would end each season at 85-77 based upon deGrom’s pitching alone.  He has pitched well.  His team on the other hand …

Since the 2016 season dropped off these 3 year splits Cubs players will drop the most.  Javier Baez hangs in there at #25 having a career year in 2018.

Ranks 7-25 are fairly bunched up.  Although the top three, clearly in the lead are pitchers, there are only 10 pitchers in the top 25.  Mike Trout is ranked #15 last three years which will differ from the WAR table below.


Rank 2019 Rank WAR oWAR dWAR Name_Teamid Pos
+001+ +003+ 25.2 24.9 1.1 Mike_Trout_ANA CF-DH
+002+ +012+ 24.1 17.2 5.5 Mookie_Betts_BOS RF-CF
+003+ +022+ 21.9 X X Max_Scherzer_WAS PITCH
+004+ +008+ 21.3 X X Jacob_deGrom_NYN PITCH
+005+ +005+ 20.4 X X Justin_Verlander_TOT PITCH
+006+ +002+ 19.4 19.8 1.1 Alex_Bregman_HOU 3B-SS
+007+ +032+ 19 14.5 3 Aaron_Judge_NYA RF-DH
+008+ +085+ 18.7 X X Aaron_Nola_PHI PITCH
+009+ +009+ 18.6 19.1 -1.4 Christian_Yelich_TOT CF-LF-RF
+010+ +023+ 18.5 15.3 4.1 Nolan_Arenado_COL 3B
+011+ +013+ 18.5 11.4 8 Matt_Chapman_OAK 3B
+012+ +102+ 18.1 16.7 2.4 Jose_Ramirez_CLE 3B-2B
+013+ +043+ 18.1 15 5.6 Francisco_Lindor_CLE SS
+014+ +001+ 17.4 13.4 2.1 Cody_Bellinger_LAN 1B-LF-CF-RF
+015+ +085+ 17.2 16.9 1.6 Jose_Altuve_HOU 2B
+016+ +015+ 16.4 16.6 0.9 Anthony_Rendon_WAS 3B
+017+ +028+ 15.8 X X Zack_Greinke_TOT PITCH
+018+ XXXXX 15.4 8.5 9.3 Andrelton_Simmons_ANA SS
+019+ +015+ 15.4 X X Stephen_Strasburg_WAS PITCH
+020+ +176+ 15.2 X X Chris_Sale_BOS PITCH
+021+ +134+ 15 10.7 5.5 Lorenzo_Cain_TOT CF
+022+ +055+ 15 13.4 -0.8 Freddie_Freeman_ATL 1B-3B
+023+ +010+ 15 X X Gerrit_Cole_TOT PITCH
+024+ +014+ 14.6 12 5.1 Trevor_Story_COL SS
+025+ +005+ 14.3 X X Mike_Minor_TOT PITCH

All WAR data displayed here is calculated by  Our detailed explanation written in 2013 about WAR can be read here.  The above rank columns are the same as in the WAA table.  Ranks for WAR are calculated from the combined WAR for each player using the same methodology used to rank WAA values.

Baseball-reference calculates an oWAR (offense) and dWAR (defense) component which is shown above.  Since WAR folds very subjective and error prone defense theories into their calculation,  showing all three WAR columns provide context as to why some players rank so high or low.

Slight diversion: This brings us back to 2012 when this happened.

Rank WAR oWAR dWAR Name_TeamID Pos Year
+039+ 4.8 1.5 3.6 Darwin_Barney_CHN 2B 2012

Darwin Barney had a combined WAR of 4.8 in 2012 ranking him +39 in MLB on a Cubs team that went 61-101, WAA=-40.     By showing dWAR we can see Darwin Barney’s defense was a significant factor in his combined WAR.  He did win a gold glove that season but how many games did his defensive skills win for the Cubs?  Here’s his long form record according to this data model.

Rank WAA BA OBP PA RBI R Name_TeamID Pos
-126- -1.87 0.254 0.299 588 44 73 Darwin_Barney_CHN 2B  2012

This is a rather large dispute between the two value systems.  Based on the Cubs overall seasonal record this data model shows what part of that –40 Darwin Barney contributed, -1.87.  That’s how this model works.  Not sure what WAR=4.8 is supposed to mean.

FanGraphs has their own own way of calculating WAR which is described in this article:

A Layman Attempts To Calculate WAR: Batting Runs. 

The article ends with them calculating only one component of WAR.  Even the person interviewed didn’t fully understand how a Fangraph WAR is calculated.

This data model found baseball-reference to be the most accurate after spot checking which is why we use it for context in every post like this.  Fangraph WAR is very inflated.  Generally this model and WAR agree on top and bottom players with exceptions.  This is why playoff horse race and WAR models converged in late stages of playoff season because concentration of top players playing is highest.

Highlighted in bold blue in the above WAR 3 year split table show players who propelled to the top based upon rather subjective defense theories.  Mike Trout isn’t one of them, his value is mostly oWAR which makes his an almost apples to apples comparison with this model.

Trout plays for the Angels who have been a below average team these last three years.  This model counts runs actually produced.  WAR estimates runs based on hits and lots of other factors.  That model favors players like Trout.  Trout is a #1 player if MLB baseball wins and losses were determined by Draft Kings.  In real baseball games however teams win by the runs they score and don’t let up which is what this data model counts.  That Trout is ranked  #15 by this data model for the last three years is still extremely good making him an elite MLB player on a mediocre sub average team.

The next post will show Trout ranking #4 for the 2010 decade even though he didn’t play an entire decade.  He will soon be the #1 active player based upon career numbers and most likely a first ballot HOF — especially if ANA can win a World Series now that Joe is managing them.

Top 25 players of the decade coming tomorrow before the decade ends — hopefully.  Until then …

Mike Montgomery Traded

Mike Montgomery was recently traded to Kansas City who will make him a starter instead of reliever.  As has been mentioned here over and over Sabermetrics, including WAR do not value relief very highly.  Since Mike Montgomery is approaching Free Agency he obviously wants the good starter stats to make him appear more valuable in the FA bidding market.

Since Mike Montgomery threw the final pitch of the 2016 baseball season helping secure the first World Series in all living Cubs fans lifetime, let’s look back at his career.

This model does not discriminate against relief pitchers and, except for this year and last year,  Mike Montgomery was very good for the Cubs.  Let’s see why.

Mike Montgomery Full Career

Year Rank WAA Name_TeamID Pos WinPct League Age
2019 XXXXX -0.76 Mike_Montgomery_CHN PITCH XXX mlb
2018 XXXXX 0.23 Mike_Montgomery_CHN PITCH XXX mlb
2017 +105+ 2.92 Mike_Montgomery_CHN PITCH XXX mlb
2016 +069+ 1.18 Mike_Montgomery_CHN PITCH XXX mlb
2016 +069+ 2.60 Mike_Montgomery_SEA PITCH XXX mlb
2015 XXXXX -1.45 Mike_Montgomery_SEA PITCH XXX mlb
2015 XXXXX -0.17 Mike_Montgomery_SEA PITCH 0.488 aaa 25
2014 XXXXX 0.06 Mike_Montgomery_TBA PITCH 0.502 aaa 24
2013 XXXXX -1.41 Mike_Montgomery_TBA PITCH 0.442 aaa 23
2012 -071- -3.11 Mike_Montgomery_KCA PITCH 0.347 aaa 22
2012 -022- -3.63 Mike_Montgomery_KCA PITCH 0.218 aa 22
2011 -141- -2.39 Mike_Montgomery_KCA PITCH 0.429 aaa 21
2010 XXXXX 0.92 Mike_Montgomery_KCA PITCH 0.569 aa 20
2010 +188+ 1.70 Mike_Montgomery_KCA PITCH 0.810 aplus 20
2009 +129+ 2.12 Mike_Montgomery_KCA PITCH 0.683 aplus 19

The above is a full career table showing all the leagues covered by this model.  Minor league records include WinPct and Age because that is important for those leagues.  This type of table sorts most recent year from the top.

Note: Montgomery’s 2016 rank is based upon the sum of his CHN and SEA record for that year.  WAAs are not added together in different leagues like his two 2012 records.  Those ranks were based upon the WAA recorded for each league.  WAAs cannot be summed across different classes of players (i.e. AA and AAA).

Mike Montgomery played very well for KCA’s A+ affilliate, the Wilmington Blue Rocks, in 2009 and 2010.  He struggled in AA and AAA for many years and got dealt to Tampa Bay and Seattle where he made his first MLB appearance in 2015 — and that didn’t go well either.  The Mariners had him start 16 games that year.  In 2016 Seattle made him a long reliever which he excelled at.

He came to the Cubs in 2016 after becoming a reliever  and had a very good season ranking #69 in MLB according to this data model.  In 2017 he ranked #105 which is very good.  Last season he was almost completely average, even steven and this season hasn’t gone well for him.

The rumor mill buzzed that he began asking to be a starter in 2017 which means his relief stints weren’t getting him the credit he deserved because starting pitching is where the glory in Sabermetrics lie.  Let’s see what WAR thinks of his career.

Mike Montgomery Career WAR Edition

Year Rank WAR IP Name_Tm Pos
2015 XXXXX 0.5 90.0 Mike_Montgomery_SEA PITCH
2016 XXXXX 2.0 100.0 Mike_Montgomery_TOT PITCH
2017 +197+ 2.2 130.2 Mike_Montgomery_CHN PITCH
2018 XXXXX 1.3 124.0 Mike_Montgomery_CHN PITCH
2019 XXXXX -0.3 27.0 Mike_Montgomery_CHN PITCH

Ranks provide context to the weighting factor of a value system.  According to WAR Montgomery just barely made their top 200 in 2017 and unranked every other year — quite a difference from this model’s rating of him.   The above demonstrates how Sabermetrics does not value relief highly which is why pitchers either want to close as a reliever or start.

Montgomery wants to start for his future contract (i.e. $$$).   Possibly his angst over starting and the disrespect he received from Sabermetrics caused his decline in later years.  Montgomery provided significant help with the Cubs winning a WS and getting to NLCS in 2017.  Teams, however, cannot afford players who play for their Draft Kings teams and not for their real team.   WAR has a blind spot for relievers and unfortunately teams still use that measure to bid contracts.

Moneyball is about gathering players who create wins and as long as teams  are in servitude with stats like WAR, wRC+, OPS+ ,etc. etc. , those teams will overpay for players allowing the Moneyball teams to pick up bargains.  The real Moneyball that Billy Beane uses to keep OAK competitive year after year is more like this model than what was shown in the movie and regurgitated ad nauseum on sites like Reddit.

Cubs got a catcher from KCA in exchange so we’ll see how that goes.  The catcher position is the toughest position in baseball to play so it’s probably good to have a couple extra around for a playoff push.  That is all for now.   Until then ….

Who are these new guys? Part 3

Today the Cubs play White Sox in a doesn’t matter pre season game so there should be new guys on each side.  This post will be another table dump showing each player’s trajectory through A+, AA, and AAA.   Let’s start with starting pitcher for CHA.

Note: It appears Cubs are using a real starting lineup and so far, 3rd inning, there are very few CHN new guys that we haven’t already covered.  Current team affiliation in table title.

Manny Banuelos CHA

Year Rank WAA Name_TeamID Pos WinPct League Age
2018 +196+ 1.57 Manny_Banuelos_LAN PITCH 0.568 aaa 27
2017 XXXXX -1.43 Manny_Banuelos_ANA PITCH 0.432 aaa 26
2016 XXXXX -0.48 Manny_Banuelos_ATL PITCH 0.429 aaa 25
2016 XXXXX -0.71 Manny_Banuelos_ATL PITCH 0.325 aa 25
2015 XXXXX -0.69 Manny_Banuelos_ATL PITCH XXX mlb
2015 +037+ 3.49 Manny_Banuelos_ATL PITCH 0.685 aaa 24
2014 XXXXX 0.29 Manny_Banuelos_NYA PITCH 0.587 aaa 23
2014 XXXXX -0.92 Manny_Banuelos_NYA PITCH 0.416 aa 23
2014 XXXXX 0.38 Manny_Banuelos_NYA PITCH 0.635 aplus 23
2012 XXXXX -0.13 Manny_Banuelos_NYA PITCH 0.476 aaa 21
2011 XXXXX 0.42 Manny_Banuelos_NYA PITCH 0.555 aaa 20
2011 XXXXX 1.28 Manny_Banuelos_NYA PITCH 0.560 aa 20
2010 XXXXX 0.19 Manny_Banuelos_NYA PITCH 0.556 aa 19
2010 +147+ 1.97 Manny_Banuelos_NYA PITCH 0.700 aplus 19

Manny had a decent season for the Dodgers’ AAA affiliate and now plays for CHA.  At age 27 he probably should be in MLB this season if he can make it.  Gave up 2 earned runs in 1.1 IP so that’s not a good sign.  Don’t know what his current preseason stats are though.

Luis Lugo CHN

Year Rank WAA Name_TeamID Pos WinPct League Age
2018 XXXXX -0.10 Luis_Lugo_KCA PITCH 0.481 aa 24
2017 XXXXX -1.30 Luis_Lugo_CLE PITCH 0.456 aa 23
2016 XXXXX -0.29 Luis_Lugo_CLE PITCH 0.490 aplus 22
2015 XXXXX -1.34 Luis_Lugo_CLE PITCH 0.452 aplus 21

Luis Lugo is a minor league starter on the Cubs’ AA affiliate and he hasn’t pitched well.  Still very young.  Pitchers can be very finicky from season to season.

Yonder Alonso CHA

Year Rank WAA Name_TeamID Pos WinPct League Age
2018 +165+ 1.97 Yonder_Alonso_CLE 1B XXX mlb
2017 XXXXX 1.55 Yonder_Alonso_TOT 1B XXX mlb
2017 XXXXX 1.24 Yonder_Alonso_OAK 1B XXX mlb
2017 XXXXX 0.23 Yonder_Alonso_SEA 1B XXX mlb
2016 -159- -1.81 Yonder_Alonso_OAK 1B XXX mlb
2015 XXXXX -0.92 Yonder_Alonso_SDN 1B XXX mlb
2015 XXXXX 0.15 Yonder_Alonso_SDN BAT NA aaa 28
2015 XXXXX -0.08 Yonder_Alonso_SDN BAT NA aplus 28
2014 XXXXX -0.90 Yonder_Alonso_SDN 1B XXX mlb
2014 XXXXX -0.32 Yonder_Alonso_SDN BAT NA aaa 27
2013 XXXXX -0.17 Yonder_Alonso_SDN 1B XXX mlb
2013 XXXXX -0.02 Yonder_Alonso_SDN BAT NA aaa 26
2012 -051- -3.09 Yonder_Alonso_SDN 1B XXX mlb
2011 XXXXX 0.32 Yonder_Alonso_CIN LF XXX mlb
2011 XXXXX -0.04 Yonder_Alonso_CIN BAT 0.498 aaa 24
2010 XXXXX -0.15 Yonder_Alonso_CIN X XXX mlb
2010 XXXXX -0.46 Yonder_Alonso_CIN BAT 0.480 aaa 23
2010 XXXXX 0.38 Yonder_Alonso_CIN BAT 0.560 aa 23
2009 XXXXX -0.15 Yonder_Alonso_CIN BAT 0.476 aa 22
2009 XXXXX 1.09 Yonder_Alonso_CIN BAT 0.604 aplus 22
2008 XXXXX -0.32 Yonder_Alonso_CIN BAT NA aplus 21

Yonder Alonso is a new guy for CHA but not a new guy in MLB.  He had a decent season ranked in top 200 last season and has moved around a lot from team to team during his career.

Eloy Jimenez CHA

Year Rank WAA Name_TeamID Pos WinPct League Age
2018 XXXXX 0.53 Eloy_Jimenez_CHA BAT 0.557 aaa 21
2018 +057+ 2.67 Eloy_Jimenez_CHA BAT 0.725 aa 21
2017 XXXXX 0.17 Eloy_Jimenez_CHA BAT 0.545 aa 20
2017 +120+ 1.74 Eloy_Jimenez_CHN BAT 0.692 aplus 20
2017 +120+ 1.95 Eloy_Jimenez_CHA BAT 0.807 aplus 20

He’s the guy Cubs gave up for Quintana in order to shore up a weak starting rotation to make another World Series run in 2017.  The above numbers show how dominant he has been in minors.  That does not necessarily guarantee dominance in MLB.  Sox could call him up this season if they want to make a run for a playoff spot.

Zack Collins CHA

Year Rank WAA Name_TeamID Pos WinPct League Age
2018 XXXXX 0.38 Zack_Collins_CHA BAT 0.514 aa 23
2017 XXXXX 0.19 Zack_Collins_CHA BAT 0.581 aa 22
2017 +178+ 1.60 Zack_Collins_CHA BAT 0.572 aplus 22
2016 XXXXX 0.80 Zack_Collins_CHA BAT 0.600 aplus 21

Slightly above average minor league pitcher.  At age 23 he’s very young and could help the Sox next season or maybe even late this season.

Yolmer Sanchez CHA

Year Rank WAA Name_TeamID Pos WinPct League Age
2017 XXXXX -0.80 Yolmer_Sanchez_CHA 2B-3B XXX mlb

Not sure where Yolmer came from.  He only has one MLB record for 2017 missing 2018 and no minor league records.  Played a full season in 2017 slightly below average.

Tony Barnette CHN

Year Rank WAA Name_TeamID Pos WinPct League Age
2018 XXXXX 1.11 Tony_Barnette_TEX PITCH XXX mlb
2018 XXXXX 0.38 Tony_Barnette_TEX PITCH NA aa 34
2017 -196- -1.51 Tony_Barnette_TEX PITCH XXX mlb
2017 XXXXX 0.32 Tony_Barnette_TEX PITCH NA aaa 33
2016 +103+ 2.94 Tony_Barnette_TEX PITCH XXX mlb
2009 -004- -6.11 Tony_Barnette_ARI PITCH 0.333 aaa 25
2008 XXXXX 1.99 Tony_Barnette_ARI PITCH 0.558 aa 24

Looks like there’s a 6 year missing gap between 2009, when he totally tanked for the Arizona Diamondbacks AAA affiliate, and 2016.  According to baseball-reference he played in Japan during those seasons.  He pitched well last season but had a rough 2017.  We’ll see how this acquisition turns out this season because past results don’t affect future results.

Junichi Tazawa CHN

Year Rank WAA Name_TeamID Pos WinPct League Age
2018 -140- -1.91 Junichi_Tazawa_TOT PITCH XXX mlb
2018 -140- -2.25 Junichi_Tazawa_MIA PITCH XXX mlb
2018 -140- 0.36 Junichi_Tazawa_ANA PITCH XXX mlb
2018 XXXXX -0.92 Junichi_Tazawa_DET PITCH NA aaa 32
2017 XXXXX -0.02 Junichi_Tazawa_MIA PR XXX mlb
2017 -159- -1.74 Junichi_Tazawa_MIA PITCH XXX mlb
2016 XXXXX 0.04 Junichi_Tazawa_BOS PITCH XXX mlb
2015 XXXXX -0.25 Junichi_Tazawa_BOS PITCH XXX mlb
2014 XXXXX 1.24 Junichi_Tazawa_BOS PITCH XXX mlb
2013 XXXXX 1.11 Junichi_Tazawa_BOS PITCH XXX mlb
2012 +108+ 2.67 Junichi_Tazawa_BOS PITCH XXX mlb
2012 XXXXX 1.74 Junichi_Tazawa_BOS PITCH 0.685 aaa 26
2011 XXXXX -0.15 Junichi_Tazawa_BOS PITCH XXX mlb
2011 XXXXX 0.71 Junichi_Tazawa_BOS PITCH 0.723 aaa 25
2011 XXXXX -0.25 Junichi_Tazawa_BOS PITCH 0.451 aa 25
2011 XXXXX -0.80 Junichi_Tazawa_BOS PITCH 0.313 aplus 25
2009 -153- -1.85 Junichi_Tazawa_BOS PITCH XXX mlb
2009 XXXXX 0.48 Junichi_Tazawa_BOS PITCH 0.691 aaa 23
2009 XXXXX 3.23 Junichi_Tazawa_BOS PITCH 0.648 aa 23

He pitched well for BOS between 2012 and 2014 which includes their 2013 WS run.  2017 and 2018 weren’t very good however.  Hopefully the Cubs can get one last good year out of him.

Kelvin Herrera CHA

Year Rank WAA Name_TeamID Pos WinPct League Age
2018 +194+ 1.76 Kelvin_Herrera_TOT PITCH XXX mlb
2018 +194+ 1.89 Kelvin_Herrera_KCA PITCH XXX mlb
2018 +194+ -0.08 Kelvin_Herrera_WAS PITCH XXX mlb
2017 XXXXX 0.17 Kelvin_Herrera_KCA PITCH XXX mlb
2016 +139+ 2.42 Kelvin_Herrera_KCA PITCH XXX mlb
2015 +158+ 1.99 Kelvin_Herrera_KCA PITCH XXX mlb
2014 +056+ 3.80 Kelvin_Herrera_KCA PITCH XXX mlb
2013 XXXXX 0.04 Kelvin_Herrera_KCA PITCH XXX mlb
2013 XXXXX 1.13 Kelvin_Herrera_KCA PITCH 0.818 aaa 23
2012 +075+ 3.23 Kelvin_Herrera_KCA PITCH XXX mlb
2011 XXXXX 1.01 Kelvin_Herrera_KCA PITCH 0.767 aaa 21
2011 +117+ 2.10 Kelvin_Herrera_KCA PITCH 0.762 aa 21
2011 XXXXX 1.28 Kelvin_Herrera_KCA PITCH 0.892 aplus 21

Not sure how CHA acquired Kelvin Herrera but the above shows a pretty decent career as a reliever.  Totally dominated minor leagues looking at Win%

That is all for now.  Will do another one of these in the future picking some game at random.  This is rather labor intensive copy/pasting these tables.  A searchable web site is in the works.  A post about Arenado, Harper, and Bryant coming next.  Who is better?  Until then ….