This will be the Cubs final team status for 2019. Below shows a month by month breakdown of team status during the 6 month 2019 season.
2019 CHN MONTHLY
These new team status records reduce W and L columns to a single real team WAA which is simply Wins – Losses. This makes it easier to visualize a team’s trend throughout a season. BAT, PITCH, and UR columns are the same as they always have been. BAT is derived from runs scored, PITCH derived from runs scored against, and UR derived from unearned runs. All three show runs above average. A negative value would be runs below average.
The only stat that matters in baseball is real team WAA. The Cubs went +4 in April which is very good. If a team goes +4 every month for 6 months they would be at +24 WAA or a record of 93-69 at the end of a season.
The Cubs gain another +2 in May, then flat line until August where they have another +4 month. In September they lose it all back to end the season at +6 (84-78), where they were at the end of May. This is interesting since they gained +30 in September while going almost -8 in UR for the same month. UR drop could have had a big impact in their late September collapse but not sure. UR is still an open issue for integration into Tier Combo simulation which is fodder for simulation posts later this off season.
Pythagorean Expectation is a formula that estimates wins from run differential. In 2019 the Cubs scored 814 runs giving up 717, almost a 100 run difference. If we plug those numbers into the PE formula we get:
PE = (Rs)^2 / (Rs^2 + Ra^2) = (814)^2 / ( 814^2 + 717^2 ) = 0.563
PE returns a Win%. Over 162 games PE estimates Cubs would win 91 games (91-71) which is a WAA = 20. The MLB commish only cares about real team WAA when determining who goes to the playoffs.
If we run these numbers for all 30 MLB teams we’ll see the Cubs are #1 in under performing this estimate. Below are the top 5 PE under performers for 2019.
If the Cubs hadn’t collapsed at the end of September they probably wouldn’t make this list. But they did. Under performing PE means a team won many blow out games and lost many very close games. Why that happened is fodder for arguments at the pub. It could be bad luck, bad managerial decisions, the reliever(s) you like to complain about, players choking under pressure, etc. Nobody can know for sure and the situation for each team will be different. There is no way to model the why for this difference mathematically.
The sum of player WAA calculated for their playing time on a team will add to that team’s total PEWAA number above exactly. Players who play for multiple teams will have separate WAAs for each team with their total being the sum of WAA for each team they play for.
This year Cubs, based upon all CHN WAAs, were over valued compared to their real win/loss record. The error in PE estimation is exactly the error in this data model’s valuation. No estimation is without error which is why it’s called an estimation. Note: The linked post to our PE error estimation is from 2014. This math may be reworked during off season.
So PE estimated the Cubs winning 91 games. Let’s see how they would have fared with the rest of the league had they actually won that many.
At 91 wins, Cubs would have still been bottom of the pack with the Cardinals. Even had they not collapsed in September they probably wouldn’t have gotten far in the playoffs. Washington won the World Series based upon the value of their current roster which was much higher than their seasonal real win loss record according to our Playoff Horse Race chart at the beginning of playoff season.
Teams can increase valuation over seasonal numbers through acquisitions and moving bad/negative valued players off roster. Now that we know Cubs’ players will be over valued compared to their real win/loss record, let’s look at the top Cubs for 2019.
Top Cubs 2019
Hendricks tops the list once again. Baez was #1 Cub last season. No Cubs in the top 50 but lots ranked in the top 200. An average team should field around 6 players ranked in the top 200 with 30 MLB franchises and around 3 in the top 100. Cubs have 3 in top 100 and around 10 in top 100 which is above average. Based on an 84-78 record the Cubs were slightly above average and based upon PEWAA from which player WAAs are derived, they are more above average.
The above shows a team with no real superstars but lots of above average players. This is not the kind of team that gets far into playoff season and would be big underdogs to top teams like HOU, NYA, LAN, and even WAS, the 2019 World Series champion.
Castellanos put up +2.46 in 2 months just playing for the Cubs. If he put up these numbers for 6 months he would have almost made top ten MLB players according to this data model. This model does not give mulligans however. He had very negative WAA at Detroit which dropped him out of ranking in top 200. Detroit ended the season with a record of 47-114 which translates into a WAA of -67. Players on DET share this negative value because losing that many games is a team effort, which Castellanos was part of for the first 4 months of the 2019 season.
Castellanos put up good game stats like OBP and Slugging Pct but he hit very poorly in RISP situations for DET which cost him value with this data model and literally lost games for the Tigers. It turned out to be a good acquisition for the Cubs in 2019 but can he put up those numbers for 6 months next season or the season after that? That’s fodder for our three year free agent ranking discussion.
Wick, Mills, and Ryan are new guys who will show up in the minor league report coming soon. There are many holes to fill next season and the Cubs are running out of money so they’ll need new guys from their minor league system to come up and perform like they did in 2015. More on this later during minor league look see. Until then ….