League Result Breakdown: Successes & Failures

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With the dust finally settling, I ended the 2026 season with $3K in profit over 12 leagues. Here are my league results and some of overarching thoughts on the season and some leagues.

Pitching ratios were a mess.

In both league sizes, the final pitching ratio results were consistently well below average. When I could get middling ratio values, I performed decently. The major factor bringing down my ratios was not hitting on any of the season’s top starters. Here are the top six pitchers from our player rater:

• Jacob Misiorowski
• Cam Schlittler
• Yoshinobu Yamamoto
• Chris Sale
• Drew Rasmussen
• Dylan Cease

I did not draft one of them across 12 leagues. By random chance, I should have drafted some of them. I missed out in so many ways when drafting pitchers. For example, the 15-team league that finished 4th with 73 of 75 Hitting points drafted the following pitchers:

• Bryan Woo
• Cole Ragans
• Daniel Palencia
• Ryan Walker
• Matthew Boyd
• Mike Burrows
• Cody Ponce
• Braxton Ashcraft
• Merrill Kelly
• Kyle Harrison
• Liam Hendriks
• Emerson Hancock
• Landen Roupp
• Justin Steele

That’s too big of a hole to come out of.

As can be seen, I was able to fix some errors and volume enough wins, strikeouts, and saves. The ratios were just trash. It’s a problem I need to find a solution for.

Devaluing Runs and RBI

Last season I struggled with hitting, especially with home runs and batting average/on-base percentage. I could volume my way to decent finishes in runs and RBI. This had been happening for years, and I changed my draft valuations to address it. I de-emphasized runs and RBI and put more weight on home runs and rates. The results were amazing. Some thoughts on this approach.

I was drafting with a completely different ranking than everyone else. After the first three rounds, it was rare for my top player to be close to near the top of the ADP. I found that my rankings were pushing up good players on bad teams relative to the field. These players were devalued because they didn’t have the same volume in runs and RBI. Another group of players I added were projected to hit at the bottom of their team’s lineup (Michael Harris II and Andy Pages). Some of the players I had on multiple teams were:

• Alec Burleson
• Hunter Goodman
• Michael Harris II
• CJ Abrams
• Otto Lopez
• Andy Pages

A couple of issues I found with this approach.

1. In the 12-team leagues, I completely missed on home runs in a couple of leagues (though one was a league where I drafted Aaron Judge and a full season from him might have changed that), so I might emphasize home runs more for 12-teamers next year.
2. The run-RBI mix was a little out of whack, with me getting 2.5 more RBI points. This difference was as simple as hitters who hit for average and power get a ton of RBI. I might add a couple more leadoff hitters in the draft. Maybe.

What I’m thinking is that I need to use this same approach with struggling pitching ratios. Overweight them since I’m able to stream myself to volume in the counting stats.

It’s dumb to draft several hurt players.

I decided to use my two industry leagues (LABR and Tout Wars) to overemphasize a strategy and see how it works. Both leagues have unlimited IL slots, so I leaned into injuries and injury risk this year. My two 9th place teams in the tables above are those two industry leagues. Oopsy.

Here are the reasons it failed.

1. In LABR, we only had $100 FAAB with $1 minimum bids. I drafted five players who I knew would start the season hurt, so I needed 5% of my budget to replace those players. LABR is a 12-team league, so the pool of rostered players was shallow to begin with. Many of the guys I drafted to stash on the IL weren’t any better than the healthy players I could have added.
2. Since I was using so much FAAB to handle all the empty slots, I could not spend as much as I needed on talented players when they were available.
3. In Tout Wars, the approach didn’t work either because of the league’s depth (three more teams). No talented players were on the wire. It would have been nice to start with a stronger floor.
4. Most importantly, my healthy players got hurt, and then I needed to spend even more FAAB to scavenge the waiver wire.

In the end, I wouldn’t use this strategy at all. Just draft the best team possible to win week 1. I might add a player I know for sure will be back in less than a month and not have him as one of my core 15 players.

In shallow leagues, mass streaming works.

On May 31st, here are the standings in my NFBC Online Championship.

I knew I was in trouble. The week before, I had spent $253 on a player, leaving me with an average of $7 per week. Then I began grinding away. In some weeks, I would add eight $1 players, going a buck over budget, but I would replenish the budget the next week by making fewer moves. I slowly kept climbing.

I was briefly able to tie the second-place team and get into the money.

In the end, the other managers pulled ahead to 86 points, and I lost by 4.5 points. It helped that Tatis got going, but in these shallow leagues, winning the week is huge.

My big takeaway from this Hail Mary is that in instances where up to 10 moves can be made each week, aggressively stream platoon bats and tw0-start pitchers to win the week with $1 adds. If you miss out on those adds one week, oh well. I will say that once starting this approach, a manager has to keep it going because most of the adds will need to be dropped for a fresh group of streamers.

In a 26-week season, the cost of those 10 additions adds up to just $260 of a $1000 budget. The remaining $740 can be used to add difference-makers when they pop up or get dropped by other teams.

And here is the $253 player (and his stats) that I added to “help” my team: