The closest any hitter has come to hitting .400 in the past 50 years came in 1994, when Tony Gwynn batted .394 before the strike ended the season. Two of the three highest OPS seasons in the past 50 also came in 1994, when Jeff Bagwell sported a .368/.451/.750 line while Frank Thomas had a .353/.487/.729 line of his own. Matt Williams' 43 homers in 115 games put him on pace for 60.5 homers in a full season, just shy of Roger Maris' then record. On the pitching side, Greg Maddux's 1.56 ERA in 1994 is the second-lowest of the past 50 seasons.
The reason we saw so many historic performances in 1994 shouldn't come as much of a surprise to anyone who plays Fantasy baseball: Sometimes wacky things can happen in a small sample size. We talk a lot about regression to the mean and small sample sizes, and this is exactly why — the more games you have, the closer a player's production will skew toward their "true" talent level.
That's why we're skeptical of guys like Frankie Montas, Sean Manaea and Kyle Tucker, and why we're not just writing off Corey Kluber after his rough start to the 2019 season was met by a season-ending injury. It's not that what we saw from those players in 2019 can't be real; we just didn't see enough from them to say for sure.
Well, no matter what proposal ends up going through to play in 2020, we're going to have a bunch of small sample sizes to deal with across the league. Whether it is 115-ish games like the players have proposed or between 50 and 76 as MLB and the teams prefer, we're going to be facing a strange landscape in 2020. Scott White has gone over what the impact of a 50-game season might be for the game as a whole and we did a mock draft with a 50-game season in mind last week, but I want to dive into what a shortened season might actually mean for player performances.
One way to do that is simply look at leaderboards from the roughly 50-game point in 2019, which leads us to all kinds of interesting outcomes, such as Cody Bellinger hitting .382/.469/.770 — a positively Bagwell-ian line. Or, on the other end of the spectrum, Jose Ramirez hitting .204/.308/.301 nearly through the end of May. On the pitching side, we had Yu Darvish sporting a 5.40 ERA with 6.22 BB/9, while Caleb Smith ranked third in the league with a 2.38 ERA along with a 12.06 K/9.
One-third of a season is going to lead to much stranger outcomes than a full season, and you have to start preparing yourself for those possibilities. We really might see someone hit .400 in 2020; we also might see a first-round pick flirt with the Mendoza line. And both outcomes are possible from the same player in some cases.
However, we can do more to show what a player's potential range of outcomes is by getting a bit more granular. For a number of players, I took their best, worst, and median 50-game stretch in strikeout rate, home runs, and BABIP and put them together to show what the range of possible outcomes could be for a 50-game season.
First, let's look at the range of possible outcomes for Bellinger based on his best (green) and worst (red) seasons, as well as his career averages (white) (pro-rated to 50 games):
K% | HR | BABIP | BA |
16.4% | 15 | 0.313 | 0.312 |
22.0% | 15 | 0.313 | 0.290 |
26.6% | 15 | 0.313 | 0.272 |
16.4% | 12 | 0.313 | 0.300 |
22.0% | 12 | 0.313 | 0.278 |
26.6% | 12 | 0.313 | 0.260 |
16.4% | 8 | 0.313 | 0.284 |
22.0% | 8 | 0.313 | 0.263 |
26.6% | 8 | 0.313 | 0.245 |
16.4% | 15 | 0.305 | 0.307 |
22.0% | 15 | 0.305 | 0.285 |
26.6% | 15 | 0.305 | 0.268 |
16.4% | 12 | 0.305 | 0.295 |
22.0% | 12 | 0.305 | 0.273 |
26.6% | 12 | 0.305 | 0.256 |
16.4% | 8 | 0.305 | 0.278 |
22.0% | 8 | 0.305 | 0.257 |
26.6% | 8 | 0.305 | 0.239 |
16.4% | 15 | 0.299 | 0.302 |
22.0% | 15 | 0.299 | 0.281 |
26.6% | 15 | 0.299 | 0.264 |
16.4% | 12 | 0.299 | 0.290 |
22.0% | 12 | 0.299 | 0.269 |
26.6% | 12 | 0.299 | 0.252 |
16.4% | 8 | 0.299 | 0.274 |
22.0% | 8 | 0.299 | 0.253 |
26.6% | 8 | 0.299 | 0.236 |
It's a pretty wide range of outcomes, but nothing outlandish — an average a bit higher than last year's breakout, with a floor not far from what he did in the second half of 2018. That's a pretty reasonable range of possibilities we might expect given a full season's sample.
Here's what it looks like when we're dealing with small samples, as I took his best, worst, and median 50-game stretches in K%, HR, and BABIP from 2019:
K% | HR | BABIP | BA |
12.7% | 19 | 0.388 | 0.399 |
17.4% | 19 | 0.388 | 0.376 |
20.8% | 19 | 0.388 | 0.359 |
12.7% | 15 | 0.388 | 0.384 |
17.4% | 15 | 0.388 | 0.361 |
20.8% | 15 | 0.388 | 0.345 |
12.7% | 10 | 0.388 | 0.366 |
17.4% | 10 | 0.388 | 0.344 |
20.8% | 10 | 0.388 | 0.327 |
12.7% | 19 | 0.302 | 0.335 |
17.4% | 19 | 0.302 | 0.317 |
20.8% | 19 | 0.302 | 0.304 |
12.7% | 15 | 0.302 | 0.318 |
17.4% | 15 | 0.302 | 0.301 |
20.8% | 15 | 0.302 | 0.288 |
12.7% | 10 | 0.302 | 0.298 |
17.4% | 10 | 0.302 | 0.280 |
20.8% | 10 | 0.302 | 0.268 |
12.7% | 19 | 0.224 | 0.277 |
17.4% | 19 | 0.224 | 0.264 |
20.8% | 19 | 0.224 | 0.254 |
12.7% | 15 | 0.224 | 0.259 |
17.4% | 15 | 0.224 | 0.246 |
20.8% | 15 | 0.224 | 0.236 |
12.7% | 10 | 0.224 | 0.236 |
17.4% | 10 | 0.224 | 0.223 |
20.8% | 10 | 0.224 | 0.213 |
In the best-case scenario, Bellinger could challenge for that hallowed .400 — it would require everything going right all at once, which is unlikely, but not impossible. Of course, on the other end of the spectrum, Bellinger could very well flirt with the Mendoza line — and that's if he keeps his strikeout rate below career norms.
Which is to say, Bellinger might have a lower floor than you think. It's unlikely everything goes wrong all at once, but this is one way to illustrate what kind of range of outcomes might be possible. Of course, everyone's range of outcomes is different. Here's the same exercise but for Christian Yelich:
K% | HR | BABIP | BA |
17.1% | 21 | 0.411 | 0.400 |
20.4% | 21 | 0.411 | 0.383 |
25.1% | 21 | 0.411 | 0.359 |
17.1% | 16 | 0.411 | 0.383 |
20.4% | 16 | 0.411 | 0.366 |
25.1% | 16 | 0.411 | 0.342 |
17.1% | 12 | 0.411 | 0.369 |
20.4% | 12 | 0.411 | 0.352 |
25.1% | 12 | 0.411 | 0.328 |
17.1% | 21 | 0.354 | 0.361 |
20.4% | 21 | 0.354 | 0.347 |
25.1% | 21 | 0.354 | 0.326 |
17.1% | 16 | 0.354 | 0.343 |
20.4% | 16 | 0.354 | 0.328 |
25.1% | 16 | 0.354 | 0.307 |
17.1% | 12 | 0.354 | 0.328 |
20.4% | 12 | 0.354 | 0.313 |
25.1% | 12 | 0.354 | 0.292 |
17.1% | 21 | 0.278 | 0.310 |
20.4% | 21 | 0.278 | 0.298 |
25.1% | 21 | 0.278 | 0.282 |
17.1% | 16 | 0.278 | 0.289 |
20.4% | 16 | 0.278 | 0.278 |
25.1% | 16 | 0.278 | 0.261 |
17.1% | 12 | 0.278 | 0.272 |
20.4% | 12 | 0.278 | 0.261 |
25.1% | 12 | 0.278 | 0.244 |
Because Yelich mostly managed to avoid those really low stretches in BABIP, his range of outcomes doesn't look quite as wide as Bellinger's.
We can do something similar with pitching, taking their best and worst stretches from last year and coming up with a range of potential outcomes using FIP, which takes into account strikeouts, walks-plus-hit-by-pitch, and home runs allowed. We'll start with Max Scherzer, who unsurprisingly showcases the potential for a Maddux-esque historic partial season:
K | BB+HBP | HR | FIP |
110 | 12 | 4 | 1.38 |
101 | 11 | 4 | 1.59 |
90 | 11 | 4 | 1.90 |
110 | 18 | 4 | 1.63 |
101 | 18 | 4 | 1.89 |
90 | 18 | 4 | 2.20 |
110 | 22 | 4 | 1.80 |
101 | 22 | 4 | 2.06 |
90 | 22 | 4 | 2.38 |
110 | 12 | 5 | 1.56 |
101 | 11 | 5 | 1.78 |
90 | 11 | 5 | 2.09 |
110 | 18 | 5 | 1.82 |
101 | 18 | 5 | 2.08 |
90 | 18 | 5 | 2.39 |
110 | 22 | 5 | 1.99 |
101 | 22 | 5 | 2.25 |
90 | 22 | 5 | 2.56 |
110 | 12 | 10 | 2.49 |
101 | 11 | 10 | 2.70 |
90 | 11 | 10 | 3.02 |
110 | 18 | 10 | 2.75 |
101 | 18 | 10 | 3.00 |
90 | 18 | 10 | 3.32 |
110 | 22 | 10 | 2.92 |
101 | 22 | 10 | 3.18 |
90 | 22 | 10 | 3.49 |
However, what might make Scherzer stand out even more — and what might make him even more of a target for 2020 drafts — is how narrow the range of outcomes is. His best-case scenario is a 1.38 FIP while his average is 2.30, not far from his 2.45 overall mark from 2019. However, his worst case scenario is still good for a 3.49 FIP — that's with his worst 11-start stretch in terms of home runs, strikeouts, and walks-plus-hit-by-pitch.
Of course, things could go worse for him. After all, he dealt with a back injury in the second half, and as a soon-to-be 36-year-old, there's always the possibility that age catches up with Scherzer faster than expected. However, based on what we saw from him last season, even a small-sample size shouldn't lead to too much trouble for Scherzer.
To put that in context, here is the same thing based on Jacob deGrom's 2019:
K | BB+HBP | HR | FIP |
98 | 11 | 3 | 1.49 |
90 | 11 | 3 | 1.72 |
70 | 11 | 3 | 2.29 |
98 | 18 | 3 | 1.79 |
90 | 18 | 3 | 2.02 |
70 | 18 | 3 | 2.59 |
98 | 24 | 3 | 2.05 |
90 | 24 | 3 | 2.28 |
70 | 24 | 3 | 2.85 |
98 | 11 | 6 | 2.05 |
90 | 11 | 6 | 2.28 |
70 | 11 | 6 | 2.85 |
98 | 18 | 6 | 2.35 |
90 | 18 | 6 | 2.58 |
70 | 18 | 6 | 3.15 |
98 | 24 | 6 | 2.60 |
90 | 24 | 6 | 2.83 |
70 | 24 | 6 | 3.40 |
98 | 11 | 9 | 2.60 |
90 | 11 | 9 | 2.83 |
70 | 11 | 9 | 3.40 |
98 | 18 | 9 | 2.90 |
90 | 18 | 9 | 3.13 |
70 | 18 | 9 | 3.70 |
98 | 24 | 9 | 3.16 |
90 | 24 | 9 | 3.39 |
70 | 24 | 9 | 3.96 |
We see a similar upside from deGrom, but a slightly lower floor, because he just isn't the same kind of strikeout pitcher as Scherzer. Of course, when you're talking about a pitcher's worst-case scenario still making him an above-average pitcher, there really isn't much to be concerned about. It's not just the upside that makes the best players in Fantasy the best — it's also that you don't need to worry about them.
Matthew Boyd helps us illustrate that point quite well:
K | BB+HBP | HR | FIP |
99 | 11 | 7 | 2.20 |
84 | 11 | 7 | 2.63 |
70 | 11 | 7 | 3.03 |
99 | 17 | 7 | 2.46 |
84 | 17 | 7 | 2.89 |
70 | 17 | 7 | 3.29 |
99 | 28 | 7 | 2.93 |
84 | 28 | 7 | 3.36 |
70 | 28 | 7 | 3.76 |
99 | 11 | 16 | 3.88 |
84 | 11 | 16 | 4.30 |
70 | 11 | 16 | 4.70 |
99 | 17 | 16 | 4.13 |
84 | 17 | 16 | 4.56 |
70 | 17 | 16 | 4.96 |
99 | 28 | 16 | 4.60 |
84 | 28 | 16 | 5.03 |
70 | 28 | 16 | 5.43 |
99 | 11 | 20 | 4.62 |
84 | 11 | 20 | 5.05 |
70 | 11 | 20 | 5.45 |
99 | 17 | 20 | 4.88 |
84 | 17 | 20 | 5.30 |
70 | 17 | 20 | 5.70 |
99 | 28 | 20 | 5.35 |
84 | 28 | 20 | 5.78 |
70 | 28 | 20 | 6.18 |
The upside here is considerable, which is why he is one of my favorite breakout picks for 2020. Boyd altered his approach to be more slider heavy in 2019, and when he was at his best, it led to pretty incredible results. However, he was also way too homer prone, which led to some huge blow ups, and that shows up in his range of potential outcomes.
Boyd has ace potential for a full season or a partial season, if he can keep the ball in the yard. His range of possible outcomes when he limits home runs is well above average across the board. However, we can also see how if he repeats last year's homer issues, there's almost no path for him to be an above-average pitcher. And, on the low end of the range, Boyd might be one of the worst pitchers in baseball.
And that's why you can get him in the middle rounds. If he hits, he'll be a huge value; if he can't fix his issues, however, you're not going to have enough time to make up for the dent he'll make in your ERA.
Over the coming days and weeks, I will dive further into this concept to illustrate what players' ranges of outcomes might look like in both 50- and 76-game seasons.