Stats for The Arm — Pitcher Evaluation
The stats DMP uses to evaluate pitchers, and why traditional stats like ERA and pitcher wins mislead
You should read this if:
You bet MLB props and want to understand the mental models that drive outcomes.
The Core Insight
"FIP isolates what pitchers control (strikeouts, walks, home runs). ERA is contaminated by defense, luck, and scorer judgment. The difference between them is one of the most exploitable signals in sports betting."
The MLB Mental Model
FIP (use) vs ERA (misleading)
FIP = (13*HR + 3*BB - 2*K) / IP + constant
Predicts: True pitching talent. Excellent: 3.20, Great: 3.50, Average: 4.20, Awful: 5.00
K% (use) vs K/9 (less useful)
K per batter faced, not per inning. Stabilizes in ~70 BF.
Predicts: Strikeout probability. Excellent: 27%, Great: 24%, Average: 20%, Awful: 13%
xFIP (normalizes HR luck)
Replaces actual HR/FB with league-average rate
Predicts: Whether a pitcher's HR rate is sustainable or will regress
Never use: W-L or Saves
Pitcher wins measure run support. Saves measure role, not quality.
Predicts: Nothing about pitching skill — these are team and role stats
The Pitching Stats That Matter
Every pitcher stat below is grounded in the book's framework: strip out defense and luck, isolate true talent, and look for the gap between process (stuff, K%, command) and results (ERA, wins). Gaps are where props get mispriced.
FIP (Fielding Independent Pitching)
ERA estimatorA run-average-scale number built only from the things a pitcher fully controls: strikeouts, walks, hit-by-pitches, and home runs. Scaled to look like ERA so you can compare them directly.
Why it matters
ERA is contaminated by defense, shift positioning, outfielder routes, official-scorer judgment, and pure BABIP luck. FIP removes all of it. The book calls FIP "to ERA what true shooting is to field goal percentage."
How to use it
Use FIP — never ERA alone — as the primary pitcher-skill input for ER and K projections. When FIP is much lower than ERA, that ER prop is mispriced on the over side; when FIP is much higher than ERA, the pitcher is living on defense and is about to regress.
| Tier | Value | What it means |
|---|---|---|
| Elite | ≤ 3.20 | Ace-level true talent — ER unders live |
| Great | 3.50 | Mid-rotation plus — solid pitcher-first matchups |
| Average | 4.20 | League-average SP — defer to matchup/park |
| Poor | ≥ 5.00 | Back-end / replacement — ER overs, fade K overs |
"FIP is to ERA what true shooting is to field goal percentage." — appendix-charts.md / BIG-IDEAS.md
xFIP (Expected FIP)
Regression-adjusted FIPFIP, but we replace the pitcher's actual HR/FB rate with the league-average ~9.5%. Because HR/FB rate is the most volatile important pitching stat, this tells you what FIP "should" look like once HR luck normalizes.
Why it matters
A pitcher riding a 5% HR/FB rate is about to give up more dingers; one stuck at 15% is about to give up fewer. xFIP catches both cases before the market does.
How to use it
Whenever HR/FB is below 7% or above 11%, lean on xFIP over FIP for ER projections. Flyball pitchers benefit most from this regression adjustment.
| Tier | Value | What it means |
|---|---|---|
| Elite | ≤ 3.20 | HR-normalized true talent is elite |
| Great | 3.50 | Strong underlying skill |
| Average | 4.20 | League-average once HR/FB regresses |
| Poor | ≥ 5.00 | Bad even with league-average HR luck |
SIERA (Skill-Interactive ERA)
ERA estimatorA FanGraphs ERA estimator that adds batted-ball profile (GB% vs FB%) on top of FIP's K/BB/HR framework. It rewards pitchers whose batted-ball suppression is a skill, not luck.
Why it matters
For extreme groundball pitchers, FIP understates their ER-suppression ability. SIERA captures the fact that grounders carry lower BABIP damage and feed double plays.
How to use it
Use SIERA (over FIP) when projecting ER props for high-GB arms. A SIERA well below FIP is the sinker-baller's true-talent number.
| Tier | Value | What it means |
|---|---|---|
| Elite | ≤ 3.20 | Ace including batted-ball skill |
| Great | 3.50 | Strong SP — GB skill counts |
| Average | 4.20 | Mid-rotation |
| Poor | ≥ 5.00 | Poor even accounting for GB tilt |
K% (Strikeout Rate)
Rate statStrikeouts divided by total batters faced. This is the direct driver of a pitcher's strikeout prop — project expected BF × K%, adjusted for the opposing lineup's K vulnerability and the park's K factor.
Why it matters
K% stabilizes in ~60–70 batters faced — the fastest of any pitcher skill. That means K props are reliable from early April when nothing else is trustworthy yet. The book calls strikeout props "the cleanest bet in baseball."
How to use it
Every pitcher K prop starts here. High K% vs high-K opposing lineup + large-zone ump + dry-air park = stack the K over. CSW% leads K% — if CSW% is up but K% hasn't caught up, buy K overs before the market adjusts.
| Tier | Value | What it means |
|---|---|---|
| Elite | 27%+ | K artist — target K overs aggressively |
| Great | 24% | Above-average whiff stuff |
| Average | 20% | Neutral — lean on matchup |
| Poor | ≤ 15% | Contact pitcher — fade K overs |
BB% (Walk Rate)
Rate stat / CommandWalks divided by total batters faced. The book's second-most-stable pitcher skill (~170 BF / 7 starts to stabilize).
Why it matters
Walks inflate pitch counts, which caps IP, which caps K ceilings. High BB% also drives WHIP and ER directly via baserunners. A pitcher with great Stuff+ but a Location+ under 100 walks too many to ever be an ace.
How to use it
High BB% pitcher → IP under, walks-allowed over, potentially ER over. Combine with Zone% — a low-Zone% nibbler is the archetype.
| Tier | Value | What it means |
|---|---|---|
| Elite | ≤ 4.5% | Strike-thrower — go deep in games |
| Great | 5.5% | Strong command |
| Average | 7.7% | League-average |
| Poor | ≥ 9% | Walks-over target; IP-under target |
CSW% (Called Strikes + Whiffs)
Leading indicatorThe share of a pitcher's total pitches that generate either a called strike or a swinging strike. Think of it as dominance per pitch.
Why it matters
CSW% is more responsive than K% — it stabilizes essentially within a single start. A pitcher whose CSW% jumped 3 points in his last outing is signaling a K% rise before the K counts catch up.
How to use it
Check CSW% trend vs. the K% trend. Rising CSW% + flat K% = K over buy before the line moves. Falling CSW% from a name-brand ace = K under fade before the market adjusts.
| Tier | Value | What it means |
|---|---|---|
| Elite | 32%+ | Nasty stuff — K overs live |
| Great | 30% | Above-average dominance |
| Average | 28% | League-average |
| Poor | < 25% | Hittable — fade K overs |
SwStr% (Swinging Strike Rate)
Leading indicatorSwinging strikes divided by total pitches. The purest bat-missing signal.
Why it matters
SwStr% is the leading indicator for K%. It stabilizes faster and flags stuff changes (new pitch, velo bump) before the K counts arrive.
How to use it
Use in tandem with CSW% — if both are up, K over conviction rises. Specifically useful when pitch-mix changes mid-season.
| Tier | Value | What it means |
|---|---|---|
| Elite | 14%+ | Top-tier whiff stuff |
| Great | 12% | Above-average swing-and-miss |
| Average | 10 – 11% | League-average |
| Poor | < 9% | Contact pitcher — K props unsafe |
Whiff%
Per-pitch qualitySwings-and-misses divided by total swings. Unlike SwStr%, which uses all pitches as the denominator, Whiff% isolates "when they swung, how often did they miss."
Why it matters
Lets you evaluate specific pitches in the mix. A slider with 40% whiff vs. a lineup that chases sliders is a K prop green light.
How to use it
Pair with pitch mix and opposing lineup's splits by pitch type. Elite whiff on the out-pitch + chase-prone lineup = K over stack.
| Tier | Value | What it means |
|---|---|---|
| Elite | 30%+ | Dominant swing-and-miss arsenal |
| Great | 27% | Plus stuff |
| Average | 24% | League-average |
| Poor | < 20% | Contact-friendly arsenal |
Stuff+
Statcast-style modelFanGraphs/Eno Sarris model that grades the raw quality of a pitcher's pitches (velocity, movement, spin axis) versus the league, scaled to 100 = average.
Why it matters
Isolates "how good is the pitch" from "where did they throw it" and "what was the result." A pitcher with 120 Stuff+ and a bad ERA is a future-breakout candidate the market hasn't priced.
How to use it
Gap signal: high Stuff+ + high ERA → K over, ER under reversion incoming. Low Stuff+ + low ERA → fade, his results aren't supported.
| Tier | Value | What it means |
|---|---|---|
| Elite | 115+ | Top-10% pitch quality |
| Great | 108 | Plus arsenal |
| Average | 100 | League-average stuff |
| Poor | ≤ 90 | Below-average — command/deception required |
Location+
Statcast-style modelModels the quality of where a pitcher locates, independent of what pitch he throws. 100 = league-average command.
Why it matters
Separates command from stuff. Elite Stuff+ with sub-95 Location+ is the recipe for walks and missed-spot homers.
How to use it
Low Location+ → walks-allowed over and ER over even with elite Stuff+. High Location+ on a finesse arm is how they survive despite weak velo.
| Tier | Value | What it means |
|---|---|---|
| Elite | 105+ | Pinpoint command |
| Great | 102 | Above-average location |
| Average | 100 | League-average |
| Poor | < 97 | Misses spots — walks/HR prone |
HR/FB (Home Run per Fly Ball)
Regression signalOf the flyballs a pitcher allows, what share become home runs? League average is ~9.5%.
Why it matters
The book calls this "the most volatile important stat in baseball." It bounces year-to-year on park, weather, and batted-ball luck — which means extreme values are the market's most reliable mispricing.
How to use it
HR/FB above 12% or below 7% → use xFIP, not FIP, for ER projections. Flyball pitchers at 14%+ are due for ER-unders; at 5% they're due for ER-overs.
| Tier | Value | What it means |
|---|---|---|
| Elite | ≤ 5% | Extremely lucky — regression coming up |
| Great | 7% | Below-avg HR suppression skill or luck |
| Average | 9.5% | League-average |
| Poor | ≥ 13% | Unlucky or pitches up — regression down coming |
LOB% (Left On Base)
Regression signalShare of baserunners the pitcher strands. The book frames it as "the ERA of run sequencing" — over a full season it regresses hard to ~72%.
Why it matters
Sequencing luck inflates or deflates ERA without telling you anything about true talent. A pitcher stranding 85% of runners has an ERA about to rise; 60% means an ERA about to fall.
How to use it
LOB% > 80% → ER over lean in upcoming starts. LOB% < 65% → ER under lean. The regression is pure math.
| Tier | Value | What it means |
|---|---|---|
| Elite | 80% | Lucky / high-leverage success — fade |
| Great | 75% | Above-average sequencing |
| Average | 72% | League-average — no signal |
| Poor | ≤ 65% | Unlucky sequencing — buy ER unders |
GB% / FB% (Batted-Ball Split)
Profile statWhat share of balls-in-play the pitcher turns into ground balls vs flyballs. League averages are ~44% GB and ~35% FB.
Why it matters
GB pitchers suppress HR and allow a few more singles (.240 BABIP on grounders); FB pitchers are boom-bust with more Ks and more HRs. Park amplifies the effect.
How to use it
FB pitcher at Yankee Stadium, Great American, Coors = stack HRs-allowed overs. GB pitcher at any park = fade HRs-allowed overs regardless of opposing lineup power.
| Tier | Value | What it means |
|---|---|---|
| Elite | GB 50%+ or FB 30%- | Extreme worm-killer — HR-suppressor |
| Great | GB 47% or FB 33% | Pronounced GB tilt |
| Average | GB 44% / FB 35% | League-average profile |
| Poor | FB 40%+ | Extreme flyball — HR-prone in wrong park |
Framework in Action: FIP vs ERA: Rick Porcello
Porcello posted 4.92 ERA in 2014, then won the Cy Young with 3.15 ERA in 2016. Same pitcher. The difference? His team defensive efficiency went from .672 to .707. FIP would have told you he was the same pitcher both years. ERA fooled everyone.
When to Apply This Framework
- ✓Every pitcher evaluation — always start with FIP, not ERA
- ✓FIP-ERA gap > 0.5 = strong regression signal for ER props
- ✓K% is reliable from early April — use it for K props immediately
When to Pass
- ⚠️Never use ERA alone to evaluate a pitcher for props
- ⚠️Never use pitcher W-L record for any analysis
- ⚠️Never trust early-season ERA without checking FIP
Key Takeaways
- ✓FIP is to ERA what true shooting is to field goal percentage — it strips out what the player does not control
- ✓K% and BB% are the most stable year-to-year pitcher skills
- ✓The FIP-ERA gap is one of the most reliably predictive signals in all of sports
How DMP Helps
DMP shows FIP alongside ERA everywhere, highlights the gap, and uses FIP as the primary pitcher skill input.