Calculate baseball FIP to evaluate pitcher performance independent of defense. Compare to ERA with HR, BB, HBP, K, and IP inputs.
Fielding Independent Pitching (FIP) is one of the most important metrics in modern baseball analytics. Unlike ERA, which is heavily influenced by the quality of the defense behind a pitcher, FIP isolates the outcomes that a pitcher truly controls: home runs, walks, hit batters, and strikeouts. This makes FIP a much better predictor of future pitcher performance than ERA.
FIP was developed by Tom Tango and works on the principle that pitchers have limited control over what happens once a ball is put in play. BABIP (Batting Average on Balls in Play) fluctuates around .300 for most pitchers regardless of talent, meaning that high or low ERAs are often driven by luck on batted balls rather than pitcher skill. FIP strips away this noise.
This calculator computes FIP from standard pitching statistics, compares it to the pitcher's actual ERA, and provides context through league-average benchmarks across MLB seasons. It also calculates xFIP (which normalizes home run rate) and SIERA for a more complete picture of pitcher quality.
FIP separates pitcher skill from luck and defense, giving you a clearer picture of a pitcher's true ability and likely future performance. Keep these notes focused on your operational context. Tie the context to the calculator’s intended domain. Use this clarification to avoid ambiguous interpretation. Align this note with review checkpoints. Apply this where interpretation shifts by use case.
FIP = ((13×HR) + (3×(BB+HBP)) - (2×K)) / IP + FIP constant. FIP constant ≈ 3.10-3.20 (varies by season, calculated so league FIP = league ERA). xFIP replaces HR with expected HR based on fly ball rate: xHR = FB × league HR/FB rate.
Result: FIP = 3.15
With 18 HR, 50 BB+HBP, 200 K in 190 IP: FIP = ((13×18) + (3×50) - (2×200)) / 190 + 3.17 = 3.15. This closely matches the ERA of 3.20, suggesting the pitcher's results are genuine.
FIP assigns weighted values to the three outcomes pitchers control most: home runs (13×), walks/HBP (3×), and strikeouts (-2×). These weights were derived empirically to best approximate the run value of each event. Home runs are weighted highest because each HR is essentially a guaranteed 1.4 runs. Walks contribute about 0.3 runs. Strikeouts remove batters without any chance of reaching base. The constant aligns FIP with the ERA scale for easy comparison.
xFIP normalizes the HR component by using (fly balls × league HR/FB rate) instead of actual HR. This is useful because HR/FB% for individual pitchers fluctuates significantly. SIERA (Skill-Interactive ERA) adds ground ball rate and interaction effects for a more sophisticated estimate. kwERA is the simplest variant, using only strikeout and walk rates: kwERA = 5.40 - 12×(K%-BB%).
FIP is invaluable for fantasy baseball drafts—targeting pitchers with FIP well below ERA identifies buy-low candidates likely to improve. Conversely, pitchers with ERA well below FIP are sell-high targets. In sports betting, FIP-based models consistently outperform ERA-based models for predicting game outcomes, particularly in the second half of the season when sample sizes are larger.
In MLB, a FIP below 3.20 is excellent (All-Star caliber), 3.20-3.80 is above average, 3.80-4.20 is league average, 4.20-4.80 is below average, and above 4.80 is poor.
FIP is a better predictor of future ERA than ERA itself. A pitcher with a 2.50 ERA but 3.80 FIP is likely benefiting from good defense or luck on balls in play and will likely regress.
A FIP well below ERA suggests the pitcher has been unlucky—their defense has let them down, or they've had bad luck on batted balls. Their ERA should improve toward their FIP over time.
The FIP constant is a season-specific number (typically 3.10-3.20) that scales FIP to match league-average ERA. It's recalculated each season using: lgERA - ((13×lgHR) + (3×(lgBB+lgHBP)) - (2×lgK)) / lgIP.
xFIP replaces actual home runs with expected home runs based on fly ball rate and league-average HR/FB%. This further stabilizes the metric by removing HR luck, since HR/FB% fluctuates year to year for most pitchers.
FIP works for relievers but with more variance due to smaller sample sizes. Over a full season (60+ IP for relievers), FIP is quite reliable. For shorter samples, xFIP may be more stable.