Advanced Hitting Stats for MLB Props - Player Props Education

wOBA (Weighted On Base Average)

wOBA measures overall offensive contribution by weighting each outcome (walk, single, double, triple, home run) by its actual run value. Unlike batting average, wOBA captures the difference between a single and a home run.

Prop Application: wOBA predicts total bases and runs created better than batting average. A hitter with a .380 wOBA is producing at an elite level regardless of his batting average.

Benchmarks: Below .300 is poor. .320 is average. .340 is above average. .370+ is elite.

ISO (Isolated Power)

ISO measures extra base power by subtracting batting average from slugging percentage. A hitter with a .250 batting average and .500 slugging has a .250 ISO, indicating significant power production beyond singles.

Prop Application: ISO is the best predictor for total bases and home run props. High ISO hitters consistently exceed total bases expectations even in lower hit games.

Benchmarks: Below .120 is poor. .140 is average. .180 is above average. .220+ is elite power.

Barrel Rate

Barrel rate measures the percentage of batted balls with the optimal combination of exit velocity (98+ mph) and launch angle (26 to 30 degrees). Barrels result in extra base hits or home runs at extremely high rates.

Prop Application: Barrel rate is the most predictive stat for home run and total bases props. Hitters who barrel the ball consistently produce high variance, high upside outcomes.

Benchmarks: Below 5% is poor. 7% is average. 10% is above average. 15%+ is elite.

Hard Hit Rate

Hard hit rate measures the percentage of batted balls with exit velocity above 95 mph. Hard contact converts to hits and extra bases at higher rates than soft contact.

Prop Application: Hard hit rate supports all offensive props. Hitters with high hard hit rates produce more hits, more total bases, and more RBIs because they hit the ball with authority.

Benchmarks: Below 30% is poor. 38% is average. 45% is above average. 50%+ is elite.

Chase Rate

Chase rate measures how often a hitter swings at pitches outside the strike zone. High chase rates lead to poor contact and more strikeouts.

Prop Application: Low chase rate hitters make better contact and reach base more often. For hits props and on base related props, low chase rate (good plate discipline) is valuable.

Benchmarks: Above 35% is poor. 28% is average. 22% is above average. Below 18% is elite.

Contact Rate

Contact rate measures how often a hitter makes contact when swinging. High contact hitters put the ball in play consistently, creating more hit opportunities.

Prop Application: Contact rate is the foundation of hits props. A hitter with 85%+ contact rate will consistently put balls in play, giving himself chances to accumulate hits.

Benchmarks: Below 70% is poor. 77% is average. 82% is above average. 88%+ is elite.

BABIP (Batting Average on Balls in Play)

BABIP measures batting average on balls hit into the field of play (excluding strikeouts, walks, and home runs). It fluctuates based on luck, speed, and batted ball quality.

Prop Application: BABIP identifies regression candidates. A hitter with a .220 BABIP is running unlucky and due for positive regression on hits props. A .370 BABIP is unsustainably high.

Benchmarks: Below .270 is unlucky. .300 is average. .330 is above average. Above .350 is often unsustainable.

Sprint Speed

Sprint speed measures a player's raw speed in feet per second. Faster players beat out infield hits, take extra bases, and steal bases more successfully.

Prop Application: Sprint speed affects hits props (infield hits), runs scored props (extra bases), and stolen base props directly. Fast players outperform their contact metrics.

Benchmarks: Below 26 ft/s is slow. 27 ft/s is average. 28.5 ft/s is above average. 30+ ft/s is elite.

xBA and xSLG (Expected Stats)

Expected batting average (xBA) and expected slugging (xSLG) calculate what a hitter's stats should be based on exit velocity and launch angle of batted balls, removing fielding and luck.

Prop Application: Compare xBA/xSLG to actual BA/SLG. If actual is below expected, the hitter is due for positive regression. If actual exceeds expected, regression down is likely.

Large gaps between expected and actual stats create prop value on the regression side.